diff --git a/notebooks/HF-API-Ax.ipynb b/notebooks/HF-API-Ax.ipynb
deleted file mode 100644
index 9e6dcba..0000000
--- a/notebooks/HF-API-Ax.ipynb
+++ /dev/null
@@ -1,3907 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "[INFO 09-08 21:30:57] ax.utils.notebook.plotting: Injecting Plotly library into cell. Do not overwrite or delete cell.\n",
- "[INFO 09-08 21:30:57] ax.utils.notebook.plotting: Please see\n",
- " (https://ax.dev/tutorials/visualizations.html#Fix-for-plots-that-are-not-rendering)\n",
- " if visualizations are not rendering.\n"
- ]
- },
- {
- "data": {
- "text/html": [
- " \n",
- " "
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Loaded as API: https://accelerationconsortium-crabnet-hyperparameter.hf.space ✔\n"
- ]
- }
- ],
- "source": [
- "import torch\n",
- "from ax.service.utils.instantiation import ObjectiveProperties\n",
- "from ax.utils.notebook.plotting import init_notebook_plotting, render\n",
- "from botorch.test_functions.multi_objective import BraninCurrin\n",
- "import numpy as np\n",
- "import pandas as pd\n",
- "from ax.service.ax_client import AxClient, ObjectiveProperties\n",
- "\n",
- "round = 50\n",
- "init_notebook_plotting()\n",
- "# load the Advanced Optimization from AC huggingface\n",
- "from gradio_client import Client\n",
- "client = Client(\"AccelerationConsortium/crabnet-hyperparameter\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "metadata": {},
- "outputs": [],
- "source": [
- "# def adv_opt(x1, x2, x3, x4, x5, x6, x7, x8, x9, x10, x11, x12, x13, x14, x15, x16, x17, x18, x19, x20, c1, c2, c3): \n",
- "# result = client.predict(\n",
- "# x1, # float (numeric value between 0.0 and 1.0) in 'x1' Slider component\n",
- "# \t\tx2,\t# float (numeric value between 0.0 and 1.0)\tin 'x2' Slider component\n",
- "# \t\tx3,\t# float (numeric value between 0.0 and 1.0) in 'x3' Slider component\n",
- "# \t\tx4,\t# float (numeric value between 0.0 and 1.0) in 'x4' Slider component\n",
- "# \t\tx5,\t# float (numeric value between 0.0 and 1.0) in 'x5' Slider component\n",
- "# \t\tx6,\t# float (numeric value between 0.0 and 1.0) in 'x6' Slider component\n",
- "# \t\tx7,\t# float (numeric value between 0.0 and 1.0) in 'x7' Slider component\n",
- "# \t\tx8,\t# float (numeric value between 0.0 and 1.0) in 'x8' Slider component\n",
- "# \t\tx9,\t# float (numeric value between 0.0 and 1.0) in 'x9' Slider component\n",
- "# \t\tx10,\t# float (numeric value between 0.0 and 1.0) in 'x10' Slider component\n",
- "# \t\tx11,\t# float (numeric value between 0.0 and 1.0) in 'x11' Slider component\n",
- "# \t\tx12,\t# float (numeric value between 0.0 and 1.0) in 'x12' Slider component\n",
- "# \t\tx13,\t# float (numeric value between 0.0 and 1.0) in 'x13' Slider component\n",
- "# \t\tx14,\t# float (numeric value between 0.0 and 1.0) in 'x14' Slider component\n",
- "# \t\tx15,\t# float (numeric value between 0.0 and 1.0) in 'x15' Slider component\n",
- "# \t\tx16,\t# float (numeric value between 0.0 and 1.0) in 'x16' Slider component\n",
- "# \t\tx17,\t# float (numeric value between 0.0 and 1.0) in 'x17' Slider component\n",
- "# \t\tx18,\t# float (numeric value between 0.0 and 1.0) in 'x18' Slider component\n",
- "# \t\tx19,\t# float (numeric value between 0.0 and 1.0) in 'x19' Slider component\n",
- "# \t\tx20,\t# float (numeric value between 0.0 and 1.0) in 'x20' Slider component\n",
- "# \t\tc1,\t# Literal['c1_0', 'c1_1'] in 'c1' Radio component\n",
- "# \t\tc2,\t# Literal['c2_0', 'c2_1'] in 'c2' Radio component\n",
- "# \t\tc3,\t# Literal['c3_0', 'c3_1', 'c3_2'] in 'c3' Radio component\n",
- "# \t\t0.5,\t# float (numeric value between 0.0 and 1.0) in 'fidelity1' Slider component\n",
- "# \t\tapi_name=\"/predict\",\n",
- "# )\n",
- "# return result['data'][0][0]\t\t\t# return y1 value only\n",
- "\n",
- "# Because the parameteraization in BayBE is weird, assign values to x1, x10, x19, x20 \n",
- "def adv_opt(c1, c2, c3, x2, x3, x4, x5, x6, x7, x8, x9, x11, x12, x13, x14, x15, x16, x17, x18): \n",
- " result = client.predict(\n",
- " \t0.669938, # float (numeric value between 0.0 and 1.0) in 'x1' Slider component\n",
- "\t\tx2,\t# float (numeric value between 0.0 and 1.0)\tin 'x2' Slider component\n",
- "\t\tx3,\t# float (numeric value between 0.0 and 1.0) in 'x3' Slider component\n",
- "\t\tx4,\t# float (numeric value between 0.0 and 1.0) in 'x4' Slider component\n",
- "\t\tx5,\t# float (numeric value between 0.0 and 1.0) in 'x5' Slider component\n",
- "\t\tx6,\t# float (numeric value between 0.0 and 1.0) in 'x6' Slider component\n",
- "\t\tx7,\t# float (numeric value between 0.0 and 1.0) in 'x7' Slider component\n",
- "\t\tx8,\t# float (numeric value between 0.0 and 1.0) in 'x8' Slider component\n",
- "\t\tx9,\t# float (numeric value between 0.0 and 1.0) in 'x9' Slider component\n",
- "\t\t0.5291,\t# float (numeric value between 0.0 and 1.0) in 'x10' Slider component\n",
- "\t\tx11,\t# float (numeric value between 0.0 and 1.0) in 'x11' Slider component\n",
- "\t\tx12,\t# float (numeric value between 0.0 and 1.0000000000000002) in 'x12' Slider component\n",
- "\t\tx13,\t# float (numeric value between 0.0 and 1.0) in 'x13' Slider component\n",
- "\t\tx14,\t# float (numeric value between 0.0 and 1.0) in 'x14' Slider component\n",
- "\t\tx15,\t# float (numeric value between 0.0 and 1.0) in 'x15' Slider component\n",
- "\t\tx16,\t# float (numeric value between 0.0 and 1.0) in 'x16' Slider component\n",
- "\t\tx17,\t# float (numeric value between 0.0 and 1.0) in 'x17' Slider component\n",
- "\t\tx18,\t# float (numeric value between 0.0 and 1.0) in 'x18' Slider component\n",
- "\t\t0.079598,\t# float (numeric value between 0.0 and 0.9999999999999998) in 'x19' Slider component\n",
- "\t\t0.632394,\t# float (numeric value between 0.0 and 0.9999999999999998) in 'x20' Slider component\n",
- "\t\tc1,\t# Literal['c1_0', 'c1_1'] in 'c1' Radio component\n",
- "\t\tc2,\t# Literal['c2_0', 'c2_1'] in 'c2' Radio component\n",
- "\t\tc3,\t# Literal['c3_0', 'c3_1', 'c3_2'] in 'c3' Radio component\n",
- "\t\t0.5,\t# float (numeric value between 0.0 and 1.0) in 'fidelity1' Slider component\n",
- "\t\tapi_name=\"/predict\",\n",
- " )\n",
- " return result['data'][0][0]\t\t\t# return y1 value only\n"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "[INFO 09-08 21:31:00] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:31:00] ax.service.ax_client: Random seed set to 17. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:31:00] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:31:00] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:31:00] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:31:00] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:31:00] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:31:00] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:31:00] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:31:00] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:00] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.918383, 'x3': 0.854172, 'x4': 0.496465, 'x5': 0.138122, 'x6': 0.812023, 'x7': 0.538569, 'x8': 0.07776, 'x9': 0.308121, 'x11': 0.209567, 'x12': 0.213951, 'x13': 0.756288, 'x14': 0.228655, 'x15': 0.0343, 'x16': 0.579686, 'x17': 0.977009, 'x18': 0.285267, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:01] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.373159, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:01] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.094776, 'x3': 0.313401, 'x4': 0.777026, 'x5': 0.835036, 'x6': 0.34305, 'x7': 0.155256, 'x8': 0.612845, 'x9': 0.883873, 'x11': 0.551747, 'x12': 0.772632, 'x13': 0.180531, 'x14': 0.523466, 'x15': 0.583691, 'x16': 0.209077, 'x17': 0.024415, 'x18': 0.517168, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:03] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.505235, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:03] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.270763, 'x3': 0.650242, 'x4': 0.040359, 'x5': 0.398209, 'x6': 0.052638, 'x7': 0.415842, 'x8': 0.308785, 'x9': 0.643104, 'x11': 0.958537, 'x12': 0.537186, 'x13': 0.275821, 'x14': 0.905067, 'x15': 0.484665, 'x16': 0.928947, 'x17': 0.373057, 'x18': 0.079273, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:04] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.604472, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:04] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.199938, 'x3': 0.908766, 'x4': 0.586335, 'x5': 0.943143, 'x6': 0.423696, 'x7': 0.324186, 'x8': 0.127232, 'x9': 0.460736, 'x11': 0.05649, 'x12': 0.278933, 'x13': 0.895226, 'x14': 0.683979, 'x15': 0.154969, 'x16': 0.424672, 'x17': 0.146144, 'x18': 0.677995, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:05] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.369298, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:05] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.508758, 'x3': 0.29837, 'x4': 0.255398, 'x5': 0.931286, 'x6': 0.112039, 'x7': 0.596961, 'x8': 0.719981, 'x9': 0.761019, 'x11': 0.681326, 'x12': 0.184747, 'x13': 0.462213, 'x14': 0.252058, 'x15': 0.189768, 'x16': 0.631745, 'x17': 0.096653, 'x18': 0.490498, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:06] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.454204, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:06] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.661406, 'x3': 0.957003, 'x4': 0.068617, 'x5': 0.792449, 'x6': 0.152525, 'x7': 0.928001, 'x8': 0.016137, 'x9': 0.333581, 'x11': 0.176304, 'x12': 0.67933, 'x13': 0.7394, 'x14': 0.412571, 'x15': 0.509101, 'x16': 0.970876, 'x17': 0.232782, 'x18': 0.32967, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:07] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.429482, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:07] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.351715, 'x3': 0.493867, 'x4': 0.65777, 'x5': 0.235396, 'x6': 0.746964, 'x7': 0.265381, 'x8': 0.543623, 'x9': 0.975587, 'x11': 0.58489, 'x12': 0.37071, 'x13': 0.323761, 'x14': 0.832375, 'x15': 0.124989, 'x16': 0.34929, 'x17': 0.780439, 'x18': 0.59777, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:09] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.366566, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:09] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.954138, 'x3': 0.010549, 'x4': 0.864002, 'x5': 0.480104, 'x6': 0.490729, 'x7': 0.626392, 'x8': 0.842993, 'x9': 0.076211, 'x11': 0.333982, 'x12': 0.881449, 'x13': 0.835482, 'x14': 0.031949, 'x15': 0.418635, 'x16': 0.127972, 'x17': 0.384143, 'x18': 0.766776, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:10] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.315113, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:10] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.045114, 'x3': 0.048503, 'x4': 0.506492, 'x5': 0.039105, 'x6': 0.021122, 'x7': 0.905281, 'x8': 0.099805, 'x9': 0.111605, 'x11': 0.874291, 'x12': 0.942433, 'x13': 0.21782, 'x14': 0.752589, 'x15': 0.161366, 'x16': 0.729517, 'x17': 0.299415, 'x18': 0.54529, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:11] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.819908, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:11] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.491989, 'x3': 0.260621, 'x4': 0.116814, 'x5': 0.619172, 'x6': 0.392193, 'x7': 0.872211, 'x8': 0.461213, 'x9': 0.803751, 'x11': 0.143632, 'x12': 0.248755, 'x13': 0.579875, 'x14': 0.53129, 'x15': 0.448979, 'x16': 0.233298, 'x17': 0.21215, 'x18': 0.196327, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:13] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.344892, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:13] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.128426, 'x3': 0.706869, 'x4': 0.817755, 'x5': 0.182495, 'x6': 0.245322, 'x7': 0.572319, 'x8': 0.648406, 'x9': 0.543543, 'x11': 0.361708, 'x12': 0.452642, 'x13': 0.987698, 'x14': 0.912857, 'x15': 0.607659, 'x16': 0.890396, 'x17': 0.435788, 'x18': 0.634463, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:14] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.502429, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:14] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.827035, 'x3': 0.243734, 'x4': 0.408862, 'x5': 0.844374, 'x6': 0.652339, 'x7': 0.237824, 'x8': 0.167826, 'x9': 0.154298, 'x11': 0.890649, 'x12': 0.503633, 'x13': 0.075968, 'x14': 0.332913, 'x15': 0.023997, 'x16': 0.258067, 'x17': 0.577432, 'x18': 0.433814, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:15] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.330072, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:15] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.800321, 'x3': 0.900345, 'x4': 0.791447, 'x5': 0.506272, 'x6': 0.08104, 'x7': 0.083596, 'x8': 0.932876, 'x9': 0.480018, 'x11': 0.518928, 'x12': 0.342007, 'x13': 0.027537, 'x14': 0.404742, 'x15': 0.397597, 'x16': 0.963687, 'x17': 0.045302, 'x18': 0.883825, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:16] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.558526, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:16] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.385411, 'x3': 0.604008, 'x4': 0.749282, 'x5': 0.778107, 'x6': 0.836524, 'x7': 0.964076, 'x8': 0.696113, 'x9': 0.564956, 'x11': 0.266067, 'x12': 0.909389, 'x13': 0.500191, 'x14': 0.729102, 'x15': 0.066834, 'x16': 0.55905, 'x17': 0.679764, 'x18': 0.746312, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:18] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.400291, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:18] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.570104, 'x3': 0.063237, 'x4': 0.02398, 'x5': 0.194075, 'x6': 0.305004, 'x7': 0.346388, 'x8': 0.239244, 'x9': 0.234458, 'x11': 0.986414, 'x12': 0.108459, 'x13': 0.436155, 'x14': 0.024149, 'x15': 0.54967, 'x16': 0.183559, 'x17': 0.321659, 'x18': 0.446961, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:19] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.425661, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:19] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.728977, 'x3': 0.65893, 'x4': 0.339152, 'x5': 0.082456, 'x6': 0.459747, 'x7': 0.179441, 'x8': 0.5051, 'x9': 0.670697, 'x11': 0.499222, 'x12': 0.599135, 'x13': 0.643511, 'x14': 0.184418, 'x15': 0.244017, 'x16': 0.46797, 'x17': 0.443144, 'x18': 0.357788, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:20] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.363841, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:20] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.299478, 'x3': 0.864804, 'x4': 0.542755, 'x5': 0.600574, 'x6': 0.189275, 'x7': 0.747507, 'x8': 0.562573, 'x9': 0.218967, 'x11': 0.101001, 'x12': 0.531072, 'x13': 0.052852, 'x14': 0.050092, 'x15': 0.217022, 'x16': 0.031977, 'x17': 0.810067, 'x18': 0.001278, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:21] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.394109, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:21] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.580545, 'x3': 0.935244, 'x4': 0.390437, 'x5': 0.295243, 'x6': 0.577694, 'x7': 0.39256, 'x8': 0.63865, 'x9': 0.012147, 'x11': 0.132983, 'x12': 0.962296, 'x13': 0.160983, 'x14': 0.598674, 'x15': 0.097246, 'x16': 0.941385, 'x17': 0.062812, 'x18': 0.89364, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:23] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.335251, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:23] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.405373, 'x3': 0.398379, 'x4': 0.851575, 'x5': 0.738435, 'x6': 0.046159, 'x7': 0.789545, 'x8': 0.173674, 'x9': 0.686425, 'x11': 0.603795, 'x12': 0.020863, 'x13': 0.77584, 'x14': 0.14762, 'x15': 0.520722, 'x16': 0.316879, 'x17': 0.922991, 'x18': 0.162716, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:24] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.491085, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:24] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.229813, 'x3': 0.576926, 'x4': 0.088852, 'x5': 0.051756, 'x6': 0.318278, 'x7': 0.530608, 'x8': 0.998444, 'x9': 0.911599, 'x11': 0.885982, 'x12': 0.285545, 'x13': 0.680512, 'x14': 0.267486, 'x15': 0.422635, 'x16': 0.53649, 'x17': 0.709129, 'x18': 0.724756, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:25] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.402453, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:25] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.146672, 'x3': 0.295551, 'x4': 0.705206, 'x5': 0.330262, 'x6': 0.887604, 'x7': 0.680931, 'x8': 0.233343, 'x9': 0.704054, 'x11': 0.508152, 'x12': 0.619059, 'x13': 0.727665, 'x14': 0.46431, 'x15': 0.061974, 'x16': 0.242003, 'x17': 0.178772, 'x18': 0.206142, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:26] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.407765, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:26] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.546018, 'x3': 0.216621, 'x4': 0.756909, 'x5': 0.070907, 'x6': 0.1314, 'x7': 0.304601, 'x8': 0.4037, 'x9': 0.369116, 'x11': 0.261028, 'x12': 0.129804, 'x13': 0.239381, 'x14': 0.671484, 'x15': 0.480612, 'x16': 0.267001, 'x17': 0.532685, 'x18': 0.412258, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:28] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.527936, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:28] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.627621, 'x3': 0.562189, 'x4': 0.567229, 'x5': 0.213193, 'x6': 0.101656, 'x7': 0.221578, 'x8': 0.856107, 'x9': 0.788236, 'x11': 0.756281, 'x12': 0.639066, 'x13': 0.962201, 'x14': 0.511703, 'x15': 0.788233, 'x16': 0.114921, 'x17': 0.669795, 'x18': 0.251918, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:29] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.550557, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:29] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.327939, 'x3': 0.021417, 'x4': 0.15928, 'x5': 0.750196, 'x6': 0.508621, 'x7': 0.589237, 'x8': 0.328654, 'x9': 0.396184, 'x11': 0.472698, 'x12': 0.314812, 'x13': 0.101463, 'x14': 0.243992, 'x15': 0.329628, 'x16': 0.736498, 'x17': 0.340499, 'x18': 0.551268, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:30] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.372527, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:30] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.991093, 'x3': 0.475202, 'x4': 0.365391, 'x5': 0.525973, 'x6': 0.252648, 'x7': 0.458786, 'x8': 0.034274, 'x9': 0.559308, 'x11': 0.725681, 'x12': 0.93689, 'x13': 0.620997, 'x14': 0.8879, 'x15': 0.127784, 'x16': 0.770063, 'x17': 0.948106, 'x18': 0.81378, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:31] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.385687, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:31] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.009624, 'x3': 0.466785, 'x4': 0.004096, 'x5': 0.962112, 'x6': 0.220303, 'x7': 0.198857, 'x8': 0.77546, 'x9': 0.500952, 'x11': 0.200807, 'x12': 0.996858, 'x13': 0.487679, 'x14': 0.171038, 'x15': 0.386025, 'x16': 0.371605, 'x17': 0.860449, 'x18': 0.623057, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:33] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.925302, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:33] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.372639, 'x3': 0.504676, 'x4': 0.803523, 'x5': 0.275285, 'x6': 0.385963, 'x7': 0.496613, 'x8': 0.083671, 'x9': 0.776755, 'x11': 0.293792, 'x12': 0.701114, 'x13': 0.079894, 'x14': 0.290932, 'x15': 0.545613, 'x16': 0.528932, 'x17': 0.521591, 'x18': 0.061264, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:34] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.41773, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:34] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.453265, 'x3': 0.225305, 'x4': 0.614296, 'x5': 0.385928, 'x6': 0.349293, 'x7': 0.040543, 'x8': 0.660558, 'x9': 0.318098, 'x11': 0.783151, 'x12': 0.194812, 'x13': 0.872699, 'x14': 0.388217, 'x15': 0.224327, 'x16': 0.86855, 'x17': 0.651113, 'x18': 0.149826, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:35] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.429438, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:35] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.160563, 'x3': 0.812025, 'x4': 0.320272, 'x5': 0.824124, 'x6': 0.014657, 'x7': 0.279957, 'x8': 0.480312, 'x9': 0.091947, 'x11': 0.688011, 'x12': 0.490494, 'x13': 0.717808, 'x14': 0.011013, 'x15': 0.812779, 'x16': 0.023695, 'x17': 0.997803, 'x18': 0.712717, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:37] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.798805, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:37] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.852581, 'x3': 0.271253, 'x4': 0.906466, 'x5': 0.142194, 'x6': 0.609166, 'x7': 0.913242, 'x8': 0.96092, 'x9': 0.731145, 'x11': 0.034059, 'x12': 0.557118, 'x13': 0.345354, 'x14': 0.743553, 'x15': 0.303611, 'x16': 0.656014, 'x17': 0.012493, 'x18': 0.480819, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:38] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.352291, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:38] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.769958, 'x3': 0.614876, 'x4': 0.289937, 'x5': 0.491535, 'x6': 0.162887, 'x7': 0.7512, 'x8': 0.194713, 'x9': 0.899631, 'x11': 0.407744, 'x12': 0.35151, 'x13': 0.297228, 'x14': 0.550744, 'x15': 0.180987, 'x16': 0.075501, 'x17': 0.607312, 'x18': 0.962324, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:39] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.38684, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:39] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.700751, 'x3': 0.827059, 'x4': 0.837764, 'x5': 0.911468, 'x6': 0.284119, 'x7': 0.9718, 'x8': 0.368263, 'x9': 0.21531, 'x11': 0.57601, 'x12': 0.590114, 'x13': 0.936136, 'x14': 0.766948, 'x15': 0.460604, 'x16': 0.570996, 'x17': 0.881131, 'x18': 0.310555, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:41] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.356471, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:41] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.114014, 'x3': 0.685171, 'x4': 0.63762, 'x5': 0.687486, 'x6': 0.539633, 'x7': 0.10713, 'x8': 0.010299, 'x9': 0.864685, 'x11': 0.326933, 'x12': 0.157498, 'x13': 0.408794, 'x14': 0.099334, 'x15': 0.004865, 'x16': 0.919999, 'x17': 0.26581, 'x18': 0.073434, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:42] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.423064, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:42] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.931517, 'x3': 0.148307, 'x4': 0.104621, 'x5': 0.349122, 'x6': 0.070674, 'x7': 0.70724, 'x8': 0.553369, 'x9': 0.445213, 'x11': 0.918587, 'x12': 0.856927, 'x13': 0.527556, 'x14': 0.648028, 'x15': 0.611662, 'x16': 0.290609, 'x17': 0.719992, 'x18': 0.873762, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:43] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.448514, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:43] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.927659, 'x3': 0.568792, 'x4': 0.667811, 'x5': 0.535044, 'x6': 0.410898, 'x7': 0.937045, 'x8': 0.65345, 'x9': 0.408211, 'x11': 0.635549, 'x12': 0.138626, 'x13': 0.458225, 'x14': 0.018916, 'x15': 0.347888, 'x16': 0.189548, 'x17': 0.328252, 'x18': 0.525979, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:45] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.378066, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:45] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.26246, 'x3': 0.926774, 'x4': 0.873917, 'x5': 0.805945, 'x6': 0.670562, 'x7': 0.04799, 'x8': 0.983094, 'x9': 0.510788, 'x11': 0.384641, 'x12': 0.610299, 'x13': 0.946504, 'x14': 0.851271, 'x15': 0.179136, 'x16': 0.285888, 'x17': 0.943689, 'x18': 0.859049, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:31:46] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.502685, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:46] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.689095, 'x3': 0.405534, 'x4': 0.399574, 'x5': 0.221885, 'x6': 0.201586, 'x7': 0.633429, 'x8': 0.455679, 'x9': 0.181267, 'x11': 0.855205, 'x12': 0.434369, 'x13': 0.11678, 'x14': 0.396059, 'x15': 0.689224, 'x16': 0.909419, 'x17': 0.053847, 'x18': 0.088025, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:31:48] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.367713, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:31:48] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.605539, 'x3': 0.872299, 'x4': 0.213796, 'x5': 0.11121, 'x6': 0.032202, 'x7': 0.841482, 'x8': 0.784519, 'x9': 0.725842, 'x11': 0.350217, 'x12': 0.928007, 'x13': 0.839837, 'x14': 0.298775, 'x15': 0.010502, 'x16': 0.695296, 'x17': 0.183125, 'x18': 0.247998, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:31:49] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.362655, None)}.\n",
- "[INFO 09-08 21:31:59] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.956438, 'x3': 0.111379, 'x4': 0.812701, 'x5': 0.500298, 'x6': 0.492757, 'x7': 0.677446, 'x8': 0.771439, 'x9': 0.126318, 'x11': 0.407, 'x12': 0.734564, 'x13': 0.730297, 'x14': 0.039945, 'x15': 0.38149, 'x16': 0.150973, 'x17': 0.37304, 'x18': 0.715329, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:32:00] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.307375, None)}.\n",
- "[INFO 09-08 21:32:10] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.860171, 'x3': 0.248226, 'x4': 0.48701, 'x5': 0.735151, 'x6': 0.598088, 'x7': 0.369668, 'x8': 0.287701, 'x9': 0.174782, 'x11': 0.788171, 'x12': 0.523916, 'x13': 0.219193, 'x14': 0.280794, 'x15': 0.116662, 'x16': 0.263392, 'x17': 0.522492, 'x18': 0.486801, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:32:11] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.310877, None)}.\n",
- "[INFO 09-08 21:32:21] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.930167, 'x3': 0.023511, 'x4': 0.779489, 'x5': 0.544543, 'x6': 0.525957, 'x7': 0.522998, 'x8': 0.708293, 'x9': 0.073934, 'x11': 0.432641, 'x12': 0.854394, 'x13': 0.70412, 'x14': 0.104066, 'x15': 0.344059, 'x16': 0.158902, 'x17': 0.429973, 'x18': 0.711241, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:32:23] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.321867, None)}.\n",
- "[INFO 09-08 21:32:32] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.862724, 'x3': 0.139132, 'x4': 0.515433, 'x5': 0.817205, 'x6': 0.658181, 'x7': 0.254809, 'x8': 0.296886, 'x9': 0.092925, 'x11': 0.781938, 'x12': 0.635044, 'x13': 0.227684, 'x14': 0.272877, 'x15': 0.068097, 'x16': 0.197792, 'x17': 0.563024, 'x18': 0.518522, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:32:34] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.343778, None)}.\n",
- "[INFO 09-08 21:32:43] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.878259, 'x3': 0.284985, 'x4': 0.433807, 'x5': 0.721021, 'x6': 0.571453, 'x7': 0.33806, 'x8': 0.17685, 'x9': 0.227963, 'x11': 0.804552, 'x12': 0.588611, 'x13': 0.228353, 'x14': 0.41233, 'x15': 0.076675, 'x16': 0.357271, 'x17': 0.614142, 'x18': 0.518607, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:32:45] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.319661, None)}.\n",
- "[INFO 09-08 21:32:54] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.823379, 'x3': 0.216077, 'x4': 0.436577, 'x5': 0.689994, 'x6': 0.572413, 'x7': 0.314463, 'x8': 0.229818, 'x9': 0.127721, 'x11': 0.843564, 'x12': 0.577634, 'x13': 0.150951, 'x14': 0.352835, 'x15': 0.16683, 'x16': 0.398911, 'x17': 0.484884, 'x18': 0.394275, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:32:55] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.336024, None)}.\n",
- "[INFO 09-08 21:33:04] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.914585, 'x3': 0.237758, 'x4': 0.607464, 'x5': 0.602007, 'x6': 0.524895, 'x7': 0.53995, 'x8': 0.462271, 'x9': 0.19872, 'x11': 0.622153, 'x12': 0.605939, 'x13': 0.451757, 'x14': 0.221416, 'x15': 0.231095, 'x16': 0.263897, 'x17': 0.478979, 'x18': 0.596649, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:33:05] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.308017, None)}.\n",
- "[INFO 09-08 21:33:14] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.934716, 'x3': 0.20251, 'x4': 0.694068, 'x5': 0.549276, 'x6': 0.508729, 'x7': 0.636728, 'x8': 0.613214, 'x9': 0.176557, 'x11': 0.511932, 'x12': 0.642241, 'x13': 0.58054, 'x14': 0.123013, 'x15': 0.301487, 'x16': 0.205728, 'x17': 0.424533, 'x18': 0.654407, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:33:15] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.302182, None)}.\n",
- "[INFO 09-08 21:33:24] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.968173, 'x3': 0.1717, 'x4': 0.740744, 'x5': 0.47268, 'x6': 0.45295, 'x7': 0.664558, 'x8': 0.627649, 'x9': 0.194822, 'x11': 0.442202, 'x12': 0.767855, 'x13': 0.709371, 'x14': 0.188279, 'x15': 0.343718, 'x16': 0.282544, 'x17': 0.455, 'x18': 0.725827, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:33:26] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.323059, None)}.\n",
- "[INFO 09-08 21:33:34] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.94461, 'x3': 0.187574, 'x4': 0.711953, 'x5': 0.567657, 'x6': 0.523468, 'x7': 0.610313, 'x8': 0.582368, 'x9': 0.162645, 'x11': 0.564288, 'x12': 0.60088, 'x13': 0.536756, 'x14': 0.124445, 'x15': 0.28704, 'x16': 0.204066, 'x17': 0.407337, 'x18': 0.622444, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:33:36] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.304211, None)}.\n",
- "[INFO 09-08 21:33:44] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.646949, 'x3': 0.897648, 'x4': 0.37962, 'x5': 0.410046, 'x6': 0.555796, 'x7': 0.533244, 'x8': 0.60165, 'x9': 0.120206, 'x11': 0.128197, 'x12': 0.807416, 'x13': 0.310599, 'x14': 0.578117, 'x15': 0.178043, 'x16': 0.825023, 'x17': 0.176347, 'x18': 0.726304, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:33:45] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.325664, None)}.\n",
- "[INFO 09-08 21:33:55] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.92365, 'x3': 0.23627, 'x4': 0.63906, 'x5': 0.573198, 'x6': 0.544761, 'x7': 0.63405, 'x8': 0.579734, 'x9': 0.177951, 'x11': 0.520451, 'x12': 0.598802, 'x13': 0.519354, 'x14': 0.111317, 'x15': 0.260558, 'x16': 0.177839, 'x17': 0.432569, 'x18': 0.63863, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:33:56] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.30144, None)}.\n",
- "[WARNING 09-08 21:33:56] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:33:56] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:33:56] ax.service.ax_client: Random seed set to 23. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:33:56] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:33:56] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:33:56] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:33:56] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:33:56] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:33:56] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:33:56] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:33:56] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:33:56] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.576151, 'x3': 0.432452, 'x4': 0.051388, 'x5': 0.125111, 'x6': 0.037974, 'x7': 0.766262, 'x8': 0.245618, 'x9': 0.422158, 'x11': 0.732171, 'x12': 0.524107, 'x13': 0.431736, 'x14': 0.205192, 'x15': 0.201047, 'x16': 0.318235, 'x17': 0.076495, 'x18': 0.798657, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:33:57] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.464081, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:33:57] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.665069, 'x3': 0.991722, 'x4': 0.25624, 'x5': 0.074461, 'x6': 0.147753, 'x7': 0.648021, 'x8': 0.857335, 'x9': 0.825165, 'x11': 0.387583, 'x12': 0.021397, 'x13': 0.546658, 'x14': 0.036905, 'x15': 0.740772, 'x16': 0.141122, 'x17': 0.237186, 'x18': 0.993471, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:33:58] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.463374, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:33:58] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.944589, 'x3': 0.021487, 'x4': 0.60415, 'x5': 0.714668, 'x6': 0.298053, 'x7': 0.899846, 'x8': 0.368484, 'x9': 0.527033, 'x11': 0.121166, 'x12': 0.348109, 'x13': 0.902979, 'x14': 0.400464, 'x15': 0.358089, 'x16': 0.65089, 'x17': 0.479038, 'x18': 0.286038, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:00] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.391413, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:00] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.887583, 'x3': 0.76985, 'x4': 0.238045, 'x5': 0.9763, 'x6': 0.663456, 'x7': 0.857257, 'x8': 0.762672, 'x9': 0.792119, 'x11': 0.486432, 'x12': 0.612743, 'x13': 0.950241, 'x14': 0.309649, 'x15': 0.119446, 'x16': 0.462103, 'x17': 0.796464, 'x18': 0.912635, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:01] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.40182, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:01] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.099867, 'x3': 0.552775, 'x4': 0.356293, 'x5': 0.666413, 'x6': 0.063668, 'x7': 0.097997, 'x8': 0.618976, 'x9': 0.085031, 'x11': 0.981687, 'x12': 0.171674, 'x13': 0.272638, 'x14': 0.626312, 'x15': 0.289746, 'x16': 0.209584, 'x17': 0.253602, 'x18': 0.672627, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:02] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.794423, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:02] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.481429, 'x3': 0.901241, 'x4': 0.799687, 'x5': 0.235981, 'x6': 0.334854, 'x7': 0.231989, 'x8': 0.995134, 'x9': 0.997036, 'x11': 0.371657, 'x12': 0.956124, 'x13': 0.798401, 'x14': 0.94663, 'x15': 0.136486, 'x16': 0.759524, 'x17': 0.163499, 'x18': 0.162053, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:03] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.404838, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:03] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.826029, 'x3': 0.909667, 'x4': 0.534676, 'x5': 0.310862, 'x6': 0.018861, 'x7': 0.44262, 'x8': 0.414911, 'x9': 0.951227, 'x11': 0.545069, 'x12': 0.887879, 'x13': 0.09742, 'x14': 0.021084, 'x15': 0.318178, 'x16': 0.174904, 'x17': 0.032665, 'x18': 0.45668, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:05] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.524309, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:05] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.163557, 'x3': 0.626124, 'x4': 0.934175, 'x5': 0.112798, 'x6': 0.73927, 'x7': 0.699905, 'x8': 0.21675, 'x9': 0.174062, 'x11': 0.047863, 'x12': 0.329627, 'x13': 0.681547, 'x14': 0.915849, 'x15': 0.022657, 'x16': 0.43429, 'x17': 0.513027, 'x18': 0.193295, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:06] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.401543, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:06] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.694711, 'x3': 0.515304, 'x4': 0.122784, 'x5': 0.849238, 'x6': 0.254418, 'x7': 0.325111, 'x8': 0.04107, 'x9': 0.099529, 'x11': 0.18705, 'x12': 0.236242, 'x13': 0.567857, 'x14': 0.341407, 'x15': 0.225226, 'x16': 0.855742, 'x17': 0.38055, 'x18': 0.943938, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:07] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.386711, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:07] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.349988, 'x3': 0.046515, 'x4': 0.870869, 'x5': 0.769681, 'x6': 0.113772, 'x7': 0.67359, 'x8': 0.791539, 'x9': 0.540368, 'x11': 0.795563, 'x12': 0.306964, 'x13': 0.202105, 'x14': 0.569203, 'x15': 0.156969, 'x16': 0.281587, 'x17': 0.356042, 'x18': 0.080772, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:08] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.462858, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:08] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.231307, 'x3': 0.37838, 'x4': 0.287094, 'x5': 0.328048, 'x6': 0.34701, 'x7': 0.554773, 'x8': 0.664405, 'x9': 0.377634, 'x11': 0.436567, 'x12': 0.568899, 'x13': 0.726848, 'x14': 0.764479, 'x15': 0.253714, 'x16': 0.749045, 'x17': 0.195597, 'x18': 0.569832, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:10] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.392894, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:10] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.756326, 'x3': 0.157397, 'x4': 0.182519, 'x5': 0.002169, 'x6': 0.879904, 'x7': 0.298446, 'x8': 0.966265, 'x9': 0.748543, 'x11': 0.90643, 'x12': 0.15059, 'x13': 0.049253, 'x14': 0.174381, 'x15': 0.07928, 'x16': 0.985021, 'x17': 0.723078, 'x18': 0.829884, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:11] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.403539, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:11] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.377556, 'x3': 0.596622, 'x4': 0.57151, 'x5': 0.96096, 'x6': 0.19256, 'x7': 0.803671, 'x8': 0.184461, 'x9': 0.208878, 'x11': 0.078106, 'x12': 0.803781, 'x13': 0.839032, 'x14': 0.672892, 'x15': 0.652281, 'x16': 0.239279, 'x17': 0.453261, 'x18': 0.150599, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:12] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.43241, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:12] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.394096, 'x3': 0.417802, 'x4': 0.88303, 'x5': 0.553343, 'x6': 0.604331, 'x7': 0.917985, 'x8': 0.918394, 'x9': 0.022617, 'x11': 0.554038, 'x12': 0.232824, 'x13': 0.554212, 'x14': 0.107323, 'x15': 0.094908, 'x16': 0.724921, 'x17': 0.138187, 'x18': 0.580105, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:13] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.379237, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:13] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.772864, 'x3': 0.851594, 'x4': 0.370999, 'x5': 0.48109, 'x6': 0.291987, 'x7': 0.417398, 'x8': 0.201143, 'x9': 0.558888, 'x11': 0.461432, 'x12': 0.815732, 'x13': 0.342557, 'x14': 0.607897, 'x15': 0.667903, 'x16': 0.472648, 'x17': 0.931446, 'x18': 0.400381, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:15] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.377832, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:15] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.618332, 'x3': 0.134329, 'x4': 0.522594, 'x5': 0.87041, 'x6': 0.137233, 'x7': 0.161658, 'x8': 0.712167, 'x9': 0.854598, 'x11': 0.039497, 'x12': 0.549625, 'x13': 0.232082, 'x14': 0.954732, 'x15': 0.300586, 'x16': 0.978506, 'x17': 0.657856, 'x18': 0.816689, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:16] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.550584, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:16] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.654119, 'x3': 0.692246, 'x4': 0.78698, 'x5': 0.929131, 'x6': 0.059726, 'x7': 0.283926, 'x8': 0.327302, 'x9': 0.398108, 'x11': 0.821462, 'x12': 0.062097, 'x13': 0.86765, 'x14': 0.787548, 'x15': 0.75842, 'x16': 0.559205, 'x17': 0.528386, 'x18': 0.887487, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:17] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.583915, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:17] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.987872, 'x3': 0.286473, 'x4': 0.071395, 'x5': 0.281739, 'x6': 0.401675, 'x7': 0.043329, 'x8': 0.839428, 'x9': 0.188473, 'x11': 0.681509, 'x12': 0.326209, 'x13': 0.698336, 'x14': 0.65007, 'x15': 0.141348, 'x16': 0.053348, 'x17': 0.755344, 'x18': 0.329583, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:19] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.385724, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:19] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.929886, 'x3': 0.538125, 'x4': 0.703613, 'x5': 0.028239, 'x6': 0.512716, 'x7': 0.211898, 'x8': 0.295139, 'x9': 0.484805, 'x11': 0.804523, 'x12': 0.586966, 'x13': 0.651085, 'x14': 0.561204, 'x15': 0.379164, 'x16': 0.864332, 'x17': 0.437883, 'x18': 0.956119, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:20] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.489584, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:20] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.08065, 'x3': 0.755201, 'x4': 0.827537, 'x5': 0.329321, 'x6': 0.229822, 'x7': 0.954552, 'x8': 0.08895, 'x9': 0.636977, 'x11': 0.289981, 'x12': 0.13057, 'x13': 0.063051, 'x14': 0.377866, 'x15': 0.209597, 'x16': 0.61987, 'x17': 0.980715, 'x18': 0.692734, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:21] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.633726, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:21] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.178133, 'x3': 0.32032, 'x4': 0.622655, 'x5': 0.403424, 'x6': 0.088838, 'x7': 0.584236, 'x8': 0.950682, 'x9': 0.110298, 'x11': 0.571946, 'x12': 0.633738, 'x13': 0.958312, 'x14': 0.364475, 'x15': 0.732374, 'x16': 0.921761, 'x17': 0.829062, 'x18': 0.513548, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:22] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.624748, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:22] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.549365, 'x3': 0.886589, 'x4': 0.138942, 'x5': 0.569482, 'x6': 0.776197, 'x7': 0.07927, 'x8': 0.168855, 'x9': 0.589432, 'x11': 0.412569, 'x12': 0.286945, 'x13': 0.183638, 'x14': 0.865855, 'x15': 0.038278, 'x16': 0.166314, 'x17': 0.09836, 'x18': 0.4435, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:24] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.374312, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:24] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.46111, 'x3': 0.665555, 'x4': 0.266955, 'x5': 0.760702, 'x6': 0.496584, 'x7': 0.836555, 'x8': 0.462667, 'x9': 0.288724, 'x11': 0.931015, 'x12': 0.993581, 'x13': 0.599785, 'x14': 0.198127, 'x15': 0.365057, 'x16': 0.411997, 'x17': 0.570909, 'x18': 0.203522, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:25] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.312043, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:25] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.86821, 'x3': 0.640771, 'x4': 0.000244, 'x5': 0.692398, 'x6': 0.180863, 'x7': 0.609441, 'x8': 0.884886, 'x9': 0.270873, 'x11': 0.230381, 'x12': 0.913389, 'x13': 0.301254, 'x14': 0.771666, 'x15': 0.183365, 'x16': 0.530487, 'x17': 0.701671, 'x18': 0.412334, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:26] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.434124, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:26] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.737994, 'x3': 0.809517, 'x4': 0.591823, 'x5': 0.155087, 'x6': 0.420785, 'x7': 0.743922, 'x8': 0.508603, 'x9': 0.686262, 'x11': 0.619406, 'x12': 0.21444, 'x13': 0.76832, 'x14': 0.591923, 'x15': 0.274117, 'x16': 0.437888, 'x17': 0.853877, 'x18': 0.924861, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:27] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.384347, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:28] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.904241, 'x3': 0.216275, 'x4': 0.299572, 'x5': 0.508916, 'x6': 0.008401, 'x7': 0.991354, 'x8': 0.027794, 'x9': 0.978446, 'x11': 0.88546, 'x12': 0.416054, 'x13': 0.657852, 'x14': 0.970673, 'x15': 0.62555, 'x16': 0.947652, 'x17': 0.611539, 'x18': 0.35813, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:29] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.487872, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:29] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.274495, 'x3': 0.52995, 'x4': 0.938587, 'x5': 0.456162, 'x6': 0.820989, 'x7': 0.484662, 'x8': 0.872932, 'x9': 0.439972, 'x11': 0.099006, 'x12': 0.507018, 'x13': 0.446197, 'x14': 0.471078, 'x15': 0.072575, 'x16': 0.202916, 'x17': 0.318828, 'x18': 0.661385, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:30] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.367877, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:30] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.330772, 'x3': 0.278291, 'x4': 0.336399, 'x5': 0.233852, 'x6': 0.21767, 'x7': 0.254818, 'x8': 0.258087, 'x9': 0.236357, 'x11': 0.47989, 'x12': 0.265792, 'x13': 0.399699, 'x14': 0.317771, 'x15': 0.342468, 'x16': 0.887185, 'x17': 0.87832, 'x18': 0.038257, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:31] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.578467, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:31] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.679764, 'x3': 0.061163, 'x4': 0.194713, 'x5': 0.408836, 'x6': 0.555389, 'x7': 0.513074, 'x8': 0.122456, 'x9': 0.888873, 'x11': 0.988571, 'x12': 0.949776, 'x13': 0.815853, 'x14': 0.743312, 'x15': 0.012012, 'x16': 0.62875, 'x17': 0.421152, 'x18': 0.298218, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:33] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.425381, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:33] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.210988, 'x3': 0.172043, 'x4': 0.756111, 'x5': 0.676491, 'x6': 0.446483, 'x7': 0.387913, 'x8': 0.135348, 'x9': 0.83778, 'x11': 0.869891, 'x12': 0.606396, 'x13': 0.937458, 'x14': 0.013104, 'x15': 0.247918, 'x16': 0.081207, 'x17': 0.538797, 'x18': 0.548923, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:34] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.402401, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:34] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.428011, 'x3': 0.829747, 'x4': 0.104019, 'x5': 0.034502, 'x6': 0.108684, 'x7': 0.128765, 'x8': 0.654428, 'x9': 0.514365, 'x11': 0.634966, 'x12': 0.778737, 'x13': 0.512288, 'x14': 0.424507, 'x15': 0.849595, 'x16': 0.587064, 'x17': 0.812331, 'x18': 0.234069, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:35] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.553064, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:35] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.430257, 'x3': 0.294, 'x4': 0.657306, 'x5': 0.808413, 'x6': 0.288657, 'x7': 0.483149, 'x8': 0.553222, 'x9': 0.596393, 'x11': 0.949205, 'x12': 0.134859, 'x13': 0.28089, 'x14': 0.986985, 'x15': 0.001569, 'x16': 0.840309, 'x17': 0.106264, 'x18': 0.47345, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:36] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.477623, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:36] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.049002, 'x3': 0.12681, 'x4': 0.249198, 'x5': 0.343858, 'x6': 0.047133, 'x7': 0.350988, 'x8': 0.92645, 'x9': 0.446595, 'x11': 0.338199, 'x12': 0.990974, 'x13': 0.805786, 'x14': 0.682262, 'x15': 0.409099, 'x16': 0.128069, 'x17': 0.445359, 'x18': 0.986222, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:38] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.789268, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:38] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.961473, 'x3': 0.409681, 'x4': 0.343962, 'x5': 0.044736, 'x6': 0.709048, 'x7': 0.608294, 'x8': 0.688973, 'x9': 0.677137, 'x11': 0.817828, 'x12': 0.291475, 'x13': 0.471903, 'x14': 0.25672, 'x15': 0.234413, 'x16': 0.38724, 'x17': 0.97281, 'x18': 0.726231, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:39] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.344466, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:39] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.340241, 'x3': 0.844114, 'x4': 0.894441, 'x5': 0.992135, 'x6': 0.396712, 'x7': 0.103068, 'x8': 0.406333, 'x9': 0.154322, 'x11': 0.166628, 'x12': 0.632195, 'x13': 0.635247, 'x14': 0.755356, 'x15': 0.557407, 'x16': 0.633929, 'x17': 0.203513, 'x18': 0.293287, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:40] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.514438, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:40] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.893725, 'x3': 0.658021, 'x4': 0.993483, 'x5': 0.267233, 'x6': 0.312764, 'x7': 0.650639, 'x8': 0.175935, 'x9': 0.880786, 'x11': 0.698719, 'x12': 0.560045, 'x13': 0.424405, 'x14': 0.408105, 'x15': 0.473599, 'x16': 0.702376, 'x17': 0.282428, 'x18': 0.099389, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:34:41] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.423706, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:42] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.747471, 'x3': 0.312825, 'x4': 0.146081, 'x5': 0.881149, 'x6': 0.224842, 'x7': 0.895153, 'x8': 0.656809, 'x9': 0.705789, 'x11': 0.808156, 'x12': 0.825087, 'x13': 0.001918, 'x14': 0.029539, 'x15': 0.621907, 'x16': 0.192608, 'x17': 0.056019, 'x18': 0.68012, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:34:43] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.351254, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:34:43] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.52498, 'x3': 0.762712, 'x4': 0.413493, 'x5': 0.822667, 'x6': 0.085522, 'x7': 0.51913, 'x8': 0.303684, 'x9': 0.044954, 'x11': 0.088691, 'x12': 0.314106, 'x13': 0.894689, 'x14': 0.228427, 'x15': 0.069851, 'x16': 0.266015, 'x17': 0.130771, 'x18': 0.610298, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:34:44] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.366485, None)}.\n",
- "[INFO 09-08 21:34:53] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.531847, 'x3': 0.593334, 'x4': 0.245504, 'x5': 0.778154, 'x6': 0.469736, 'x7': 0.857721, 'x8': 0.49509, 'x9': 0.384948, 'x11': 0.908171, 'x12': 0.960669, 'x13': 0.505877, 'x14': 0.163374, 'x15': 0.402683, 'x16': 0.379421, 'x17': 0.482459, 'x18': 0.292377, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:34:54] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.340369, None)}.\n",
- "[INFO 09-08 21:35:03] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.508062, 'x3': 0.624224, 'x4': 0.288235, 'x5': 0.708635, 'x6': 0.554206, 'x7': 0.818598, 'x8': 0.463143, 'x9': 0.373604, 'x11': 0.907993, 'x12': 0.938037, 'x13': 0.663077, 'x14': 0.220017, 'x15': 0.315897, 'x16': 0.42768, 'x17': 0.587136, 'x18': 0.257405, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:35:04] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.322098, None)}.\n",
- "[INFO 09-08 21:35:14] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.681213, 'x3': 0.406218, 'x4': 0.181799, 'x5': 0.842365, 'x6': 0.330307, 'x7': 0.887951, 'x8': 0.597746, 'x9': 0.599564, 'x11': 0.847164, 'x12': 0.864174, 'x13': 0.192704, 'x14': 0.075757, 'x15': 0.536871, 'x16': 0.265583, 'x17': 0.219004, 'x18': 0.544413, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:35:15] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.35647, None)}.\n",
- "[INFO 09-08 21:35:24] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.444717, 'x3': 0.653093, 'x4': 0.28032, 'x5': 0.73318, 'x6': 0.500045, 'x7': 0.809111, 'x8': 0.475676, 'x9': 0.289656, 'x11': 0.920118, 'x12': 0.954344, 'x13': 0.622108, 'x14': 0.222815, 'x15': 0.349662, 'x16': 0.409913, 'x17': 0.568186, 'x18': 0.237074, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:35:25] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.346468, None)}.\n",
- "[INFO 09-08 21:35:35] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.568739, 'x3': 0.664633, 'x4': 0.250828, 'x5': 0.786389, 'x6': 0.561461, 'x7': 0.903481, 'x8': 0.414571, 'x9': 0.382152, 'x11': 0.942229, 'x12': 1.0, 'x13': 0.616727, 'x14': 0.146607, 'x15': 0.349454, 'x16': 0.442576, 'x17': 0.61406, 'x18': 0.146388, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:35:36] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.345815, None)}.\n",
- "[INFO 09-08 21:35:45] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.683802, 'x3': 0.405679, 'x4': 0.129251, 'x5': 0.956701, 'x6': 0.208729, 'x7': 0.934684, 'x8': 0.600827, 'x9': 0.594891, 'x11': 0.8536, 'x12': 1.0, 'x13': 0.021211, 'x14': 0.015327, 'x15': 0.641233, 'x16': 0.212946, 'x17': 0.091376, 'x18': 0.519581, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:35:47] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.340806, None)}.\n",
- "[INFO 09-08 21:35:56] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.49727, 'x3': 0.633388, 'x4': 0.281106, 'x5': 0.732671, 'x6': 0.537139, 'x7': 0.866249, 'x8': 0.458687, 'x9': 0.360809, 'x11': 0.898664, 'x12': 1.0, 'x13': 0.615871, 'x14': 0.193745, 'x15': 0.356095, 'x16': 0.444077, 'x17': 0.52024, 'x18': 0.226404, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:35:57] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.323113, None)}.\n",
- "[INFO 09-08 21:36:07] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.526501, 'x3': 0.634139, 'x4': 0.271108, 'x5': 0.735508, 'x6': 0.529615, 'x7': 0.836392, 'x8': 0.469646, 'x9': 0.357945, 'x11': 0.930601, 'x12': 1.0, 'x13': 0.602417, 'x14': 0.178956, 'x15': 0.350205, 'x16': 0.39649, 'x17': 0.601306, 'x18': 0.250622, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:36:08] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.364537, None)}.\n",
- "[INFO 09-08 21:36:17] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.455953, 'x3': 0.640001, 'x4': 0.241783, 'x5': 0.82536, 'x6': 0.500432, 'x7': 0.87695, 'x8': 0.415541, 'x9': 0.356773, 'x11': 0.879334, 'x12': 0.874313, 'x13': 0.64712, 'x14': 0.250254, 'x15': 0.341681, 'x16': 0.50316, 'x17': 0.434425, 'x18': 0.138531, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:36:18] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.33202, None)}.\n",
- "[INFO 09-08 21:36:27] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.468647, 'x3': 0.673574, 'x4': 0.309415, 'x5': 0.708237, 'x6': 0.554615, 'x7': 0.903421, 'x8': 0.441078, 'x9': 0.313954, 'x11': 0.886934, 'x12': 0.872424, 'x13': 0.613253, 'x14': 0.186401, 'x15': 0.379766, 'x16': 0.499421, 'x17': 0.504903, 'x18': 0.172082, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:36:28] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.335171, None)}.\n",
- "[INFO 09-08 21:36:37] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.406526, 'x3': 0.617846, 'x4': 0.280172, 'x5': 0.776766, 'x6': 0.540304, 'x7': 0.881659, 'x8': 0.425299, 'x9': 0.37522, 'x11': 0.89565, 'x12': 1.0, 'x13': 0.697111, 'x14': 0.185436, 'x15': 0.319848, 'x16': 0.416762, 'x17': 0.425094, 'x18': 0.187921, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:36:39] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.324543, None)}.\n",
- "[INFO 09-08 21:36:48] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.454127, 'x3': 0.653508, 'x4': 0.240256, 'x5': 0.776892, 'x6': 0.513997, 'x7': 0.869276, 'x8': 0.452644, 'x9': 0.333339, 'x11': 0.885293, 'x12': 1.0, 'x13': 0.652578, 'x14': 0.247824, 'x15': 0.333875, 'x16': 0.46893, 'x17': 0.476521, 'x18': 0.174495, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:36:49] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.32713, None)}.\n",
- "[WARNING 09-08 21:36:49] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:36:49] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:36:49] ax.service.ax_client: Random seed set to 42. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:36:49] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:36:49] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:36:49] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:36:49] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:36:49] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:36:49] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:36:49] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:36:49] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:36:49] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.997513, 'x3': 0.104366, 'x4': 0.822979, 'x5': 0.419432, 'x6': 0.528322, 'x7': 0.056241, 'x8': 0.455292, 'x9': 0.749203, 'x11': 0.221074, 'x12': 0.617698, 'x13': 0.810095, 'x14': 0.212291, 'x15': 0.038436, 'x16': 0.881824, 'x17': 0.65063, 'x18': 0.666585, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:36:51] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.510923, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:36:51] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.028678, 'x3': 0.748257, 'x4': 0.112076, 'x5': 0.517183, 'x6': 0.034321, 'x7': 0.819032, 'x8': 0.563061, 'x9': 0.185619, 'x11': 0.744641, 'x12': 0.137562, 'x13': 0.213577, 'x14': 0.87748, 'x15': 0.680689, 'x16': 0.344031, 'x17': 0.21139, 'x18': 0.190914, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:36:52] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.767957, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:36:52] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.401359, 'x3': 0.28001, 'x4': 0.504128, 'x5': 0.166136, 'x6': 0.415945, 'x7': 0.628799, 'x8': 0.11119, 'x9': 0.318852, 'x11': 0.996969, 'x12': 0.278384, 'x13': 0.4869, 'x14': 0.509352, 'x15': 0.444765, 'x16': 0.564434, 'x17': 0.41581, 'x18': 0.916697, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:36:53] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.40661, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:36:53] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.232601, 'x3': 0.138953, 'x4': 0.476343, 'x5': 0.675591, 'x6': 0.222226, 'x7': 0.500422, 'x8': 0.272182, 'x9': 0.597903, 'x11': 0.06127, 'x12': 0.799825, 'x13': 0.940577, 'x14': 0.750627, 'x15': 0.212146, 'x16': 0.021959, 'x17': 0.103447, 'x18': 0.099987, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:36:54] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.408955, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:36:55] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.146586, 'x3': 0.946388, 'x4': 0.663216, 'x5': 0.962019, 'x6': 0.596818, 'x7': 0.715537, 'x8': 0.862637, 'x9': 0.943104, 'x11': 0.351504, 'x12': 0.340313, 'x13': 0.921421, 'x14': 0.9966, 'x15': 0.335343, 'x16': 0.633417, 'x17': 0.923878, 'x18': 0.849285, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:36:56] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.553045, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:36:56] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.735913, 'x3': 0.68505, 'x4': 0.978161, 'x5': 0.717268, 'x6': 0.460729, 'x7': 0.100346, 'x8': 0.703815, 'x9': 0.121167, 'x11': 0.618608, 'x12': 0.556574, 'x13': 0.344321, 'x14': 0.293417, 'x15': 0.179015, 'x16': 0.827735, 'x17': 0.126924, 'x18': 0.59917, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:36:57] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.476397, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:36:57] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.502808, 'x3': 0.200209, 'x4': 0.621705, 'x5': 0.621269, 'x6': 0.272838, 'x7': 0.281371, 'x8': 0.381413, 'x9': 0.662358, 'x11': 0.184853, 'x12': 0.381066, 'x13': 0.618168, 'x14': 0.420272, 'x15': 0.710409, 'x16': 0.556321, 'x17': 0.047245, 'x18': 0.688053, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:36:58] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.505831, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:36:58] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.471472, 'x3': 0.587812, 'x4': 0.317255, 'x5': 0.438271, 'x6': 0.790308, 'x7': 0.592989, 'x8': 0.519753, 'x9': 0.226062, 'x11': 0.661775, 'x12': 0.861751, 'x13': 0.40452, 'x14': 0.739942, 'x15': 0.071445, 'x16': 0.21787, 'x17': 0.611484, 'x18': 0.16551, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:00] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.28815, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:00] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.880128, 'x3': 0.794493, 'x4': 0.010126, 'x5': 0.194985, 'x6': 0.153974, 'x7': 0.223924, 'x8': 0.929542, 'x9': 0.842601, 'x11': 0.432787, 'x12': 0.023421, 'x13': 0.82925, 'x14': 0.036386, 'x15': 0.415052, 'x16': 0.273556, 'x17': 0.314317, 'x18': 0.415392, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:01] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.440851, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:01] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.093616, 'x3': 0.751313, 'x4': 0.428596, 'x5': 0.303239, 'x6': 0.379525, 'x7': 0.256131, 'x8': 0.481878, 'x9': 0.867127, 'x11': 0.818045, 'x12': 0.105486, 'x13': 0.151587, 'x14': 0.661775, 'x15': 0.223014, 'x16': 0.751514, 'x17': 0.455974, 'x18': 0.236476, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:02] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.609849, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:02] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.461413, 'x3': 0.220536, 'x4': 0.937621, 'x5': 0.887709, 'x6': 0.014083, 'x7': 0.190508, 'x8': 0.965062, 'x9': 0.640029, 'x11': 0.566205, 'x12': 0.497838, 'x13': 0.424926, 'x14': 0.7956, 'x15': 0.900558, 'x16': 0.031488, 'x17': 0.159508, 'x18': 0.902263, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:03] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.492187, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:03] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.555013, 'x3': 0.614487, 'x4': 0.242558, 'x5': 0.048723, 'x6': 0.547177, 'x7': 0.933792, 'x8': 0.076731, 'x9': 0.201531, 'x11': 0.089025, 'x12': 0.759346, 'x13': 0.582173, 'x14': 0.114598, 'x15': 0.254357, 'x16': 0.69389, 'x17': 0.719841, 'x18': 0.486333, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:05] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.389866, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:05] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.292053, 'x3': 0.642252, 'x4': 0.58312, 'x5': 0.796226, 'x6': 0.201905, 'x7': 0.380655, 'x8': 0.134875, 'x9': 0.083197, 'x11': 0.132772, 'x12': 0.564519, 'x13': 0.666546, 'x14': 0.918578, 'x15': 0.494207, 'x16': 0.334029, 'x17': 0.018367, 'x18': 0.811488, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:06] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.403337, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:06] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.168638, 'x3': 0.360498, 'x4': 0.035047, 'x5': 0.395332, 'x6': 0.316443, 'x7': 0.063087, 'x8': 0.682939, 'x9': 0.419564, 'x11': 0.376541, 'x12': 0.956897, 'x13': 0.877612, 'x14': 0.538597, 'x15': 0.6293, 'x16': 0.616917, 'x17': 0.347115, 'x18': 0.085185, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:07] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.702745, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:07] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.82473, 'x3': 0.974421, 'x4': 0.776968, 'x5': 0.539268, 'x6': 0.869313, 'x7': 0.812251, 'x8': 0.291013, 'x9': 0.981078, 'x11': 0.899848, 'x12': 0.28859, 'x13': 0.099206, 'x14': 0.371515, 'x15': 0.025616, 'x16': 0.141649, 'x17': 0.782448, 'x18': 0.561344, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:08] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.31135, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:08] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.801461, 'x3': 0.15881, 'x4': 0.089329, 'x5': 0.815309, 'x6': 0.494652, 'x7': 0.972068, 'x8': 0.824335, 'x9': 0.575569, 'x11': 0.68773, 'x12': 0.821268, 'x13': 0.00901, 'x14': 0.375299, 'x15': 0.394906, 'x16': 0.515558, 'x17': 0.244968, 'x18': 0.309665, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:10] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.424351, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:10] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.331282, 'x3': 0.459942, 'x4': 0.271461, 'x5': 0.567872, 'x6': 0.57658, 'x7': 0.336979, 'x8': 0.734365, 'x9': 0.48906, 'x11': 0.467501, 'x12': 0.044369, 'x13': 0.693502, 'x14': 0.828855, 'x15': 0.113563, 'x16': 0.946204, 'x17': 0.946458, 'x18': 0.059812, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:11] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.42896, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:11] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.674874, 'x3': 0.814525, 'x4': 0.544461, 'x5': 0.493559, 'x6': 0.109678, 'x7': 0.537316, 'x8': 0.372399, 'x9': 0.92768, 'x11': 0.943706, 'x12': 0.712127, 'x13': 0.282348, 'x14': 0.011077, 'x15': 0.728594, 'x16': 0.295277, 'x17': 0.386125, 'x18': 0.582842, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:12] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.383786, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:12] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.562872, 'x3': 0.299241, 'x4': 0.930197, 'x5': 0.339058, 'x6': 0.172746, 'x7': 0.844637, 'x8': 0.542434, 'x9': 0.359023, 'x11': 0.252337, 'x12': 0.350524, 'x13': 0.555216, 'x14': 0.134253, 'x15': 0.134944, 'x16': 0.086338, 'x17': 0.307606, 'x18': 0.736117, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:13] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.307245, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:14] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.423193, 'x3': 0.113374, 'x4': 0.381522, 'x5': 0.812021, 'x6': 0.368372, 'x7': 0.126514, 'x8': 0.60795, 'x9': 0.913941, 'x11': 0.066351, 'x12': 0.299703, 'x13': 0.062221, 'x14': 0.052813, 'x15': 0.157171, 'x16': 0.388295, 'x17': 0.566939, 'x18': 0.977282, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:15] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.506476, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:15] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.658216, 'x3': 0.14117, 'x4': 0.792792, 'x5': 0.032422, 'x6': 0.882543, 'x7': 0.680135, 'x8': 0.666033, 'x9': 0.809142, 'x11': 0.155448, 'x12': 0.118553, 'x13': 0.188572, 'x14': 0.984201, 'x15': 0.09237, 'x16': 0.528433, 'x17': 0.17906, 'x18': 0.285443, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:16] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.368736, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:16] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.192912, 'x3': 0.473552, 'x4': 0.598943, 'x5': 0.287427, 'x6': 0.050126, 'x7': 0.001959, 'x8': 0.759672, 'x9': 0.130011, 'x11': 0.876623, 'x12': 0.778261, 'x13': 0.513694, 'x14': 0.311658, 'x15': 0.436271, 'x16': 0.962991, 'x17': 0.879577, 'x18': 0.035572, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:17] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.679238, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:17] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.841398, 'x3': 0.054026, 'x4': 0.529095, 'x5': 0.984747, 'x6': 0.138534, 'x7': 0.908194, 'x8': 0.748709, 'x9': 0.849494, 'x11': 0.187526, 'x12': 0.882653, 'x13': 0.380434, 'x14': 0.649335, 'x15': 0.670627, 'x16': 0.908498, 'x17': 0.52834, 'x18': 0.326472, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:19] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.407379, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:19] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.185299, 'x3': 0.659891, 'x4': 0.286826, 'x5': 0.074732, 'x6': 0.675778, 'x7': 0.217632, 'x8': 0.355494, 'x9': 0.285996, 'x11': 0.711809, 'x12': 0.362849, 'x13': 0.596352, 'x14': 0.440444, 'x15': 0.04775, 'x16': 0.317353, 'x17': 0.093068, 'x18': 0.788716, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:20] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.454268, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:20] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.713101, 'x3': 0.96081, 'x4': 0.104695, 'x5': 0.324122, 'x6': 0.256906, 'x7': 0.598321, 'x8': 0.203023, 'x9': 0.653756, 'x11': 0.443727, 'x12': 0.52159, 'x13': 0.169642, 'x14': 0.76948, 'x15': 0.453915, 'x16': 0.128904, 'x17': 0.856177, 'x18': 0.538585, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:37:21] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.414735, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:21] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.920792, 'x3': 0.569505, 'x4': 0.883582, 'x5': 0.830288, 'x6': 0.075624, 'x7': 0.725721, 'x8': 0.414583, 'x9': 0.437208, 'x11': 0.504122, 'x12': 0.054742, 'x13': 0.652366, 'x14': 0.526143, 'x15': 0.201669, 'x16': 0.707492, 'x17': 0.66857, 'x18': 0.479807, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:37:23] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.367028, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:23] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.113741, 'x3': 0.605451, 'x4': 0.551232, 'x5': 0.659276, 'x6': 0.332493, 'x7': 0.754059, 'x8': 0.986451, 'x9': 0.397038, 'x11': 0.244848, 'x12': 0.06635, 'x13': 0.334086, 'x14': 0.150571, 'x15': 0.378773, 'x16': 0.201091, 'x17': 0.562178, 'x18': 0.17203, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:37:24] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.458157, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:24] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.488132, 'x3': 0.386198, 'x4': 0.064972, 'x5': 0.024043, 'x6': 0.217471, 'x7': 0.688948, 'x8': 0.44083, 'x9': 0.107433, 'x11': 0.496945, 'x12': 0.45531, 'x13': 0.123278, 'x14': 0.266811, 'x15': 0.747722, 'x16': 0.980806, 'x17': 0.826263, 'x18': 0.962787, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:25] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.382868, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:25] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.519476, 'x3': 0.780882, 'x4': 0.870082, 'x5': 0.910619, 'x6': 0.719315, 'x7': 0.435901, 'x8': 0.579848, 'x9': 0.54614, 'x11': 0.97289, 'x12': 0.787491, 'x13': 0.899438, 'x14': 0.573114, 'x15': 0.097624, 'x16': 0.26067, 'x17': 0.262084, 'x18': 0.421934, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:37:26] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.388971, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:26] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.250655, 'x3': 0.995154, 'x4': 0.46049, 'x5': 0.182407, 'x6': 0.0294, 'x7': 0.882466, 'x8': 0.645802, 'x9': 0.676089, 'x11': 0.805548, 'x12': 0.607317, 'x13': 0.851234, 'x14': 0.393649, 'x15': 0.153871, 'x16': 0.650809, 'x17': 0.999571, 'x18': 0.872043, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:37:27] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.516793, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:28] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.780357, 'x3': 0.445548, 'x4': 0.962825, 'x5': 0.210439, 'x6': 0.29137, 'x7': 0.469768, 'x8': 0.331357, 'x9': 0.167981, 'x11': 0.374177, 'x12': 0.850646, 'x13': 0.441509, 'x14': 0.937292, 'x15': 0.238172, 'x16': 0.44095, 'x17': 0.773045, 'x18': 0.374111, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:29] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.451111, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:29] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.367797, 'x3': 0.183936, 'x4': 0.647881, 'x5': 0.453237, 'x6': 0.654968, 'x7': 0.839349, 'x8': 0.235034, 'x9': 0.771169, 'x11': 0.595385, 'x12': 0.002544, 'x13': 0.760766, 'x14': 0.358613, 'x15': 0.269321, 'x16': 0.004455, 'x17': 0.035574, 'x18': 0.124211, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:30] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.354334, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:30] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.605244, 'x3': 0.086728, 'x4': 0.056711, 'x5': 0.701831, 'x6': 0.093991, 'x7': 0.346221, 'x8': 0.050911, 'x9': 0.889414, 'x11': 0.685, 'x12': 0.32139, 'x13': 0.989905, 'x14': 0.678706, 'x15': 0.482116, 'x16': 0.894589, 'x17': 0.710683, 'x18': 0.675562, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:31] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.463292, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:31] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.012012, 'x3': 0.293621, 'x4': 0.363841, 'x5': 0.947071, 'x6': 0.957833, 'x7': 0.961866, 'x8': 0.398201, 'x9': 0.054125, 'x11': 0.410112, 'x12': 0.543515, 'x13': 0.307332, 'x14': 0.099669, 'x15': 0.0132, 'x16': 0.581089, 'x17': 0.472937, 'x18': 0.925664, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:33] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.761844, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:33] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.972646, 'x3': 0.47952, 'x4': 0.320809, 'x5': 0.844405, 'x6': 0.249132, 'x7': 0.293323, 'x8': 0.671911, 'x9': 0.535304, 'x11': 0.579236, 'x12': 0.52907, 'x13': 0.35338, 'x14': 0.003586, 'x15': 0.279288, 'x16': 0.369839, 'x17': 0.397669, 'x18': 0.198107, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:34] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.478326, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:34] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.598012, 'x3': 0.511274, 'x4': 0.811021, 'x5': 0.464037, 'x6': 0.365073, 'x7': 0.227598, 'x8': 0.126227, 'x9': 0.965535, 'x11': 0.835227, 'x12': 0.886757, 'x13': 0.064431, 'x14': 0.383505, 'x15': 0.597212, 'x16': 0.588889, 'x17': 0.225137, 'x18': 0.909244, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:37:35] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.410932, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:35] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.647638, 'x3': 0.121056, 'x4': 0.667476, 'x5': 0.36863, 'x6': 0.42724, 'x7': 0.421698, 'x8': 0.960344, 'x9': 0.256741, 'x11': 0.394027, 'x12': 0.050605, 'x13': 0.836361, 'x14': 0.26036, 'x15': 0.003606, 'x16': 0.79413, 'x17': 0.085032, 'x18': 0.755908, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:36] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.355181, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:37:36] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.235014, 'x3': 0.265205, 'x4': 0.974603, 'x5': 0.123147, 'x6': 0.501539, 'x7': 0.771139, 'x8': 0.613799, 'x9': 0.686802, 'x11': 0.638668, 'x12': 0.834247, 'x13': 0.397902, 'x14': 0.963298, 'x15': 0.47227, 'x16': 0.728728, 'x17': 0.848534, 'x18': 0.506024, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:37:38] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.382943, None)}.\n",
- "[INFO 09-08 21:37:48] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.527249, 'x3': 0.588511, 'x4': 0.434578, 'x5': 0.394748, 'x6': 0.795749, 'x7': 0.643318, 'x8': 0.50437, 'x9': 0.339145, 'x11': 0.699549, 'x12': 0.837013, 'x13': 0.363603, 'x14': 0.740623, 'x15': 0.077896, 'x16': 0.229861, 'x17': 0.661386, 'x18': 0.213753, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:37:49] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.309309, None)}.\n",
- "[INFO 09-08 21:38:00] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.561357, 'x3': 0.65619, 'x4': 0.31245, 'x5': 0.459585, 'x6': 0.84873, 'x7': 0.59264, 'x8': 0.486103, 'x9': 0.25973, 'x11': 0.699636, 'x12': 0.832663, 'x13': 0.374679, 'x14': 0.708174, 'x15': 0.003123, 'x16': 0.13154, 'x17': 0.618998, 'x18': 0.142925, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:38:01] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.277058, None)}.\n",
- "[INFO 09-08 21:38:12] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.551934, 'x3': 0.614467, 'x4': 0.33107, 'x5': 0.418036, 'x6': 0.860266, 'x7': 0.612517, 'x8': 0.510645, 'x9': 0.20798, 'x11': 0.693131, 'x12': 0.906017, 'x13': 0.370299, 'x14': 0.779692, 'x15': 0.0, 'x16': 0.152816, 'x17': 0.658769, 'x18': 0.131289, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:38:13] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.287414, None)}.\n",
- "[INFO 09-08 21:38:24] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.531013, 'x3': 0.63433, 'x4': 0.316895, 'x5': 0.433367, 'x6': 0.83159, 'x7': 0.584022, 'x8': 0.498825, 'x9': 0.262155, 'x11': 0.690861, 'x12': 0.870934, 'x13': 0.403654, 'x14': 0.694249, 'x15': 0.020173, 'x16': 0.161586, 'x17': 0.622186, 'x18': 0.149122, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:38:25] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.292799, None)}.\n",
- "[INFO 09-08 21:38:35] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.541442, 'x3': 0.622343, 'x4': 0.316836, 'x5': 0.509041, 'x6': 0.829287, 'x7': 0.626494, 'x8': 0.493723, 'x9': 0.206141, 'x11': 0.674968, 'x12': 0.755657, 'x13': 0.316811, 'x14': 0.811745, 'x15': 0.041787, 'x16': 0.158519, 'x17': 0.607742, 'x18': 0.155545, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:38:36] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.284952, None)}.\n",
- "[INFO 09-08 21:38:46] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.496787, 'x3': 0.719367, 'x4': 0.307529, 'x5': 0.436828, 'x6': 0.774176, 'x7': 0.663578, 'x8': 0.493389, 'x9': 0.185292, 'x11': 0.739846, 'x12': 0.817829, 'x13': 0.330527, 'x14': 0.748722, 'x15': 0.03062, 'x16': 0.11773, 'x17': 0.631502, 'x18': 0.159405, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:38:47] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.272563, None)}.\n",
- "[INFO 09-08 21:38:57] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.537687, 'x3': 0.670021, 'x4': 0.311638, 'x5': 0.447389, 'x6': 0.799104, 'x7': 0.637189, 'x8': 0.49953, 'x9': 0.208429, 'x11': 0.718958, 'x12': 0.81125, 'x13': 0.338072, 'x14': 0.755677, 'x15': 0.021197, 'x16': 0.128285, 'x17': 0.609314, 'x18': 0.143, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:38:59] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.277877, None)}.\n",
- "[INFO 09-08 21:39:10] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.468503, 'x3': 0.73104, 'x4': 0.304165, 'x5': 0.510225, 'x6': 0.871872, 'x7': 0.624521, 'x8': 0.451669, 'x9': 0.206241, 'x11': 0.690479, 'x12': 0.822701, 'x13': 0.34899, 'x14': 0.749854, 'x15': 0.031514, 'x16': 0.132674, 'x17': 0.710948, 'x18': 0.19447, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:39:11] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.290093, None)}.\n",
- "[INFO 09-08 21:39:21] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.549752, 'x3': 0.651495, 'x4': 0.323149, 'x5': 0.501429, 'x6': 0.81248, 'x7': 0.686088, 'x8': 0.505291, 'x9': 0.137293, 'x11': 0.699014, 'x12': 0.848147, 'x13': 0.332943, 'x14': 0.679783, 'x15': 0.0, 'x16': 0.13098, 'x17': 0.611533, 'x18': 0.240947, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:39:22] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.285154, None)}.\n",
- "[INFO 09-08 21:39:32] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.586326, 'x3': 0.290924, 'x4': 0.87221, 'x5': 0.314273, 'x6': 0.333697, 'x7': 0.808742, 'x8': 0.515403, 'x9': 0.410583, 'x11': 0.227766, 'x12': 0.3455, 'x13': 0.515929, 'x14': 0.368015, 'x15': 0.161847, 'x16': 0.193944, 'x17': 0.26098, 'x18': 0.660906, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:39:33] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.344002, None)}.\n",
- "[INFO 09-08 21:39:44] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.509168, 'x3': 0.689766, 'x4': 0.316354, 'x5': 0.455679, 'x6': 0.794145, 'x7': 0.62143, 'x8': 0.477859, 'x9': 0.178872, 'x11': 0.711791, 'x12': 0.813729, 'x13': 0.334173, 'x14': 0.744861, 'x15': 0.0, 'x16': 0.139247, 'x17': 0.631008, 'x18': 0.178157, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:39:45] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.287344, None)}.\n",
- "[INFO 09-08 21:39:55] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.53519, 'x3': 0.688569, 'x4': 0.271813, 'x5': 0.504941, 'x6': 0.8654, 'x7': 0.740635, 'x8': 0.540903, 'x9': 0.248412, 'x11': 0.724232, 'x12': 0.846688, 'x13': 0.364126, 'x14': 0.72736, 'x15': 0.113622, 'x16': 0.08221, 'x17': 0.633703, 'x18': 0.126184, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:39:56] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.281287, None)}.\n",
- "[WARNING 09-08 21:39:56] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:39:56] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:39:56] ax.service.ax_client: Random seed set to 87. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:39:56] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:39:56] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:39:56] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:39:56] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:39:56] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:39:56] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:39:56] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:39:56] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:39:56] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.195271, 'x3': 0.681871, 'x4': 0.439029, 'x5': 0.194549, 'x6': 0.018985, 'x7': 0.506456, 'x8': 0.635988, 'x9': 0.737048, 'x11': 0.574687, 'x12': 0.503303, 'x13': 0.056656, 'x14': 0.861832, 'x15': 0.663063, 'x16': 0.8088, 'x17': 0.264166, 'x18': 0.474308, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:39:57] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.565551, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:39:58] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.397385, 'x3': 0.231449, 'x4': 0.887639, 'x5': 0.676671, 'x6': 0.332573, 'x7': 0.783469, 'x8': 0.493092, 'x9': 0.920699, 'x11': 0.8032, 'x12': 0.850164, 'x13': 0.26312, 'x14': 0.707429, 'x15': 0.209754, 'x16': 0.318915, 'x17': 0.20124, 'x18': 0.944568, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:39:59] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.417135, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:39:59] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.658685, 'x3': 0.109685, 'x4': 0.358373, 'x5': 0.477043, 'x6': 0.502097, 'x7': 0.199124, 'x8': 0.312182, 'x9': 0.757919, 'x11': 0.957787, 'x12': 0.702143, 'x13': 0.443481, 'x14': 0.209049, 'x15': 0.044369, 'x16': 0.961383, 'x17': 0.546678, 'x18': 0.20179, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:00] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.373554, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:00] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.017713, 'x3': 0.361133, 'x4': 0.240587, 'x5': 0.119788, 'x6': 0.249302, 'x7': 0.905556, 'x8': 0.023925, 'x9': 0.167158, 'x11': 0.259579, 'x12': 0.375606, 'x13': 0.998475, 'x14': 0.876393, 'x15': 0.298702, 'x16': 0.505013, 'x17': 0.386907, 'x18': 0.314656, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:01] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.694512, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:01] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.883064, 'x3': 0.145457, 'x4': 0.187435, 'x5': 0.618942, 'x6': 0.104046, 'x7': 0.254278, 'x8': 0.33714, 'x9': 0.81256, 'x11': 0.928942, 'x12': 0.300093, 'x13': 0.143933, 'x14': 0.492449, 'x15': 0.758781, 'x16': 0.616767, 'x17': 0.153597, 'x18': 0.12658, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:02] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.450041, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:02] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.712261, 'x3': 0.691218, 'x4': 0.736873, 'x5': 0.009847, 'x6': 0.294395, 'x7': 0.031952, 'x8': 0.541591, 'x9': 0.527804, 'x11': 0.700427, 'x12': 0.084698, 'x13': 0.410187, 'x14': 0.092441, 'x15': 0.367974, 'x16': 0.012901, 'x17': 0.341644, 'x18': 0.659254, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:04] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.548743, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:04] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.482213, 'x3': 0.592404, 'x4': 0.016138, 'x5': 0.834481, 'x6': 0.620965, 'x7': 0.946392, 'x8': 0.732267, 'x9': 0.682285, 'x11': 0.54639, 'x12': 0.498859, 'x13': 0.35886, 'x14': 0.590643, 'x15': 0.37833, 'x16': 0.64435, 'x17': 0.933615, 'x18': 0.416555, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:05] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.365666, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:05] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.841386, 'x3': 0.842783, 'x4': 0.382948, 'x5': 0.691733, 'x6': 0.131541, 'x7': 0.154022, 'x8': 0.947283, 'x9': 0.274996, 'x11': 0.236854, 'x12': 0.672564, 'x13': 0.835049, 'x14': 0.261405, 'x15': 0.156101, 'x16': 0.826685, 'x17': 0.031222, 'x18': 0.03721, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:40:06] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.464809, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:06] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.145767, 'x3': 0.862293, 'x4': 0.1326, 'x5': 0.92837, 'x6': 0.362189, 'x7': 0.3876, 'x8': 0.241996, 'x9': 0.308395, 'x11': 0.882561, 'x12': 0.726728, 'x13': 0.122416, 'x14': 0.527113, 'x15': 0.255151, 'x16': 0.081742, 'x17': 0.16361, 'x18': 0.449668, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:40:07] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.503842, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:07] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.441753, 'x3': 0.286871, 'x4': 0.697913, 'x5': 0.442842, 'x6': 0.051867, 'x7': 0.164305, 'x8': 0.879273, 'x9': 0.101306, 'x11': 0.747797, 'x12': 0.888534, 'x13': 0.322455, 'x14': 0.93475, 'x15': 0.864707, 'x16': 0.540102, 'x17': 0.350682, 'x18': 0.983368, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:09] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.48623, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:09] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.536251, 'x3': 0.612673, 'x4': 0.28069, 'x5': 0.535588, 'x6': 0.890188, 'x7': 0.711227, 'x8': 0.453242, 'x9': 0.649397, 'x11': 0.33859, 'x12': 0.412396, 'x13': 0.567586, 'x14': 0.324949, 'x15': 0.025354, 'x16': 0.389538, 'x17': 0.75435, 'x18': 0.063365, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:10] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.393321, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:10] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.267138, 'x3': 0.732609, 'x4': 0.997456, 'x5': 0.368066, 'x6': 0.212056, 'x7': 0.298741, 'x8': 0.272824, 'x9': 0.560714, 'x11': 0.42973, 'x12': 0.013812, 'x13': 0.638937, 'x14': 0.826927, 'x15': 0.221011, 'x16': 0.765654, 'x17': 0.474281, 'x18': 0.821762, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:11] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.482789, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:11] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.963825, 'x3': 0.340039, 'x4': 0.493864, 'x5': 0.258159, 'x6': 0.260843, 'x7': 0.638776, 'x8': 0.786829, 'x9': 0.13425, 'x11': 0.622043, 'x12': 0.460942, 'x13': 0.207267, 'x14': 0.141617, 'x15': 0.167243, 'x16': 0.2735, 'x17': 0.301028, 'x18': 0.164408, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:13] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.403048, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:13] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.63665, 'x3': 0.7608, 'x4': 0.926599, 'x5': 0.870622, 'x6': 0.075101, 'x7': 0.916757, 'x8': 0.084091, 'x9': 0.458068, 'x11': 0.756806, 'x12': 0.185492, 'x13': 0.47201, 'x14': 0.304625, 'x15': 0.714303, 'x16': 0.846391, 'x17': 0.239078, 'x18': 0.635587, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:40:14] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.39552, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:14] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.592024, 'x3': 0.188474, 'x4': 0.628032, 'x5': 0.943459, 'x6': 0.157099, 'x7': 0.549885, 'x8': 0.692524, 'x9': 0.887302, 'x11': 0.065727, 'x12': 0.810602, 'x13': 0.538218, 'x14': 0.441431, 'x15': 0.324552, 'x16': 0.589492, 'x17': 0.115601, 'x18': 0.544263, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:15] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.37496, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:15] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.232814, 'x3': 0.438853, 'x4': 0.777099, 'x5': 0.582816, 'x6': 0.591501, 'x7': 0.351295, 'x8': 0.971648, 'x9': 0.046542, 'x11': 0.654559, 'x12': 0.109798, 'x13': 0.030569, 'x14': 0.644023, 'x15': 0.079007, 'x16': 0.881794, 'x17': 0.958607, 'x18': 0.907975, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:16] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.380816, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:16] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.780689, 'x3': 0.237305, 'x4': 0.311457, 'x5': 0.249197, 'x6': 0.831719, 'x7': 0.927115, 'x8': 0.904189, 'x9': 0.595316, 'x11': 0.898849, 'x12': 0.025902, 'x13': 0.716428, 'x14': 0.565196, 'x15': 0.114812, 'x16': 0.576105, 'x17': 0.057074, 'x18': 0.548685, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:40:18] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.414104, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:18] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.421088, 'x3': 0.48768, 'x4': 0.162398, 'x5': 0.357402, 'x6': 0.420665, 'x7': 0.220644, 'x8': 0.681826, 'x9': 0.440105, 'x11': 0.31776, 'x12': 0.832907, 'x13': 0.224552, 'x14': 0.271236, 'x15': 0.352667, 'x16': 0.891329, 'x17': 0.89995, 'x18': 0.934865, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:19] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.514425, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:19] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.042964, 'x3': 0.109064, 'x4': 0.965724, 'x5': 0.90989, 'x6': 0.004906, 'x7': 0.090818, 'x8': 0.838509, 'x9': 0.694622, 'x11': 0.869964, 'x12': 0.424721, 'x13': 0.5224, 'x14': 0.063216, 'x15': 0.138884, 'x16': 0.2061, 'x17': 0.714524, 'x18': 0.304949, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:40:20] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.810763, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:20] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.923461, 'x3': 0.385317, 'x4': 0.895834, 'x5': 0.407074, 'x6': 0.141373, 'x7': 0.695145, 'x8': 0.527248, 'x9': 0.293391, 'x11': 0.441546, 'x12': 0.251219, 'x13': 0.371082, 'x14': 0.556222, 'x15': 0.678793, 'x16': 0.157929, 'x17': 0.948078, 'x18': 0.246032, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:21] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.358942, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:22] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.719264, 'x3': 0.966477, 'x4': 0.461138, 'x5': 0.956081, 'x6': 0.460178, 'x7': 0.971731, 'x8': 0.35185, 'x9': 0.109473, 'x11': 0.185684, 'x12': 0.098449, 'x13': 0.074798, 'x14': 0.905756, 'x15': 0.194483, 'x16': 0.713975, 'x17': 0.510031, 'x18': 0.712288, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:23] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.356528, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:23] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.45711, 'x3': 0.813467, 'x4': 0.80687, 'x5': 0.140205, 'x6': 0.62653, 'x7': 0.010436, 'x8': 0.42094, 'x9': 0.209754, 'x11': 0.090424, 'x12': 0.449829, 'x13': 0.132717, 'x14': 0.403348, 'x15': 0.059084, 'x16': 0.068335, 'x17': 0.230076, 'x18': 0.45409, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:24] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.387717, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:24] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.847937, 'x3': 0.563843, 'x4': 0.658787, 'x5': 0.278588, 'x6': 0.122062, 'x7': 0.841807, 'x8': 0.133644, 'x9': 0.865211, 'x11': 0.626531, 'x12': 0.627687, 'x13': 0.687045, 'x14': 0.697735, 'x15': 0.281435, 'x16': 0.399107, 'x17': 0.820701, 'x18': 0.090255, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:25] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.365434, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:25] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.168572, 'x3': 0.606078, 'x4': 0.919383, 'x5': 0.10909, 'x6': 0.383478, 'x7': 0.577468, 'x8': 0.92682, 'x9': 0.835612, 'x11': 0.488918, 'x12': 0.713255, 'x13': 0.39626, 'x14': 0.462974, 'x15': 0.182307, 'x16': 0.630485, 'x17': 0.984452, 'x18': 0.427751, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:26] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.515739, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:27] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.497586, 'x3': 0.058242, 'x4': 0.468823, 'x5': 0.527754, 'x6': 0.202468, 'x7': 0.855022, 'x8': 0.194082, 'x9': 0.511588, 'x11': 0.139306, 'x12': 0.937192, 'x13': 0.158869, 'x14': 0.122046, 'x15': 0.697865, 'x16': 0.249243, 'x17': 0.54738, 'x18': 0.895056, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:28] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.371573, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:28] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.289373, 'x3': 0.984694, 'x4': 0.210814, 'x5': 0.658164, 'x6': 0.034585, 'x7': 0.736681, 'x8': 0.583507, 'x9': 0.080363, 'x11': 0.948318, 'x12': 0.058899, 'x13': 0.850442, 'x14': 0.139712, 'x15': 0.341523, 'x16': 0.443536, 'x17': 0.674029, 'x18': 0.799856, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:29] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.48407, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:29] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.898485, 'x3': 0.736138, 'x4': 0.327616, 'x5': 0.799936, 'x6': 0.716823, 'x7': 0.41303, 'x8': 0.861639, 'x9': 0.98582, 'x11': 0.271587, 'x12': 0.861512, 'x13': 0.342489, 'x14': 0.961352, 'x15': 0.063508, 'x16': 0.026828, 'x17': 0.26737, 'x18': 0.687113, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:30] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.329689, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:30] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.971837, 'x3': 0.064766, 'x4': 0.706104, 'x5': 0.704381, 'x6': 0.485677, 'x7': 0.325861, 'x8': 0.100998, 'x9': 0.723731, 'x11': 0.015504, 'x12': 0.478965, 'x13': 0.309213, 'x14': 0.828939, 'x15': 0.270177, 'x16': 0.951392, 'x17': 0.597526, 'x18': 0.205242, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:31] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.502107, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:31] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.331497, 'x3': 0.316209, 'x4': 0.823883, 'x5': 0.816036, 'x6': 0.761939, 'x7': 0.524427, 'x8': 0.313205, 'x9': 0.318519, 'x11': 0.705968, 'x12': 0.660239, 'x13': 0.754691, 'x14': 0.007482, 'x15': 0.007909, 'x16': 0.518979, 'x17': 0.437625, 'x18': 0.342515, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:33] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.3915, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:33] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.601464, 'x3': 0.467399, 'x4': 0.415651, 'x5': 0.030311, 'x6': 0.088446, 'x7': 0.484992, 'x8': 0.382788, 'x9': 0.469702, 'x11': 0.547199, 'x12': 0.762186, 'x13': 0.952871, 'x14': 0.505677, 'x15': 0.238036, 'x16': 0.138222, 'x17': 0.783193, 'x18': 0.585094, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:34] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.414149, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:34] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.803708, 'x3': 0.884406, 'x4': 0.973394, 'x5': 0.606289, 'x6': 0.278734, 'x7': 0.207493, 'x8': 0.738605, 'x9': 0.184139, 'x11': 0.822592, 'x12': 0.603068, 'x13': 0.743005, 'x14': 0.90941, 'x15': 0.628465, 'x16': 0.741388, 'x17': 0.720143, 'x18': 0.114926, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:35] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.51957, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:35] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.808224, 'x3': 0.098727, 'x4': 0.024949, 'x5': 0.310091, 'x6': 0.221891, 'x7': 0.429154, 'x8': 0.607593, 'x9': 0.242669, 'x11': 0.727352, 'x12': 0.102392, 'x13': 0.416128, 'x14': 0.306614, 'x15': 0.001569, 'x16': 0.782524, 'x17': 0.223836, 'x18': 0.479417, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:40:37] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.458941, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:37] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.386482, 'x3': 0.348165, 'x4': 0.376134, 'x5': 0.171264, 'x6': 0.529646, 'x7': 0.722508, 'x8': 0.822265, 'x9': 0.839166, 'x11': 0.052514, 'x12': 0.787816, 'x13': 0.893014, 'x14': 0.607928, 'x15': 0.278485, 'x16': 0.746189, 'x17': 0.819124, 'x18': 0.10008, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:40:38] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.435103, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:38] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.68683, 'x3': 0.493976, 'x4': 0.846806, 'x5': 0.988071, 'x6': 0.321242, 'x7': 0.260238, 'x8': 0.889398, 'x9': 0.997674, 'x11': 0.210427, 'x12': 0.639492, 'x13': 0.836924, 'x14': 0.106436, 'x15': 0.47515, 'x16': 0.096671, 'x17': 0.413169, 'x18': 0.859274, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:39] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.366831, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:39] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.982701, 'x3': 0.920809, 'x4': 0.295169, 'x5': 0.375085, 'x6': 0.014704, 'x7': 0.045542, 'x8': 0.247146, 'x9': 0.658117, 'x11': 0.419413, 'x12': 0.979638, 'x13': 0.607825, 'x14': 0.447334, 'x15': 0.89721, 'x16': 0.52378, 'x17': 0.101095, 'x18': 0.325593, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:40] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.573391, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:40] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.113434, 'x3': 0.574061, 'x4': 0.351515, 'x5': 0.878374, 'x6': 0.151172, 'x7': 0.677284, 'x8': 0.433927, 'x9': 0.323048, 'x11': 0.76908, 'x12': 0.836865, 'x13': 0.253398, 'x14': 0.92502, 'x15': 0.421496, 'x16': 0.60441, 'x17': 0.366198, 'x18': 0.139416, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:42] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.574297, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:42] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.691853, 'x3': 0.822552, 'x4': 0.249353, 'x5': 0.517227, 'x6': 0.601197, 'x7': 0.469867, 'x8': 0.151871, 'x9': 0.728505, 'x11': 0.451663, 'x12': 0.022047, 'x13': 0.807699, 'x14': 0.222917, 'x15': 0.174975, 'x16': 0.929431, 'x17': 0.708014, 'x18': 0.252274, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:43] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.428988, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:40:43] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.485257, 'x3': 0.960063, 'x4': 0.528682, 'x5': 0.325397, 'x6': 0.297884, 'x7': 0.508324, 'x8': 0.090598, 'x9': 0.577321, 'x11': 0.293201, 'x12': 0.436511, 'x13': 0.984763, 'x14': 0.724843, 'x15': 0.07084, 'x16': 0.290382, 'x17': 0.051621, 'x18': 0.511516, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:40:44] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.345897, None)}.\n",
- "[INFO 09-08 21:40:53] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.842442, 'x3': 0.655355, 'x4': 0.385962, 'x5': 0.800583, 'x6': 0.621601, 'x7': 0.446767, 'x8': 0.810247, 'x9': 0.944552, 'x11': 0.249391, 'x12': 0.83526, 'x13': 0.37306, 'x14': 0.861795, 'x15': 0.107031, 'x16': 0.119297, 'x17': 0.261724, 'x18': 0.653334, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:40:54] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.318215, None)}.\n",
- "[INFO 09-08 21:41:03] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.855916, 'x3': 0.67538, 'x4': 0.364151, 'x5': 0.810835, 'x6': 0.650719, 'x7': 0.432185, 'x8': 0.837171, 'x9': 0.962707, 'x11': 0.246451, 'x12': 0.850775, 'x13': 0.360794, 'x14': 0.890776, 'x15': 0.093927, 'x16': 0.08991, 'x17': 0.251237, 'x18': 0.671753, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:41:04] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.338306, None)}.\n",
- "[INFO 09-08 21:41:13] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.892598, 'x3': 0.724734, 'x4': 0.393437, 'x5': 0.718125, 'x6': 0.658985, 'x7': 0.467452, 'x8': 0.742864, 'x9': 0.916851, 'x11': 0.334067, 'x12': 0.787127, 'x13': 0.383129, 'x14': 0.912178, 'x15': 0.088008, 'x16': 0.09072, 'x17': 0.359471, 'x18': 0.603701, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:41:14] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.340657, None)}.\n",
- "[INFO 09-08 21:41:22] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.81997, 'x3': 0.567251, 'x4': 0.596882, 'x5': 0.427973, 'x6': 0.24454, 'x7': 0.745375, 'x8': 0.316083, 'x9': 0.852133, 'x11': 0.51947, 'x12': 0.677458, 'x13': 0.600228, 'x14': 0.691569, 'x15': 0.243884, 'x16': 0.336224, 'x17': 0.656542, 'x18': 0.252085, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:41:23] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.342342, None)}.\n",
- "[INFO 09-08 21:41:32] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.807309, 'x3': 0.581126, 'x4': 0.435938, 'x5': 0.75173, 'x6': 0.488796, 'x7': 0.519447, 'x8': 0.718485, 'x9': 0.94992, 'x11': 0.273168, 'x12': 0.832899, 'x13': 0.434617, 'x14': 0.785404, 'x15': 0.160043, 'x16': 0.194768, 'x17': 0.309065, 'x18': 0.573071, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:41:34] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.323035, None)}.\n",
- "[INFO 09-08 21:41:42] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.805966, 'x3': 0.614578, 'x4': 0.444459, 'x5': 0.781114, 'x6': 0.572614, 'x7': 0.467936, 'x8': 0.751433, 'x9': 0.873123, 'x11': 0.250838, 'x12': 0.780316, 'x13': 0.389222, 'x14': 0.785489, 'x15': 0.132267, 'x16': 0.191121, 'x17': 0.27877, 'x18': 0.621331, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:41:43] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.320196, None)}.\n",
- "[INFO 09-08 21:41:52] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.782764, 'x3': 0.571029, 'x4': 0.529237, 'x5': 0.626249, 'x6': 0.400006, 'x7': 0.606482, 'x8': 0.543141, 'x9': 0.828555, 'x11': 0.359539, 'x12': 0.720483, 'x13': 0.481204, 'x14': 0.696661, 'x15': 0.194659, 'x16': 0.283431, 'x17': 0.440805, 'x18': 0.455823, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:41:53] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.339779, None)}.\n",
- "[INFO 09-08 21:42:02] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.797231, 'x3': 0.639612, 'x4': 0.40323, 'x5': 0.749335, 'x6': 0.534787, 'x7': 0.519815, 'x8': 0.738608, 'x9': 0.901256, 'x11': 0.258562, 'x12': 0.818088, 'x13': 0.379532, 'x14': 0.79253, 'x15': 0.133584, 'x16': 0.150971, 'x17': 0.302955, 'x18': 0.60938, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:42:03] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.32755, None)}.\n",
- "[INFO 09-08 21:42:12] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.847239, 'x3': 0.590057, 'x4': 0.463816, 'x5': 0.791382, 'x6': 0.572982, 'x7': 0.448515, 'x8': 0.754931, 'x9': 0.942549, 'x11': 0.2841, 'x12': 0.795744, 'x13': 0.44818, 'x14': 0.825942, 'x15': 0.136366, 'x16': 0.207895, 'x17': 0.289516, 'x18': 0.592646, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:42:13] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.321937, None)}.\n",
- "[INFO 09-08 21:42:22] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.840877, 'x3': 0.54618, 'x4': 0.44924, 'x5': 0.736369, 'x6': 0.56188, 'x7': 0.426918, 'x8': 0.710935, 'x9': 0.916623, 'x11': 0.244816, 'x12': 0.823904, 'x13': 0.373316, 'x14': 0.80404, 'x15': 0.178026, 'x16': 0.180476, 'x17': 0.293015, 'x18': 0.615131, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:42:23] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.334656, None)}.\n",
- "[INFO 09-08 21:42:32] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.795703, 'x3': 0.624064, 'x4': 0.446612, 'x5': 0.831853, 'x6': 0.529916, 'x7': 0.516204, 'x8': 0.777112, 'x9': 0.917058, 'x11': 0.270493, 'x12': 0.781191, 'x13': 0.456037, 'x14': 0.792259, 'x15': 0.115956, 'x16': 0.233711, 'x17': 0.274356, 'x18': 0.591968, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:42:33] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.327926, None)}.\n",
- "[INFO 09-08 21:42:42] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.79054, 'x3': 0.638381, 'x4': 0.494576, 'x5': 0.724806, 'x6': 0.590439, 'x7': 0.430294, 'x8': 0.799529, 'x9': 0.935937, 'x11': 0.303987, 'x12': 0.815548, 'x13': 0.4962, 'x14': 0.712415, 'x15': 0.101414, 'x16': 0.084256, 'x17': 0.259221, 'x18': 0.589616, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:42:43] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.31519, None)}.\n",
- "[WARNING 09-08 21:42:43] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:42:43] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:42:43] ax.service.ax_client: Random seed set to 115. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:42:43] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:42:43] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:42:43] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:42:43] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:42:43] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:42:43] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:42:43] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:42:43] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:43] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.507994, 'x3': 0.998989, 'x4': 0.781718, 'x5': 0.662859, 'x6': 0.120882, 'x7': 0.608699, 'x8': 0.30891, 'x9': 0.278067, 'x11': 0.577924, 'x12': 0.184895, 'x13': 0.73665, 'x14': 0.684309, 'x15': 0.312225, 'x16': 0.978238, 'x17': 0.079081, 'x18': 0.882734, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:42:45] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.466984, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:45] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.214269, 'x3': 0.690682, 'x4': 0.647983, 'x5': 0.82978, 'x6': 0.552979, 'x7': 0.033856, 'x8': 0.154746, 'x9': 0.974155, 'x11': 0.297694, 'x12': 0.922881, 'x13': 0.023535, 'x14': 0.268434, 'x15': 0.23762, 'x16': 0.554953, 'x17': 0.897806, 'x18': 0.658756, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:42:46] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.55375, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:46] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.854353, 'x3': 0.506526, 'x4': 0.131687, 'x5': 0.347074, 'x6': 0.326707, 'x7': 0.699712, 'x8': 0.074281, 'x9': 0.817891, 'x11': 0.381218, 'x12': 0.569959, 'x13': 0.136725, 'x14': 0.764035, 'x15': 0.124597, 'x16': 0.247161, 'x17': 0.297272, 'x18': 0.320845, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:42:47] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.350347, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:47] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.49195, 'x3': 0.017517, 'x4': 0.543736, 'x5': 0.264156, 'x6': 0.00975, 'x7': 0.124864, 'x8': 0.899323, 'x9': 0.10136, 'x11': 0.795755, 'x12': 0.963363, 'x13': 0.529771, 'x14': 0.088576, 'x15': 0.009875, 'x16': 0.660234, 'x17': 0.439688, 'x18': 0.500512, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:42:48] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.63948, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:48] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.14571, 'x3': 0.478181, 'x4': 0.385175, 'x5': 0.699089, 'x6': 0.309325, 'x7': 0.21492, 'x8': 0.727213, 'x9': 0.561471, 'x11': 0.22588, 'x12': 0.28179, 'x13': 0.093909, 'x14': 0.476898, 'x15': 0.322499, 'x16': 0.422565, 'x17': 0.158872, 'x18': 0.203029, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:42:50] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.482611, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:50] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.568801, 'x3': 0.207142, 'x4': 0.060155, 'x5': 0.809236, 'x6': 0.860565, 'x7': 0.64254, 'x8': 0.822806, 'x9': 0.195096, 'x11': 0.898748, 'x12': 0.543821, 'x13': 0.635149, 'x14': 0.568408, 'x15': 0.131685, 'x16': 0.094995, 'x17': 0.848693, 'x18': 0.479116, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:42:51] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.306178, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:51] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.268451, 'x3': 0.603536, 'x4': 0.83666, 'x5': 0.472838, 'x6': 0.146606, 'x7': 0.300181, 'x8': 0.229541, 'x9': 0.905293, 'x11': 0.330865, 'x12': 0.122051, 'x13': 0.316743, 'x14': 0.241281, 'x15': 0.664061, 'x16': 0.910738, 'x17': 0.346357, 'x18': 0.723709, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:42:52] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.547709, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:52] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.287252, 'x3': 0.241542, 'x4': 0.3669, 'x5': 0.610147, 'x6': 0.514615, 'x7': 0.823977, 'x8': 0.27635, 'x9': 0.233376, 'x11': 0.468078, 'x12': 0.603964, 'x13': 0.366256, 'x14': 0.379773, 'x15': 0.379466, 'x16': 0.769038, 'x17': 0.973069, 'x18': 0.15759, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:42:53] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.417997, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:53] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.989637, 'x3': 0.448128, 'x4': 0.18777, 'x5': 0.882568, 'x6': 0.065915, 'x7': 0.256002, 'x8': 0.180527, 'x9': 0.523252, 'x11': 0.656564, 'x12': 0.34976, 'x13': 0.903588, 'x14': 0.541718, 'x15': 0.070769, 'x16': 0.689987, 'x17': 0.034961, 'x18': 0.379047, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:42:54] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.540841, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:54] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.765892, 'x3': 0.92294, 'x4': 0.425976, 'x5': 0.857356, 'x6': 0.215436, 'x7': 0.07286, 'x8': 0.948458, 'x9': 0.4834, 'x11': 0.215112, 'x12': 0.688135, 'x13': 0.194711, 'x14': 0.631934, 'x15': 0.724199, 'x16': 0.939453, 'x17': 0.128274, 'x18': 0.345402, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:42:56] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.528455, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:56] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.648039, 'x3': 0.049538, 'x4': 0.850482, 'x5': 0.064563, 'x6': 0.365461, 'x7': 0.412029, 'x8': 0.445918, 'x9': 0.077118, 'x11': 0.353291, 'x12': 0.903142, 'x13': 0.471755, 'x14': 0.89879, 'x15': 0.258141, 'x16': 0.459154, 'x17': 0.315789, 'x18': 0.823502, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:42:57] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.360181, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:57] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.712692, 'x3': 0.773744, 'x4': 0.120145, 'x5': 0.461368, 'x6': 0.621845, 'x7': 0.33918, 'x8': 0.935797, 'x9': 0.396047, 'x11': 0.185909, 'x12': 0.263044, 'x13': 0.401504, 'x14': 0.846603, 'x15': 0.173071, 'x16': 0.592644, 'x17': 0.615887, 'x18': 0.2873, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:42:58] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.449155, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:58] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.010304, 'x3': 0.537006, 'x4': 0.450155, 'x5': 0.045919, 'x6': 0.048144, 'x7': 0.772185, 'x8': 0.527736, 'x9': 0.856171, 'x11': 0.938733, 'x12': 0.501014, 'x13': 0.860771, 'x14': 0.199894, 'x15': 0.372913, 'x16': 0.889829, 'x17': 0.422896, 'x18': 0.003211, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:42:59] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.942908, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:42:59] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.352027, 'x3': 0.96654, 'x4': 0.603848, 'x5': 0.979151, 'x6': 0.25394, 'x7': 0.927217, 'x8': 0.855607, 'x9': 0.302249, 'x11': 0.008628, 'x12': 0.246094, 'x13': 0.264877, 'x14': 0.37337, 'x15': 0.060537, 'x16': 0.151916, 'x17': 0.204687, 'x18': 0.699377, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:43:00] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.301765, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:01] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.538318, 'x3': 0.704871, 'x4': 0.23246, 'x5': 0.088463, 'x6': 0.246641, 'x7': 0.162542, 'x8': 0.758842, 'x9': 0.716994, 'x11': 0.447422, 'x12': 0.125874, 'x13': 0.841913, 'x14': 0.498551, 'x15': 0.020637, 'x16': 0.33538, 'x17': 0.843094, 'x18': 0.988956, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:02] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.541132, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:02] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.818146, 'x3': 0.790594, 'x4': 0.820968, 'x5': 0.905476, 'x6': 0.447064, 'x7': 0.005608, 'x8': 0.618467, 'x9': 0.131879, 'x11': 0.503661, 'x12': 0.619214, 'x13': 0.281538, 'x14': 0.074587, 'x15': 0.333009, 'x16': 0.566213, 'x17': 0.562281, 'x18': 0.308411, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:03] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.394824, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:03] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.689551, 'x3': 0.166247, 'x4': 0.40087, 'x5': 0.172636, 'x6': 0.09709, 'x7': 0.479306, 'x8': 0.120031, 'x9': 0.288072, 'x11': 0.927968, 'x12': 0.787491, 'x13': 0.004128, 'x14': 0.331199, 'x15': 0.680431, 'x16': 0.085822, 'x17': 0.999767, 'x18': 0.766743, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:43:04] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.483979, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:04] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.461741, 'x3': 0.311338, 'x4': 0.471413, 'x5': 0.986498, 'x6': 0.139393, 'x7': 0.678601, 'x8': 0.419644, 'x9': 0.911396, 'x11': 0.167206, 'x12': 0.976363, 'x13': 0.924035, 'x14': 0.773975, 'x15': 0.281779, 'x16': 0.026178, 'x17': 0.700757, 'x18': 0.61315, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:43:05] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.420806, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:05] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.761308, 'x3': 0.003401, 'x4': 0.083283, 'x5': 0.505223, 'x6': 0.69063, 'x7': 0.245144, 'x8': 0.015199, 'x9': 0.340277, 'x11': 0.957175, 'x12': 0.230077, 'x13': 0.336409, 'x14': 0.178558, 'x15': 0.230895, 'x16': 0.448472, 'x17': 0.259964, 'x18': 0.834618, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:43:07] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.430302, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:07] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.092785, 'x3': 0.684945, 'x4': 0.797288, 'x5': 0.216671, 'x6': 0.285266, 'x7': 0.837472, 'x8': 0.919987, 'x9': 0.504591, 'x11': 0.280009, 'x12': 0.683336, 'x13': 0.646759, 'x14': 0.507604, 'x15': 0.700471, 'x16': 0.514534, 'x17': 0.763272, 'x18': 0.087069, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:08] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.474399, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:08] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.181787, 'x3': 0.193937, 'x4': 0.566498, 'x5': 0.054259, 'x6': 0.433566, 'x7': 0.520678, 'x8': 0.216757, 'x9': 0.496568, 'x11': 0.84637, 'x12': 0.278555, 'x13': 0.449599, 'x14': 0.666415, 'x15': 0.094403, 'x16': 0.764092, 'x17': 0.918951, 'x18': 0.184316, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:43:09] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.406016, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:09] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.310516, 'x3': 0.817606, 'x4': 0.147272, 'x5': 0.773917, 'x6': 0.016941, 'x7': 0.994498, 'x8': 0.717116, 'x9': 0.091351, 'x11': 0.710129, 'x12': 0.063762, 'x13': 0.226632, 'x14': 0.92693, 'x15': 0.888098, 'x16': 0.275645, 'x17': 0.606468, 'x18': 0.64676, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:10] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.582657, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:10] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.258999, 'x3': 0.46134, 'x4': 0.681425, 'x5': 0.137299, 'x6': 0.634462, 'x7': 0.377929, 'x8': 0.796526, 'x9': 0.793412, 'x11': 0.588553, 'x12': 0.585715, 'x13': 0.214119, 'x14': 0.6942, 'x15': 0.16994, 'x16': 0.419572, 'x17': 0.230234, 'x18': 0.205096, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:43:12] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.429544, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:12] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.591437, 'x3': 0.850038, 'x4': 0.465713, 'x5': 0.582153, 'x6': 0.358004, 'x7': 0.531658, 'x8': 0.138813, 'x9': 0.113976, 'x11': 0.140818, 'x12': 0.007691, 'x13': 0.770987, 'x14': 0.116954, 'x15': 0.639783, 'x16': 0.60203, 'x17': 0.730859, 'x18': 0.966348, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:13] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.368256, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:13] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.963318, 'x3': 0.224477, 'x4': 0.763876, 'x5': 0.371024, 'x6': 0.191621, 'x7': 0.952248, 'x8': 0.638196, 'x9': 0.458257, 'x11': 0.286804, 'x12': 0.339444, 'x13': 0.547898, 'x14': 0.352079, 'x15': 0.346564, 'x16': 0.121425, 'x17': 0.793344, 'x18': 0.491697, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:43:14] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.403237, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:14] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.680194, 'x3': 0.278829, 'x4': 0.164641, 'x5': 0.685846, 'x6': 0.485826, 'x7': 0.856284, 'x8': 0.997809, 'x9': 0.887183, 'x11': 0.730616, 'x12': 0.907597, 'x13': 0.077492, 'x14': 0.213269, 'x15': 0.033936, 'x16': 0.852503, 'x17': 0.575138, 'x18': 0.804808, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:43:15] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.366497, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:15] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.036737, 'x3': 0.760604, 'x4': 0.502466, 'x5': 0.706387, 'x6': 0.177779, 'x7': 0.468295, 'x8': 0.04026, 'x9': 0.170128, 'x11': 0.067021, 'x12': 0.559301, 'x13': 0.715959, 'x14': 0.88922, 'x15': 0.085247, 'x16': 0.298789, 'x17': 0.686178, 'x18': 0.109444, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:16] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.870666, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:17] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.188214, 'x3': 0.360529, 'x4': 0.866158, 'x5': 0.555688, 'x6': 0.040953, 'x7': 0.143761, 'x8': 0.838735, 'x9': 0.834938, 'x11': 0.555379, 'x12': 0.400607, 'x13': 0.381838, 'x14': 0.784357, 'x15': 0.744789, 'x16': 0.048316, 'x17': 0.529494, 'x18': 0.146026, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:43:18] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.785715, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:18] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.319743, 'x3': 0.73683, 'x4': 0.410295, 'x5': 0.272416, 'x6': 0.378235, 'x7': 0.371365, 'x8': 0.337385, 'x9': 0.741266, 'x11': 0.887908, 'x12': 0.193664, 'x13': 0.159614, 'x14': 0.559005, 'x15': 0.27287, 'x16': 0.536458, 'x17': 0.96701, 'x18': 0.686961, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:19] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.362014, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:19] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.325242, 'x3': 0.162211, 'x4': 0.720342, 'x5': 0.790415, 'x6': 0.236259, 'x7': 0.209911, 'x8': 0.44028, 'x9': 0.626864, 'x11': 0.686065, 'x12': 0.676593, 'x13': 0.803937, 'x14': 0.190525, 'x15': 0.62487, 'x16': 0.992554, 'x17': 0.407146, 'x18': 0.886996, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:43:20] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.496652, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:20] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.525006, 'x3': 0.52345, 'x4': 0.379414, 'x5': 0.486228, 'x6': 0.772239, 'x7': 0.863671, 'x8': 0.597022, 'x9': 0.462077, 'x11': 0.113376, 'x12': 0.223576, 'x13': 0.243193, 'x14': 0.611357, 'x15': 0.092751, 'x16': 0.060295, 'x17': 0.913385, 'x18': 0.128686, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:43:21] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.357378, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:21] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.198111, 'x3': 0.786833, 'x4': 0.050259, 'x5': 0.006409, 'x6': 0.339163, 'x7': 0.306167, 'x8': 0.938959, 'x9': 0.781372, 'x11': 0.760763, 'x12': 0.977188, 'x13': 0.518839, 'x14': 0.465197, 'x15': 0.392698, 'x16': 0.480761, 'x17': 0.09466, 'x18': 0.412832, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:43:23] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.534591, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:23] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.870543, 'x3': 0.969099, 'x4': 0.533352, 'x5': 0.551051, 'x6': 0.534675, 'x7': 0.960608, 'x8': 0.768659, 'x9': 0.875069, 'x11': 0.935113, 'x12': 0.529325, 'x13': 0.632151, 'x14': 0.93837, 'x15': 0.280135, 'x16': 0.790156, 'x17': 0.695179, 'x18': 0.574855, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:24] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.367663, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:24] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.41422, 'x3': 0.716735, 'x4': 0.896321, 'x5': 0.940625, 'x6': 0.10746, 'x7': 0.400682, 'x8': 0.673081, 'x9': 0.368314, 'x11': 0.190017, 'x12': 0.267905, 'x13': 0.106565, 'x14': 0.108127, 'x15': 0.205318, 'x16': 0.743088, 'x17': 0.250474, 'x18': 0.853383, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:43:25] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.419145, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:25] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.674692, 'x3': 0.821397, 'x4': 0.981516, 'x5': 0.126804, 'x6': 0.128778, 'x7': 0.693727, 'x8': 0.849984, 'x9': 0.99475, 'x11': 0.968349, 'x12': 0.45701, 'x13': 0.96394, 'x14': 0.536201, 'x15': 0.822718, 'x16': 0.677503, 'x17': 0.049003, 'x18': 0.510886, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:26] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.36833, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:27] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.801955, 'x3': 0.197942, 'x4': 0.312274, 'x5': 0.920085, 'x6': 0.29052, 'x7': 0.790106, 'x8': 0.349382, 'x9': 0.589266, 'x11': 0.603593, 'x12': 0.140187, 'x13': 0.7494, 'x14': 0.806962, 'x15': 0.163773, 'x16': 0.158142, 'x17': 0.486487, 'x18': 0.033024, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:43:28] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.391298, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:28] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.129402, 'x3': 0.015005, 'x4': 0.795489, 'x5': 0.403306, 'x6': 0.579781, 'x7': 0.444562, 'x8': 0.429328, 'x9': 0.745504, 'x11': 0.715451, 'x12': 0.368323, 'x13': 0.60496, 'x14': 0.288006, 'x15': 0.042422, 'x16': 0.59838, 'x17': 0.833114, 'x18': 0.949019, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:29] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.372302, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:43:29] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.953212, 'x3': 0.673112, 'x4': 0.073916, 'x5': 0.816879, 'x6': 0.428322, 'x7': 0.599304, 'x8': 0.521609, 'x9': 0.409818, 'x11': 0.021486, 'x12': 0.790085, 'x13': 0.411404, 'x14': 0.898398, 'x15': 0.510098, 'x16': 0.407608, 'x17': 0.330808, 'x18': 0.19167, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:43:30] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.412453, None)}.\n",
- "[INFO 09-08 21:43:38] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.46327, 'x3': 0.838625, 'x4': 0.593909, 'x5': 0.880355, 'x6': 0.277429, 'x7': 0.965727, 'x8': 0.831238, 'x9': 0.317169, 'x11': 0.059588, 'x12': 0.292249, 'x13': 0.301951, 'x14': 0.365542, 'x15': 0.054775, 'x16': 0.170699, 'x17': 0.292494, 'x18': 0.699892, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:43:40] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.332724, None)}.\n",
- "[INFO 09-08 21:43:48] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.340898, 'x3': 0.950448, 'x4': 0.525725, 'x5': 1.0, 'x6': 0.3142, 'x7': 0.956041, 'x8': 0.910378, 'x9': 0.347395, 'x11': 0.074264, 'x12': 0.302485, 'x13': 0.206575, 'x14': 0.338043, 'x15': 0.0, 'x16': 0.226008, 'x17': 0.188905, 'x18': 0.755063, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:43:50] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.330425, None)}.\n",
- "[INFO 09-08 21:43:58] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.571913, 'x3': 0.255502, 'x4': 0.121364, 'x5': 0.76079, 'x6': 0.831304, 'x7': 0.683258, 'x8': 0.760209, 'x9': 0.252788, 'x11': 0.762461, 'x12': 0.470598, 'x13': 0.571689, 'x14': 0.5862, 'x15': 0.125515, 'x16': 0.094083, 'x17': 0.848397, 'x18': 0.410681, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:43:59] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.287412, None)}.\n",
- "[INFO 09-08 21:44:08] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.374597, 'x3': 0.960302, 'x4': 0.58494, 'x5': 0.982034, 'x6': 0.311627, 'x7': 0.942115, 'x8': 0.83685, 'x9': 0.246182, 'x11': 0.0, 'x12': 0.227571, 'x13': 0.277636, 'x14': 0.388159, 'x15': 0.01484, 'x16': 0.132637, 'x17': 0.21773, 'x18': 0.701617, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:44:10] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.3022, None)}.\n",
- "[INFO 09-08 21:44:19] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.263375, 'x3': 0.411803, 'x4': 0.591409, 'x5': 0.34661, 'x6': 0.482633, 'x7': 0.433016, 'x8': 0.376973, 'x9': 0.735557, 'x11': 0.80652, 'x12': 0.282179, 'x13': 0.365776, 'x14': 0.428434, 'x15': 0.184978, 'x16': 0.579462, 'x17': 0.894545, 'x18': 0.803988, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:44:20] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.340073, None)}.\n",
- "[INFO 09-08 21:44:29] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.47084, 'x3': 0.625035, 'x4': 0.532118, 'x5': 0.384892, 'x6': 0.479038, 'x7': 0.573669, 'x8': 0.452357, 'x9': 0.770379, 'x11': 0.841503, 'x12': 0.338659, 'x13': 0.378019, 'x14': 0.575106, 'x15': 0.245592, 'x16': 0.623865, 'x17': 0.831782, 'x18': 0.707815, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:44:30] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.35394, None)}.\n",
- "[INFO 09-08 21:44:40] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.414884, 'x3': 0.632857, 'x4': 0.511205, 'x5': 0.395039, 'x6': 0.438241, 'x7': 0.464039, 'x8': 0.305244, 'x9': 0.579096, 'x11': 0.667465, 'x12': 0.199414, 'x13': 0.393434, 'x14': 0.371982, 'x15': 0.349097, 'x16': 0.590675, 'x17': 0.861818, 'x18': 0.805093, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:44:41] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.337841, None)}.\n",
- "[INFO 09-08 21:44:50] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.350684, 'x3': 0.978572, 'x4': 0.633241, 'x5': 0.974326, 'x6': 0.235036, 'x7': 0.977094, 'x8': 0.826845, 'x9': 0.229755, 'x11': 0.0, 'x12': 0.283226, 'x13': 0.288822, 'x14': 0.398673, 'x15': 0.026239, 'x16': 0.100238, 'x17': 0.164741, 'x18': 0.756969, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:44:51] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.313341, None)}.\n",
- "[INFO 09-08 21:45:01] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.447537, 'x3': 0.472582, 'x4': 0.469754, 'x5': 0.340432, 'x6': 0.452849, 'x7': 0.482748, 'x8': 0.238707, 'x9': 0.699823, 'x11': 0.690881, 'x12': 0.318319, 'x13': 0.265443, 'x14': 0.432561, 'x15': 0.232564, 'x16': 0.509943, 'x17': 0.785397, 'x18': 0.710064, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:45:02] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.342081, None)}.\n",
- "[INFO 09-08 21:45:12] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.36715, 'x3': 1.0, 'x4': 0.594525, 'x5': 1.0, 'x6': 0.254619, 'x7': 0.964345, 'x8': 0.856677, 'x9': 0.273905, 'x11': 0.0, 'x12': 0.169207, 'x13': 0.277979, 'x14': 0.351237, 'x15': 0.044258, 'x16': 0.117341, 'x17': 0.224318, 'x18': 0.667305, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:45:13] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.302135, None)}.\n",
- "[INFO 09-08 21:45:22] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.577528, 'x3': 0.251736, 'x4': 0.111841, 'x5': 0.77642, 'x6': 0.847735, 'x7': 0.686232, 'x8': 0.763338, 'x9': 0.245719, 'x11': 0.768416, 'x12': 0.46707, 'x13': 0.574798, 'x14': 0.591266, 'x15': 0.123918, 'x16': 0.083615, 'x17': 0.854605, 'x18': 0.417167, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:45:24] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.283089, None)}.\n",
- "[INFO 09-08 21:45:33] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.597991, 'x3': 0.251677, 'x4': 0.0939, 'x5': 0.820649, 'x6': 0.89042, 'x7': 0.708239, 'x8': 0.759348, 'x9': 0.23586, 'x11': 0.754143, 'x12': 0.435438, 'x13': 0.570828, 'x14': 0.614378, 'x15': 0.10958, 'x16': 0.045789, 'x17': 0.876344, 'x18': 0.421466, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:45:34] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.288202, None)}.\n",
- "[WARNING 09-08 21:45:34] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:45:34] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:45:34] ax.service.ax_client: Random seed set to 131. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:45:34] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:45:34] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:45:34] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:45:34] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:45:34] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:45:34] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:45:34] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:45:34] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:34] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.190509, 'x3': 0.904799, 'x4': 0.796328, 'x5': 0.197967, 'x6': 0.124788, 'x7': 0.385848, 'x8': 0.74884, 'x9': 0.152706, 'x11': 0.186744, 'x12': 0.913019, 'x13': 0.473032, 'x14': 0.554079, 'x15': 0.548071, 'x16': 0.004879, 'x17': 0.785083, 'x18': 0.458585, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:45:35] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.471797, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:35] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.715992, 'x3': 0.460142, 'x4': 0.168328, 'x5': 0.778361, 'x6': 0.766595, 'x7': 0.742453, 'x8': 0.451265, 'x9': 0.65559, 'x11': 0.558795, 'x12': 0.057842, 'x13': 0.527356, 'x14': 0.089743, 'x15': 0.096249, 'x16': 0.509326, 'x17': 0.473109, 'x18': 0.627781, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:45:36] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.404419, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:36] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.265496, 'x3': 0.044747, 'x4': 0.259944, 'x5': 0.633943, 'x6': 0.344136, 'x7': 0.132836, 'x8': 0.126421, 'x9': 0.325931, 'x11': 0.487334, 'x12': 0.636282, 'x13': 0.206231, 'x14': 0.775786, 'x15': 0.414593, 'x16': 0.965611, 'x17': 0.671332, 'x18': 0.81905, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:45:37] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.594036, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:38] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.949874, 'x3': 0.127046, 'x4': 0.878163, 'x5': 0.467941, 'x6': 0.62737, 'x7': 0.539088, 'x8': 0.063991, 'x9': 0.417216, 'x11': 0.270563, 'x12': 0.780161, 'x13': 0.062581, 'x14': 0.406524, 'x15': 0.310268, 'x16': 0.229097, 'x17': 0.241335, 'x18': 0.233132, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:45:39] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.333086, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:39] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.029635, 'x3': 0.368063, 'x4': 0.53643, 'x5': 0.073278, 'x6': 0.237267, 'x7': 0.086202, 'x8': 0.264568, 'x9': 0.61881, 'x11': 0.713124, 'x12': 0.42025, 'x13': 0.639863, 'x14': 0.72048, 'x15': 0.241893, 'x16': 0.312369, 'x17': 0.933744, 'x18': 0.291834, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:45:40] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.683052, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:40] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.607927, 'x3': 0.073067, 'x4': 0.569643, 'x5': 0.605052, 'x6': 0.037466, 'x7': 0.937232, 'x8': 0.014141, 'x9': 0.487907, 'x11': 0.330838, 'x12': 0.368384, 'x13': 0.254987, 'x14': 0.017798, 'x15': 0.758066, 'x16': 0.339445, 'x17': 0.72336, 'x18': 0.135146, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:45:41] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.430973, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:41] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.908504, 'x3': 0.993668, 'x4': 0.095757, 'x5': 0.039113, 'x6': 0.30658, 'x7': 0.68422, 'x8': 0.611089, 'x9': 0.033218, 'x11': 0.030248, 'x12': 0.082375, 'x13': 0.049162, 'x14': 0.311761, 'x15': 0.142521, 'x16': 0.628545, 'x17': 0.851704, 'x18': 0.524665, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:45:42] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.402839, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:42] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.344953, 'x3': 0.834266, 'x4': 0.729606, 'x5': 0.873103, 'x6': 0.714814, 'x7': 0.027972, 'x8': 0.673049, 'x9': 0.192358, 'x11': 0.243105, 'x12': 0.43868, 'x13': 0.157641, 'x14': 0.879999, 'x15': 0.004689, 'x16': 0.427674, 'x17': 0.297321, 'x18': 0.423152, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:45:44] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.380623, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:44] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.675569, 'x3': 0.668658, 'x4': 0.825612, 'x5': 0.728683, 'x6': 0.16737, 'x7': 0.606352, 'x8': 0.998413, 'x9': 0.77189, 'x11': 0.804458, 'x12': 0.86085, 'x13': 0.607673, 'x14': 0.192002, 'x15': 0.451939, 'x16': 0.094444, 'x17': 0.620559, 'x18': 0.114391, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:45:45] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.330696, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:45] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.137271, 'x3': 0.634817, 'x4': 0.595642, 'x5': 0.934743, 'x6': 0.317757, 'x7': 0.814551, 'x8': 0.477561, 'x9': 0.801637, 'x11': 0.374454, 'x12': 0.80128, 'x13': 0.413603, 'x14': 0.996784, 'x15': 0.209242, 'x16': 0.71312, 'x17': 0.716531, 'x18': 0.479263, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:45:46] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.54508, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:46] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.312844, 'x3': 0.306017, 'x4': 0.067084, 'x5': 0.498729, 'x6': 0.088682, 'x7': 0.563493, 'x8': 0.89721, 'x9': 0.724115, 'x11': 0.050105, 'x12': 0.525273, 'x13': 0.141401, 'x14': 0.704784, 'x15': 0.828071, 'x16': 0.251992, 'x17': 0.82925, 'x18': 0.869042, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:45:48] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.453497, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:48] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.403404, 'x3': 0.967997, 'x4': 0.32671, 'x5': 0.374071, 'x6': 0.210881, 'x7': 0.892924, 'x8': 0.100201, 'x9': 0.000526, 'x11': 0.584268, 'x12': 0.016946, 'x13': 0.995674, 'x14': 0.506924, 'x15': 0.384257, 'x16': 0.055819, 'x17': 0.952074, 'x18': 0.881498, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:45:49] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.359557, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:49] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.578022, 'x3': 0.536895, 'x4': 0.227524, 'x5': 0.229671, 'x6': 0.663492, 'x7': 0.4708, 'x8': 0.290982, 'x9': 0.955178, 'x11': 0.399876, 'x12': 0.658134, 'x13': 0.3015, 'x14': 0.318929, 'x15': 0.065913, 'x16': 0.480886, 'x17': 0.130782, 'x18': 0.565229, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:45:50] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.347467, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:50] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.079943, 'x3': 0.105878, 'x4': 0.855295, 'x5': 0.809158, 'x6': 0.445665, 'x7': 0.641874, 'x8': 0.524538, 'x9': 0.454192, 'x11': 0.775834, 'x12': 0.308814, 'x13': 0.700062, 'x14': 0.79108, 'x15': 0.516389, 'x16': 0.969844, 'x17': 0.564887, 'x18': 0.271016, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:45:51] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.628513, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:51] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.532228, 'x3': 0.342148, 'x4': 0.759579, 'x5': 0.277375, 'x6': 0.278286, 'x7': 0.36595, 'x8': 0.775088, 'x9': 0.589003, 'x11': 0.14312, 'x12': 0.479818, 'x13': 0.31933, 'x14': 0.462817, 'x15': 0.483614, 'x16': 0.880204, 'x17': 0.776302, 'x18': 0.176943, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:45:52] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.516634, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:52] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.982219, 'x3': 0.731498, 'x4': 0.293523, 'x5': 0.843352, 'x6': 0.003275, 'x7': 0.114893, 'x8': 0.349652, 'x9': 0.885488, 'x11': 0.46747, 'x12': 0.193567, 'x13': 0.111033, 'x14': 0.239178, 'x15': 0.615761, 'x16': 0.091196, 'x17': 0.646926, 'x18': 0.53718, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:45:54] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.742704, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:54] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.488233, 'x3': 0.160771, 'x4': 0.67163, 'x5': 0.132975, 'x6': 0.855882, 'x7': 0.756807, 'x8': 0.584826, 'x9': 0.384463, 'x11': 0.841543, 'x12': 0.839729, 'x13': 0.884594, 'x14': 0.648861, 'x15': 0.036364, 'x16': 0.578192, 'x17': 0.079994, 'x18': 0.360705, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:45:55] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.420347, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:55] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.79739, 'x3': 0.011151, 'x4': 0.037766, 'x5': 0.966954, 'x6': 0.139054, 'x7': 0.413058, 'x8': 0.64666, 'x9': 0.358684, 'x11': 0.933306, 'x12': 0.70171, 'x13': 0.776276, 'x14': 0.033504, 'x15': 0.17188, 'x16': 0.349857, 'x17': 0.509492, 'x18': 0.712234, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:45:56] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.388764, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:56] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.304946, 'x3': 0.444746, 'x4': 0.587694, 'x5': 0.348839, 'x6': 0.489582, 'x7': 0.528398, 'x8': 0.700432, 'x9': 0.895813, 'x11': 0.66522, 'x12': 0.684411, 'x13': 0.35382, 'x14': 0.211457, 'x15': 0.139275, 'x16': 0.163776, 'x17': 0.277116, 'x18': 0.756931, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:45:58] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.393272, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:58] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.473693, 'x3': 0.782279, 'x4': 0.831978, 'x5': 0.473188, 'x6': 0.367597, 'x7': 0.951457, 'x8': 0.309674, 'x9': 0.360015, 'x11': 0.199386, 'x12': 0.176198, 'x13': 0.501058, 'x14': 0.013846, 'x15': 0.570394, 'x16': 0.402918, 'x17': 0.378966, 'x18': 0.992529, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:45:59] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.389269, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:45:59] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.995325, 'x3': 0.352178, 'x4': 0.203978, 'x5': 0.550012, 'x6': 0.522817, 'x7': 0.184649, 'x8': 0.513476, 'x9': 0.862954, 'x11': 0.577295, 'x12': 0.790746, 'x13': 0.49361, 'x14': 0.596346, 'x15': 0.026992, 'x16': 0.892478, 'x17': 0.816001, 'x18': 0.170988, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:46:00] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.382096, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:00] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.040792, 'x3': 0.14293, 'x4': 0.365904, 'x5': 0.913165, 'x6': 0.101342, 'x7': 0.700529, 'x8': 0.815066, 'x9': 0.157446, 'x11': 0.375083, 'x12': 0.399471, 'x13': 0.803076, 'x14': 0.284341, 'x15': 0.454742, 'x16': 0.567018, 'x17': 0.008373, 'x18': 0.354964, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:46:02] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.62154, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:02] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.587011, 'x3': 0.406659, 'x4': 0.270211, 'x5': 0.382382, 'x6': 0.175222, 'x7': 0.29167, 'x8': 0.564639, 'x9': 0.792042, 'x11': 0.508727, 'x12': 0.326549, 'x13': 0.184063, 'x14': 0.953942, 'x15': 0.545255, 'x16': 0.532145, 'x17': 0.328178, 'x18': 0.19903, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:46:03] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.440377, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:03] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.896313, 'x3': 0.518779, 'x4': 0.798753, 'x5': 0.94147, 'x6': 0.418702, 'x7': 0.040735, 'x8': 0.060101, 'x9': 0.744701, 'x11': 0.817206, 'x12': 0.096684, 'x13': 0.385949, 'x14': 0.74787, 'x15': 0.429588, 'x16': 0.493029, 'x17': 0.215395, 'x18': 0.58684, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:46:04] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.48689, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:04] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.33462, 'x3': 0.684513, 'x4': 0.430663, 'x5': 0.142651, 'x6': 0.576936, 'x7': 0.634485, 'x8': 0.247534, 'x9': 0.527746, 'x11': 0.909029, 'x12': 0.490654, 'x13': 0.273488, 'x14': 0.070258, 'x15': 0.284027, 'x16': 0.701713, 'x17': 0.629644, 'x18': 0.485241, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:46:05] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.357887, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:05] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.629233, 'x3': 0.818413, 'x4': 0.029844, 'x5': 0.256049, 'x6': 0.060864, 'x7': 0.2441, 'x8': 0.42391, 'x9': 0.452128, 'x11': 0.107343, 'x12': 0.819189, 'x13': 0.960084, 'x14': 0.7563, 'x15': 0.227402, 'x16': 0.777131, 'x17': 0.452905, 'x18': 0.051327, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:46:07] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.554219, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:07] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.182668, 'x3': 0.844439, 'x4': 0.29888, 'x5': 0.079288, 'x6': 0.453438, 'x7': 0.460006, 'x8': 0.911437, 'x9': 0.480899, 'x11': 0.536469, 'x12': 0.753761, 'x13': 0.030174, 'x14': 0.060893, 'x15': 0.484704, 'x16': 0.407478, 'x17': 0.3526, 'x18': 0.417396, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:46:08] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.538299, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:08] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.85351, 'x3': 0.650672, 'x4': 0.145009, 'x5': 0.442453, 'x6': 0.907018, 'x7': 0.913362, 'x8': 0.728653, 'x9': 0.561415, 'x11': 0.478926, 'x12': 0.425226, 'x13': 0.704877, 'x14': 0.874851, 'x15': 0.056955, 'x16': 0.113297, 'x17': 0.533237, 'x18': 0.108421, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:46:09] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.35616, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:09] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.366973, 'x3': 0.20693, 'x4': 0.77278, 'x5': 0.518247, 'x6': 0.203123, 'x7': 0.207116, 'x8': 0.463823, 'x9': 0.06048, 'x11': 0.852929, 'x12': 0.545632, 'x13': 0.290691, 'x14': 0.268909, 'x15': 0.603412, 'x16': 0.618621, 'x17': 0.224192, 'x18': 0.804977, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:46:10] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.448892, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:10] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.416549, 'x3': 0.55226, 'x4': 0.528743, 'x5': 0.643623, 'x6': 0.06519, 'x7': 0.257113, 'x8': 0.541814, 'x9': 0.711033, 'x11': 0.262095, 'x12': 0.037115, 'x13': 0.56537, 'x14': 0.443332, 'x15': 0.171324, 'x16': 0.814779, 'x17': 0.119481, 'x18': 0.944376, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:46:12] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.445697, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:12] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.617648, 'x3': 0.952631, 'x4': 0.932733, 'x5': 0.757032, 'x6': 0.549173, 'x7': 0.866254, 'x8': 0.849355, 'x9': 0.260295, 'x11': 0.690742, 'x12': 0.647182, 'x13': 0.138538, 'x14': 0.629375, 'x15': 0.349043, 'x16': 0.647525, 'x17': 0.79821, 'x18': 0.503321, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:46:13] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.355478, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:13] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.522085, 'x3': 0.176655, 'x4': 0.088064, 'x5': 0.734457, 'x6': 0.384548, 'x7': 0.972327, 'x8': 0.333965, 'x9': 0.128615, 'x11': 0.945949, 'x12': 0.4649, 'x13': 0.249633, 'x14': 0.526379, 'x15': 0.196463, 'x16': 0.248205, 'x17': 0.17027, 'x18': 0.238882, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:46:14] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.377954, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:14] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.963223, 'x3': 0.757526, 'x4': 0.624462, 'x5': 0.175331, 'x6': 0.14689, 'x7': 0.719438, 'x8': 0.791265, 'x9': 0.330252, 'x11': 0.629489, 'x12': 0.235768, 'x13': 0.446118, 'x14': 0.802753, 'x15': 0.828732, 'x16': 0.78723, 'x17': 0.283959, 'x18': 0.601316, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:46:15] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.382259, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:15] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.75694, 'x3': 0.470528, 'x4': 0.864557, 'x5': 0.049029, 'x6': 0.026688, 'x7': 0.800699, 'x8': 0.213273, 'x9': 0.929543, 'x11': 0.220323, 'x12': 0.743981, 'x13': 0.659704, 'x14': 0.969364, 'x15': 0.396562, 'x16': 0.528554, 'x17': 0.434622, 'x18': 0.649407, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:46:17] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.388329, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:17] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.699042, 'x3': 0.580581, 'x4': 0.328186, 'x5': 0.611005, 'x6': 0.254858, 'x7': 0.547819, 'x8': 0.661987, 'x9': 0.599869, 'x11': 0.419564, 'x12': 0.957725, 'x13': 0.895284, 'x14': 0.700832, 'x15': 0.515285, 'x16': 0.442425, 'x17': 0.048404, 'x18': 0.011582, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:46:18] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.430393, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:18] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.208894, 'x3': 0.026547, 'x4': 0.706293, 'x5': 0.412194, 'x6': 0.605283, 'x7': 0.316076, 'x8': 0.39554, 'x9': 0.098915, 'x11': 0.79559, 'x12': 0.071662, 'x13': 0.106098, 'x14': 0.157361, 'x15': 0.089906, 'x16': 0.945773, 'x17': 0.740275, 'x18': 0.840402, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:46:19] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.442407, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:19] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.690665, 'x3': 0.149308, 'x4': 0.719071, 'x5': 0.291619, 'x6': 0.224925, 'x7': 0.847134, 'x8': 0.51887, 'x9': 0.552899, 'x11': 0.03646, 'x12': 0.108698, 'x13': 0.054871, 'x14': 0.245953, 'x15': 0.26254, 'x16': 0.028956, 'x17': 0.640348, 'x18': 0.464768, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:46:20] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.391768, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:46:21] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.26739, 'x3': 0.345799, 'x4': 0.8185, 'x5': 0.186267, 'x6': 0.647255, 'x7': 0.268756, 'x8': 0.840082, 'x9': 0.473362, 'x11': 0.978907, 'x12': 0.718723, 'x13': 0.741323, 'x14': 0.931981, 'x15': 0.194166, 'x16': 0.446179, 'x17': 0.442079, 'x18': 0.030763, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:46:22] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.468249, None)}.\n",
- "[INFO 09-08 21:46:31] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.746566, 'x3': 0.592252, 'x4': 0.738688, 'x5': 0.73441, 'x6': 0.258743, 'x7': 0.657317, 'x8': 0.899448, 'x9': 0.709614, 'x11': 0.784887, 'x12': 0.810226, 'x13': 0.631987, 'x14': 0.25858, 'x15': 0.398308, 'x16': 0.101475, 'x17': 0.556088, 'x18': 0.169673, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:46:32] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.341176, None)}.\n",
- "[INFO 09-08 21:46:41] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.705063, 'x3': 0.566176, 'x4': 0.74797, 'x5': 0.801617, 'x6': 0.129428, 'x7': 0.576657, 'x8': 0.959598, 'x9': 0.725797, 'x11': 0.857249, 'x12': 0.858444, 'x13': 0.645301, 'x14': 0.132484, 'x15': 0.422146, 'x16': 0.113523, 'x17': 0.616683, 'x18': 0.204737, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:46:43] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.354976, None)}.\n",
- "[INFO 09-08 21:46:52] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.739902, 'x3': 0.611881, 'x4': 0.904355, 'x5': 0.727186, 'x6': 0.204863, 'x7': 0.621783, 'x8': 0.881429, 'x9': 0.74313, 'x11': 0.762982, 'x12': 0.877638, 'x13': 0.549703, 'x14': 0.20749, 'x15': 0.45216, 'x16': 0.070013, 'x17': 0.568056, 'x18': 0.114567, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:46:53] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.330138, None)}.\n",
- "[INFO 09-08 21:47:02] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.936174, 'x3': 0.202034, 'x4': 0.844947, 'x5': 0.522155, 'x6': 0.585748, 'x7': 0.59405, 'x8': 0.193095, 'x9': 0.458459, 'x11': 0.371338, 'x12': 0.778063, 'x13': 0.175235, 'x14': 0.382694, 'x15': 0.312758, 'x16': 0.186762, 'x17': 0.277877, 'x18': 0.237879, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:47:03] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.335784, None)}.\n",
- "[INFO 09-08 21:47:12] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.695122, 'x3': 0.62624, 'x4': 0.829751, 'x5': 0.701795, 'x6': 0.230882, 'x7': 0.606052, 'x8': 0.931895, 'x9': 0.756772, 'x11': 0.753829, 'x12': 0.842941, 'x13': 0.550595, 'x14': 0.21921, 'x15': 0.429288, 'x16': 0.092462, 'x17': 0.599438, 'x18': 0.102422, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:47:13] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.32467, None)}.\n",
- "[INFO 09-08 21:47:22] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.448775, 'x3': 0.621376, 'x4': 0.393419, 'x5': 0.23606, 'x6': 0.523435, 'x7': 0.621944, 'x8': 0.336535, 'x9': 0.586531, 'x11': 0.788328, 'x12': 0.541945, 'x13': 0.292636, 'x14': 0.168079, 'x15': 0.209639, 'x16': 0.52499, 'x17': 0.53738, 'x18': 0.533543, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:47:24] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.328446, None)}.\n",
- "[INFO 09-08 21:47:33] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.545752, 'x3': 0.625232, 'x4': 0.351725, 'x5': 0.240621, 'x6': 0.538835, 'x7': 0.547776, 'x8': 0.313137, 'x9': 0.605815, 'x11': 0.772959, 'x12': 0.569034, 'x13': 0.308435, 'x14': 0.209514, 'x15': 0.192858, 'x16': 0.657659, 'x17': 0.633239, 'x18': 0.451019, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:47:34] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.344423, None)}.\n",
- "[INFO 09-08 21:47:43] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.842316, 'x3': 0.570341, 'x4': 0.34792, 'x5': 0.520557, 'x6': 0.779509, 'x7': 0.863213, 'x8': 0.694453, 'x9': 0.57979, 'x11': 0.553129, 'x12': 0.512034, 'x13': 0.640853, 'x14': 0.673781, 'x15': 0.139103, 'x16': 0.120097, 'x17': 0.489676, 'x18': 0.169123, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:47:44] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.360445, None)}.\n",
- "[INFO 09-08 21:47:53] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.719759, 'x3': 0.65572, 'x4': 0.861296, 'x5': 0.721259, 'x6': 0.258741, 'x7': 0.65254, 'x8': 0.940515, 'x9': 0.773492, 'x11': 0.771489, 'x12': 0.838525, 'x13': 0.569728, 'x14': 0.222733, 'x15': 0.404303, 'x16': 0.022888, 'x17': 0.639534, 'x18': 0.08268, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:47:54] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.402751, None)}.\n",
- "[INFO 09-08 21:48:04] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.68374, 'x3': 0.619523, 'x4': 0.835219, 'x5': 0.682158, 'x6': 0.171282, 'x7': 0.574093, 'x8': 0.918338, 'x9': 0.734257, 'x11': 0.7423, 'x12': 0.870437, 'x13': 0.552253, 'x14': 0.228607, 'x15': 0.491136, 'x16': 0.174278, 'x17': 0.520169, 'x18': 0.127698, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:48:05] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.347937, None)}.\n",
- "[INFO 09-08 21:48:14] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.482904, 'x3': 0.68512, 'x4': 0.419392, 'x5': 0.153039, 'x6': 0.488413, 'x7': 0.647245, 'x8': 0.277682, 'x9': 0.571358, 'x11': 0.731584, 'x12': 0.519656, 'x13': 0.290422, 'x14': 0.186327, 'x15': 0.243278, 'x16': 0.587644, 'x17': 0.587862, 'x18': 0.543239, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:48:15] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.330918, None)}.\n",
- "[INFO 09-08 21:48:25] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.426967, 'x3': 0.660217, 'x4': 0.377024, 'x5': 0.277899, 'x6': 0.565413, 'x7': 0.608391, 'x8': 0.302286, 'x9': 0.485674, 'x11': 0.802657, 'x12': 0.49861, 'x13': 0.229639, 'x14': 0.160682, 'x15': 0.212373, 'x16': 0.589782, 'x17': 0.547107, 'x18': 0.483786, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:48:26] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.337022, None)}.\n",
- "[WARNING 09-08 21:48:26] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:48:26] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:48:26] ax.service.ax_client: Random seed set to 463. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:48:26] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:48:26] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:48:26] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:48:26] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:48:26] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:48:26] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:48:26] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:48:26] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:26] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.90946, 'x3': 0.707464, 'x4': 0.339527, 'x5': 0.237512, 'x6': 0.148575, 'x7': 0.80051, 'x8': 0.223319, 'x9': 0.224284, 'x11': 0.649599, 'x12': 0.893626, 'x13': 0.210957, 'x14': 0.115641, 'x15': 0.535052, 'x16': 0.89118, 'x17': 0.558197, 'x18': 0.243695, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:27] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.371914, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:27] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.635798, 'x3': 0.180693, 'x4': 0.692095, 'x5': 0.983602, 'x6': 0.306352, 'x7': 0.685211, 'x8': 0.730563, 'x9': 0.38509, 'x11': 0.883473, 'x12': 0.719147, 'x13': 0.301658, 'x14': 0.429342, 'x15': 0.478362, 'x16': 0.021825, 'x17': 0.880246, 'x18': 0.901143, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:28] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.379974, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:28] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.478649, 'x3': 0.056265, 'x4': 0.490905, 'x5': 0.262202, 'x6': 0.720335, 'x7': 0.195846, 'x8': 0.620946, 'x9': 0.304915, 'x11': 0.82104, 'x12': 0.806958, 'x13': 0.425688, 'x14': 0.567578, 'x15': 0.258241, 'x16': 0.773367, 'x17': 0.265358, 'x18': 0.485681, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:48:30] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.376268, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:30] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.826759, 'x3': 0.260834, 'x4': 0.052519, 'x5': 0.082836, 'x6': 0.101095, 'x7': 0.509901, 'x8': 0.929929, 'x9': 0.775699, 'x11': 0.10146, 'x12': 0.127054, 'x13': 0.600924, 'x14': 0.141464, 'x15': 0.15804, 'x16': 0.5002, 'x17': 0.723545, 'x18': 0.078591, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:48:31] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.401267, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:31] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.134127, 'x3': 0.204368, 'x4': 0.094052, 'x5': 0.755796, 'x6': 0.205387, 'x7': 0.394816, 'x8': 0.529538, 'x9': 0.322587, 'x11': 0.764557, 'x12': 0.083994, 'x13': 0.047819, 'x14': 0.786327, 'x15': 0.77346, 'x16': 0.563929, 'x17': 0.953848, 'x18': 0.393784, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:32] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.516677, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:32] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.407346, 'x3': 0.683791, 'x4': 0.999357, 'x5': 0.025315, 'x6': 0.363042, 'x7': 0.025717, 'x8': 0.022011, 'x9': 0.036788, 'x11': 0.530722, 'x12': 0.286593, 'x13': 0.464934, 'x14': 0.723621, 'x15': 0.205287, 'x16': 0.445061, 'x17': 0.607889, 'x18': 0.734812, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:33] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.553157, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:33] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.325009, 'x3': 0.347024, 'x4': 0.641831, 'x5': 0.185581, 'x6': 0.387088, 'x7': 0.284966, 'x8': 0.822361, 'x9': 0.963202, 'x11': 0.220337, 'x12': 0.551209, 'x13': 0.846962, 'x14': 0.502244, 'x15': 0.578153, 'x16': 0.085067, 'x17': 0.672891, 'x18': 0.587415, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:48:35] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.524063, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:35] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.687694, 'x3': 0.559239, 'x4': 0.200486, 'x5': 0.744781, 'x6': 0.667886, 'x7': 0.608862, 'x8': 0.126265, 'x9': 0.148214, 'x11': 0.718164, 'x12': 0.249281, 'x13': 0.33895, 'x14': 0.271894, 'x15': 0.050358, 'x16': 0.693399, 'x17': 0.223265, 'x18': 0.152226, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:36] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.335668, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:36] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.098176, 'x3': 0.763841, 'x4': 0.263811, 'x5': 0.908249, 'x6': 0.044863, 'x7': 0.169743, 'x8': 0.315116, 'x9': 0.677423, 'x11': 0.48461, 'x12': 0.819377, 'x13': 0.640301, 'x14': 0.940932, 'x15': 0.40059, 'x16': 0.954908, 'x17': 0.765432, 'x18': 0.307423, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:37] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.722055, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:37] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.951505, 'x3': 0.80662, 'x4': 0.06629, 'x5': 0.535643, 'x6': 0.271902, 'x7': 0.280134, 'x8': 0.769238, 'x9': 0.629888, 'x11': 0.798928, 'x12': 0.756551, 'x13': 0.155222, 'x14': 0.351959, 'x15': 0.132892, 'x16': 0.430982, 'x17': 0.985978, 'x18': 0.200286, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:38] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.52878, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:38] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.724672, 'x3': 0.332567, 'x4': 0.965794, 'x5': 0.305163, 'x6': 0.179677, 'x7': 0.141375, 'x8': 0.27639, 'x9': 0.979487, 'x11': 0.534698, 'x12': 0.615051, 'x13': 0.361399, 'x14': 0.165681, 'x15': 0.814605, 'x16': 0.562118, 'x17': 0.577527, 'x18': 0.920264, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:39] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.468918, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:39] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.511475, 'x3': 0.636616, 'x4': 0.674387, 'x5': 0.405854, 'x6': 0.070666, 'x7': 0.415405, 'x8': 0.569904, 'x9': 0.020526, 'x11': 0.216134, 'x12': 0.348417, 'x13': 0.9505, 'x14': 0.077245, 'x15': 0.437586, 'x16': 0.921135, 'x17': 0.6407, 'x18': 0.757479, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:41] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.467715, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:41] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.784695, 'x3': 0.22517, 'x4': 0.294472, 'x5': 0.628521, 'x6': 0.47832, 'x7': 0.038334, 'x8': 0.077277, 'x9': 0.370099, 'x11': 0.450011, 'x12': 0.023184, 'x13': 0.532894, 'x14': 0.38949, 'x15': 0.509908, 'x16': 0.040979, 'x17': 0.795733, 'x18': 0.098537, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:42] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.491624, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:42] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.171367, 'x3': 0.931032, 'x4': 0.861306, 'x5': 0.194535, 'x6': 0.70144, 'x7': 0.855436, 'x8': 0.879345, 'x9': 0.554137, 'x11': 0.986365, 'x12': 0.715386, 'x13': 0.025333, 'x14': 0.651313, 'x15': 0.103222, 'x16': 0.680569, 'x17': 0.370366, 'x18': 0.662616, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:43] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.350123, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:43] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.222926, 'x3': 0.309382, 'x4': 0.367197, 'x5': 0.455713, 'x6': 0.339937, 'x7': 0.93082, 'x8': 0.477668, 'x9': 0.791991, 'x11': 0.661876, 'x12': 0.191061, 'x13': 0.115237, 'x14': 0.557859, 'x15': 0.425742, 'x16': 0.102251, 'x17': 0.525886, 'x18': 0.4137, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:48:44] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.414602, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:44] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.563463, 'x3': 0.013961, 'x4': 0.183024, 'x5': 0.134806, 'x6': 0.962901, 'x7': 0.370612, 'x8': 0.041778, 'x9': 0.258379, 'x11': 0.385349, 'x12': 0.871021, 'x13': 0.908935, 'x14': 0.233243, 'x15': 0.025699, 'x16': 0.374441, 'x17': 0.486157, 'x18': 0.006397, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:46] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.427063, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:46] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.449225, 'x3': 0.829807, 'x4': 0.725689, 'x5': 0.701803, 'x6': 0.247589, 'x7': 0.553918, 'x8': 0.970293, 'x9': 0.567384, 'x11': 0.926145, 'x12': 0.422727, 'x13': 0.401246, 'x14': 0.995058, 'x15': 0.618922, 'x16': 0.982898, 'x17': 0.910427, 'x18': 0.692316, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:47] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.40121, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:47] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.283027, 'x3': 0.13947, 'x4': 0.884222, 'x5': 0.602788, 'x6': 0.002112, 'x7': 0.764334, 'x8': 0.184595, 'x9': 0.432595, 'x11': 0.322795, 'x12': 0.65805, 'x13': 0.786856, 'x14': 0.777593, 'x15': 0.24606, 'x16': 0.623876, 'x17': 0.870323, 'x18': 0.606566, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:48] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.644525, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:48] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.880291, 'x3': 0.433915, 'x4': 0.572364, 'x5': 0.798757, 'x6': 0.629102, 'x7': 0.449238, 'x8': 0.373903, 'x9': 0.898992, 'x11': 0.59943, 'x12': 0.27502, 'x13': 0.235361, 'x14': 0.446937, 'x15': 0.330393, 'x16': 0.85254, 'x17': 0.14101, 'x18': 0.949415, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:48:49] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.354765, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:49] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.89721, 'x3': 0.98719, 'x4': 0.975574, 'x5': 0.641268, 'x6': 0.124098, 'x7': 0.35425, 'x8': 0.701574, 'x9': 0.798842, 'x11': 0.281121, 'x12': 0.928874, 'x13': 0.412874, 'x14': 0.522293, 'x15': 0.765608, 'x16': 0.235491, 'x17': 0.350211, 'x18': 0.185852, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:51] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.412087, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:51] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.686497, 'x3': 0.405838, 'x4': 0.119036, 'x5': 0.387374, 'x6': 0.467299, 'x7': 0.223508, 'x8': 0.194199, 'x9': 0.591782, 'x11': 0.01393, 'x12': 0.691713, 'x13': 0.072421, 'x14': 0.960068, 'x15': 0.193148, 'x16': 0.867111, 'x17': 0.211284, 'x18': 0.965936, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:52] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.476739, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:52] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.468584, 'x3': 0.28033, 'x4': 0.824217, 'x5': 0.859253, 'x6': 0.506503, 'x7': 0.64253, 'x8': 0.079215, 'x9': 0.733958, 'x11': 0.201479, 'x12': 0.779706, 'x13': 0.200359, 'x14': 0.036673, 'x15': 0.035581, 'x16': 0.115571, 'x17': 0.580809, 'x18': 0.428273, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:53] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.321792, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:53] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.581213, 'x3': 0.563467, 'x4': 0.27301, 'x5': 0.292294, 'x6': 0.282358, 'x7': 0.466083, 'x8': 0.900692, 'x9': 0.408227, 'x11': 0.734948, 'x12': 0.458347, 'x13': 0.739705, 'x14': 0.798502, 'x15': 0.570286, 'x16': 0.725868, 'x17': 0.006998, 'x18': 0.864195, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:48:54] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.453299, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:54] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.870538, 'x3': 0.044478, 'x4': 0.633391, 'x5': 0.554001, 'x6': 0.12568, 'x7': 0.081405, 'x8': 0.393538, 'x9': 0.201148, 'x11': 0.969771, 'x12': 0.162239, 'x13': 0.774985, 'x14': 0.734761, 'x15': 0.388467, 'x16': 0.34522, 'x17': 0.43157, 'x18': 0.023075, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:48:56] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.481366, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:56] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.184265, 'x3': 0.492029, 'x4': 0.715939, 'x5': 0.350043, 'x6': 0.052149, 'x7': 0.950387, 'x8': 0.051742, 'x9': 0.654286, 'x11': 0.132838, 'x12': 0.11155, 'x13': 0.326393, 'x14': 0.317918, 'x15': 0.550884, 'x16': 0.281997, 'x17': 0.138398, 'x18': 0.457913, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:48:57] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.433376, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:57] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.797188, 'x3': 0.664205, 'x4': 0.126402, 'x5': 0.784052, 'x6': 0.768479, 'x7': 0.126487, 'x8': 0.999666, 'x9': 0.453529, 'x11': 0.67847, 'x12': 0.680701, 'x13': 0.865623, 'x14': 0.579756, 'x15': 0.085498, 'x16': 0.923653, 'x17': 0.711113, 'x18': 0.771993, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:48:58] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.426015, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:58] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.39542, 'x3': 0.901002, 'x4': 0.314481, 'x5': 0.619578, 'x6': 0.395473, 'x7': 0.565602, 'x8': 0.558894, 'x9': 0.986339, 'x11': 0.400006, 'x12': 0.251224, 'x13': 0.159038, 'x14': 0.129164, 'x15': 0.498206, 'x16': 0.662152, 'x17': 0.30029, 'x18': 0.679357, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:48:59] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.44538, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:48:59] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.740011, 'x3': 0.775615, 'x4': 0.609483, 'x5': 0.149632, 'x6': 0.575066, 'x7': 0.052739, 'x8': 0.667538, 'x9': 0.812913, 'x11': 0.337436, 'x12': 0.21434, 'x13': 0.036959, 'x14': 0.86605, 'x15': 0.280816, 'x16': 0.413816, 'x17': 0.931252, 'x18': 0.215066, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:49:00] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.411496, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:00] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.079589, 'x3': 0.539794, 'x4': 0.925249, 'x5': 0.439045, 'x6': 0.198025, 'x7': 0.738928, 'x8': 0.851964, 'x9': 0.345731, 'x11': 0.61604, 'x12': 0.846873, 'x13': 0.985746, 'x14': 0.409413, 'x15': 0.177899, 'x16': 0.172265, 'x17': 0.080845, 'x18': 0.372155, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:49:02] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.467844, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:02] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.995731, 'x3': 0.530674, 'x4': 0.748723, 'x5': 0.070196, 'x6': 0.485698, 'x7': 0.819961, 'x8': 0.306121, 'x9': 0.33072, 'x11': 0.176716, 'x12': 0.783742, 'x13': 0.468994, 'x14': 0.758642, 'x15': 0.410202, 'x16': 0.711816, 'x17': 0.168586, 'x18': 0.135547, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:49:03] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.405598, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:03] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.706939, 'x3': 0.111446, 'x4': 0.345372, 'x5': 0.839731, 'x6': 0.078898, 'x7': 0.697009, 'x8': 0.798594, 'x9': 0.059905, 'x11': 0.411535, 'x12': 0.580046, 'x13': 0.01257, 'x14': 0.696375, 'x15': 0.607638, 'x16': 0.341976, 'x17': 0.267971, 'x18': 0.978037, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:49:04] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.361064, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:04] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.342873, 'x3': 0.794847, 'x4': 0.8104, 'x5': 0.280569, 'x6': 0.866456, 'x7': 0.379926, 'x8': 0.244697, 'x9': 0.86012, 'x11': 0.902035, 'x12': 0.151139, 'x13': 0.551273, 'x14': 0.46601, 'x15': 0.013361, 'x16': 0.95239, 'x17': 0.820263, 'x18': 0.29285, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:49:05] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.426237, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:05] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.560759, 'x3': 0.919398, 'x4': 0.01539, 'x5': 0.99612, 'x6': 0.171307, 'x7': 0.984525, 'x8': 0.106752, 'x9': 0.940116, 'x11': 0.839588, 'x12': 0.313474, 'x13': 0.675303, 'x14': 0.546538, 'x15': 0.230505, 'x16': 0.201703, 'x17': 0.45028, 'x18': 0.812941, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:49:07] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.331467, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:07] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.15093, 'x3': 0.656204, 'x4': 0.449869, 'x5': 0.660808, 'x6': 0.540473, 'x7': 0.299377, 'x8': 0.420618, 'x9': 0.469509, 'x11': 0.114163, 'x12': 0.742884, 'x13': 0.350821, 'x14': 0.244442, 'x15': 0.318039, 'x16': 0.462227, 'x17': 0.537372, 'x18': 0.720091, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:49:08] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.362051, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:08] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.204777, 'x3': 0.025746, 'x4': 0.942698, 'x5': 0.923066, 'x6': 0.4328, 'x7': 0.469062, 'x8': 0.941304, 'x9': 0.247401, 'x11': 0.284349, 'x12': 0.226188, 'x13': 0.258597, 'x14': 0.08936, 'x15': 0.156168, 'x16': 0.758794, 'x17': 0.319841, 'x18': 0.469222, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:49:09] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.522511, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:09] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.494103, 'x3': 0.616376, 'x4': 0.088176, 'x5': 0.169172, 'x6': 0.026122, 'x7': 0.107722, 'x8': 0.448548, 'x9': 0.393224, 'x11': 0.049507, 'x12': 0.395413, 'x13': 0.222829, 'x14': 0.400691, 'x15': 0.833838, 'x16': 0.140419, 'x17': 0.243422, 'x18': 0.628134, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:49:10] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.499388, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:10] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.269677, 'x3': 0.414317, 'x4': 0.30091, 'x5': 0.01062, 'x6': 0.223748, 'x7': 0.335774, 'x8': 0.648204, 'x9': 0.606763, 'x11': 0.699602, 'x12': 0.630797, 'x13': 0.589298, 'x14': 0.372069, 'x15': 0.460846, 'x16': 0.280685, 'x17': 0.037306, 'x18': 0.541766, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:49:12] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.419644, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:49:12] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.922472, 'x3': 0.151152, 'x4': 0.241492, 'x5': 0.330521, 'x6': 0.596698, 'x7': 0.895987, 'x8': 0.832172, 'x9': 0.077363, 'x11': 0.471923, 'x12': 0.310207, 'x13': 0.390442, 'x14': 0.915128, 'x15': 0.123342, 'x16': 0.008503, 'x17': 0.950567, 'x18': 0.88663, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:49:13] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.289246, None)}.\n",
- "[INFO 09-08 21:49:22] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.89518, 'x3': 0.155464, 'x4': 0.253586, 'x5': 0.393612, 'x6': 0.537761, 'x7': 0.878084, 'x8': 0.829187, 'x9': 0.079118, 'x11': 0.473094, 'x12': 0.349643, 'x13': 0.340835, 'x14': 0.882169, 'x15': 0.180773, 'x16': 0.058258, 'x17': 0.859488, 'x18': 0.893274, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:49:23] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.27157, None)}.\n",
- "[INFO 09-08 21:49:33] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.521075, 'x3': 0.309984, 'x4': 0.817174, 'x5': 0.942199, 'x6': 0.657033, 'x7': 0.627115, 'x8': 0.081674, 'x9': 0.79781, 'x11': 0.20412, 'x12': 0.80129, 'x13': 0.044531, 'x14': 0.0, 'x15': 0.011983, 'x16': 0.0, 'x17': 0.497304, 'x18': 0.425744, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:49:34] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.34606, None)}.\n",
- "[INFO 09-08 21:49:44] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.442033, 'x3': 0.304065, 'x4': 0.80256, 'x5': 0.80149, 'x6': 0.475494, 'x7': 0.596623, 'x8': 0.0, 'x9': 0.795977, 'x11': 0.069108, 'x12': 0.811448, 'x13': 0.192307, 'x14': 0.0, 'x15': 0.0, 'x16': 0.003451, 'x17': 0.574974, 'x18': 0.266106, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model BoTorch.\n",
- "[INFO 09-08 21:49:45] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.322306, None)}.\n",
- "[INFO 09-08 21:49:55] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.760003, 'x3': 0.589909, 'x4': 0.233132, 'x5': 0.597876, 'x6': 0.537149, 'x7': 0.694871, 'x8': 0.187978, 'x9': 0.159841, 'x11': 0.706908, 'x12': 0.42841, 'x13': 0.287389, 'x14': 0.242413, 'x15': 0.177333, 'x16': 0.727158, 'x17': 0.301409, 'x18': 0.210387, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:49:56] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.340112, None)}.\n",
- "[INFO 09-08 21:50:06] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.898678, 'x3': 0.160955, 'x4': 0.25075, 'x5': 0.384292, 'x6': 0.544675, 'x7': 0.87552, 'x8': 0.816166, 'x9': 0.078623, 'x11': 0.474925, 'x12': 0.340361, 'x13': 0.348614, 'x14': 0.877045, 'x15': 0.172281, 'x16': 0.060933, 'x17': 0.866077, 'x18': 0.880064, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:50:07] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.274947, None)}.\n",
- "[INFO 09-08 21:50:17] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.892679, 'x3': 0.135515, 'x4': 0.258422, 'x5': 0.403746, 'x6': 0.530555, 'x7': 0.887555, 'x8': 0.866312, 'x9': 0.078876, 'x11': 0.46434, 'x12': 0.36335, 'x13': 0.332418, 'x14': 0.907996, 'x15': 0.192061, 'x16': 0.034569, 'x17': 0.867036, 'x18': 0.930563, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:50:18] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.284003, None)}.\n",
- "[INFO 09-08 21:50:28] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.889818, 'x3': 0.211016, 'x4': 0.257569, 'x5': 0.387634, 'x6': 0.603246, 'x7': 0.93786, 'x8': 0.865943, 'x9': 0.10466, 'x11': 0.535919, 'x12': 0.402563, 'x13': 0.32723, 'x14': 0.847101, 'x15': 0.135149, 'x16': 0.101635, 'x17': 0.825224, 'x18': 0.883502, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:50:29] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.286555, None)}.\n",
- "[INFO 09-08 21:50:38] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.896497, 'x3': 0.169062, 'x4': 0.248287, 'x5': 0.39828, 'x6': 0.543537, 'x7': 0.883007, 'x8': 0.819431, 'x9': 0.078515, 'x11': 0.483667, 'x12': 0.354626, 'x13': 0.33747, 'x14': 0.861844, 'x15': 0.174409, 'x16': 0.080029, 'x17': 0.839553, 'x18': 0.878455, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:50:40] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.285178, None)}.\n",
- "[INFO 09-08 21:50:50] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.84181, 'x3': 0.202343, 'x4': 0.327636, 'x5': 0.337554, 'x6': 0.557432, 'x7': 0.854498, 'x8': 0.825418, 'x9': 0.147517, 'x11': 0.508647, 'x12': 0.363005, 'x13': 0.342925, 'x14': 0.904089, 'x15': 0.18636, 'x16': 0.043399, 'x17': 0.907564, 'x18': 0.874573, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:50:52] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.2905, None)}.\n",
- "[INFO 09-08 21:51:01] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.893694, 'x3': 0.169638, 'x4': 0.259694, 'x5': 0.371902, 'x6': 0.571681, 'x7': 0.888059, 'x8': 0.837013, 'x9': 0.089312, 'x11': 0.488539, 'x12': 0.355033, 'x13': 0.355996, 'x14': 0.888752, 'x15': 0.153051, 'x16': 0.05082, 'x17': 0.882371, 'x18': 0.891026, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:51:02] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.288359, None)}.\n",
- "[INFO 09-08 21:51:11] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.933727, 'x3': 0.15753, 'x4': 0.248233, 'x5': 0.329854, 'x6': 0.489789, 'x7': 0.950663, 'x8': 0.834522, 'x9': 0.113733, 'x11': 0.473724, 'x12': 0.263879, 'x13': 0.275714, 'x14': 0.865428, 'x15': 0.245902, 'x16': 0.047888, 'x17': 0.896762, 'x18': 0.840519, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:51:12] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.278928, None)}.\n",
- "[INFO 09-08 21:51:21] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.909569, 'x3': 0.145246, 'x4': 0.253432, 'x5': 0.364977, 'x6': 0.497673, 'x7': 0.885528, 'x8': 0.810729, 'x9': 0.089703, 'x11': 0.459078, 'x12': 0.293908, 'x13': 0.316399, 'x14': 0.881002, 'x15': 0.2231, 'x16': 0.045775, 'x17': 0.882458, 'x18': 0.864847, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:51:23] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.288548, None)}.\n",
- "[WARNING 09-08 21:51:23] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:51:23] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:51:23] ax.service.ax_client: Random seed set to 845. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:51:23] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:51:23] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:51:23] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:51:23] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:51:23] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:51:23] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:51:23] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:51:23] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:23] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.258792, 'x3': 0.207902, 'x4': 0.14693, 'x5': 0.710134, 'x6': 0.047573, 'x7': 0.214425, 'x8': 0.773715, 'x9': 0.828612, 'x11': 0.897573, 'x12': 0.815782, 'x13': 0.832383, 'x14': 0.699942, 'x15': 0.354475, 'x16': 0.189247, 'x17': 0.33883, 'x18': 0.339577, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:24] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.696635, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:24] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.238537, 'x3': 0.457952, 'x4': 0.649696, 'x5': 0.193162, 'x6': 0.30758, 'x7': 0.020376, 'x8': 0.732989, 'x9': 0.023406, 'x11': 0.301656, 'x12': 0.419373, 'x13': 0.464937, 'x14': 0.783583, 'x15': 0.011778, 'x16': 0.786256, 'x17': 0.045681, 'x18': 0.823868, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:25] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.429809, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:25] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.472606, 'x3': 0.897201, 'x4': 0.331572, 'x5': 0.558874, 'x6': 0.188885, 'x7': 0.469078, 'x8': 0.33195, 'x9': 0.424265, 'x11': 0.196681, 'x12': 0.165425, 'x13': 0.124483, 'x14': 0.567719, 'x15': 0.598158, 'x16': 0.334216, 'x17': 0.448632, 'x18': 0.403487, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:26] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.467175, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:26] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.734786, 'x3': 0.7477, 'x4': 0.269822, 'x5': 0.180432, 'x6': 0.088537, 'x7': 0.756458, 'x8': 0.094056, 'x9': 0.624535, 'x11': 0.676847, 'x12': 0.102447, 'x13': 0.963306, 'x14': 0.058665, 'x15': 0.097301, 'x16': 0.274345, 'x17': 0.236885, 'x18': 0.099379, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:28] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.430054, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:28] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.976425, 'x3': 0.187432, 'x4': 0.717292, 'x5': 0.563746, 'x6': 0.407425, 'x7': 0.736418, 'x8': 0.965997, 'x9': 0.962904, 'x11': 0.82088, 'x12': 0.356395, 'x13': 0.61821, 'x14': 0.339027, 'x15': 0.510921, 'x16': 0.855412, 'x17': 0.272648, 'x18': 0.675096, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:29] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.370363, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:29] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.762855, 'x3': 0.997749, 'x4': 0.776805, 'x5': 0.666147, 'x6': 0.329017, 'x7': 0.947095, 'x8': 0.397019, 'x9': 0.304742, 'x11': 0.022397, 'x12': 0.631637, 'x13': 0.330231, 'x14': 0.455859, 'x15': 0.255211, 'x16': 0.74611, 'x17': 0.381475, 'x18': 0.615106, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:30] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.334157, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:30] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.358783, 'x3': 0.563622, 'x4': 0.588479, 'x5': 0.768435, 'x6': 0.650625, 'x7': 0.106656, 'x8': 0.197539, 'x9': 0.655916, 'x11': 0.55104, 'x12': 0.485359, 'x13': 0.755341, 'x14': 0.557611, 'x15': 0.196375, 'x16': 0.939501, 'x17': 0.978618, 'x18': 0.951843, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:31] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.406058, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:31] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.081188, 'x3': 0.953388, 'x4': 0.744644, 'x5': 0.914206, 'x6': 0.009686, 'x7': 0.511668, 'x8': 0.602491, 'x9': 0.254218, 'x11': 0.864037, 'x12': 0.719705, 'x13': 0.651343, 'x14': 0.61161, 'x15': 0.032963, 'x16': 0.357017, 'x17': 0.287726, 'x18': 0.923699, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:32] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.826315, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:32] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.949393, 'x3': 0.856225, 'x4': 0.426109, 'x5': 0.001978, 'x6': 0.696774, 'x7': 0.344091, 'x8': 0.690325, 'x9': 0.473144, 'x11': 0.989817, 'x12': 0.868272, 'x13': 0.568288, 'x14': 0.113911, 'x15': 0.136187, 'x16': 0.929155, 'x17': 0.56071, 'x18': 0.026072, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:34] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.352082, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:34] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.420292, 'x3': 0.703438, 'x4': 0.23998, 'x5': 0.432391, 'x6': 0.253584, 'x7': 0.692129, 'x8': 0.90448, 'x9': 0.566261, 'x11': 0.460198, 'x12': 0.014488, 'x13': 0.0183, 'x14': 0.902923, 'x15': 0.319535, 'x16': 0.634263, 'x17': 0.080632, 'x18': 0.407974, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:35] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.365771, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:35] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.916297, 'x3': 0.49318, 'x4': 0.867903, 'x5': 0.445113, 'x6': 0.097613, 'x7': 0.459946, 'x8': 0.266522, 'x9': 0.042633, 'x11': 0.584763, 'x12': 0.448494, 'x13': 0.520299, 'x14': 0.127831, 'x15': 0.289648, 'x16': 0.17646, 'x17': 0.139427, 'x18': 0.640275, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:36] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.459105, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:36] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.813216, 'x3': 0.682967, 'x4': 0.684846, 'x5': 0.293638, 'x6': 0.142736, 'x7': 0.231659, 'x8': 0.839147, 'x9': 0.696919, 'x11': 0.258514, 'x12': 0.532688, 'x13': 0.312428, 'x14': 0.010755, 'x15': 0.53797, 'x16': 0.284442, 'x17': 0.030602, 'x18': 0.571497, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:37] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.47096, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:37] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.585006, 'x3': 0.24323, 'x4': 0.366721, 'x5': 0.95817, 'x6': 0.353227, 'x7': 0.2751, 'x8': 0.224821, 'x9': 0.855592, 'x11': 0.239457, 'x12': 0.786551, 'x13': 0.152885, 'x14': 0.355683, 'x15': 0.07659, 'x16': 0.828461, 'x17': 0.495082, 'x18': 0.155981, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:39] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.392912, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:39] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.304822, 'x3': 0.364193, 'x4': 0.70164, 'x5': 0.417633, 'x6': 0.205313, 'x7': 0.901447, 'x8': 0.154927, 'x9': 0.392199, 'x11': 0.322554, 'x12': 0.845652, 'x13': 0.550887, 'x14': 0.445712, 'x15': 0.111847, 'x16': 0.624366, 'x17': 0.938108, 'x18': 0.305197, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:40] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.472657, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:40] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.04646, 'x3': 0.80336, 'x4': 0.254606, 'x5': 0.830253, 'x6': 0.290653, 'x7': 0.609003, 'x8': 0.785016, 'x9': 0.05088, 'x11': 0.179475, 'x12': 0.599517, 'x13': 0.897931, 'x14': 0.171218, 'x15': 0.525406, 'x16': 0.011983, 'x17': 0.536376, 'x18': 0.982462, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:41] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.581074, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:41] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.192753, 'x3': 0.114242, 'x4': 0.188738, 'x5': 0.930943, 'x6': 0.461414, 'x7': 0.832377, 'x8': 0.352025, 'x9': 0.709064, 'x11': 0.978225, 'x12': 0.390499, 'x13': 0.183958, 'x14': 0.037807, 'x15': 0.270008, 'x16': 0.402039, 'x17': 0.676453, 'x18': 0.789643, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:42] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.377659, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:42] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.663255, 'x3': 0.445725, 'x4': 0.37566, 'x5': 0.501508, 'x6': 0.518225, 'x7': 0.235103, 'x8': 0.051463, 'x9': 0.361034, 'x11': 0.448361, 'x12': 0.742267, 'x13': 0.729551, 'x14': 0.951676, 'x15': 0.211168, 'x16': 0.161836, 'x17': 0.211014, 'x18': 0.644447, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:44] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.350721, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:44] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.455876, 'x3': 0.55341, 'x4': 0.761268, 'x5': 0.313281, 'x6': 0.035035, 'x7': 0.657048, 'x8': 0.708035, 'x9': 0.862861, 'x11': 0.519716, 'x12': 0.136519, 'x13': 0.280516, 'x14': 0.314017, 'x15': 0.872012, 'x16': 0.977222, 'x17': 0.829159, 'x18': 0.498137, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:45] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.533566, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:45] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.688752, 'x3': 0.841485, 'x4': 0.824472, 'x5': 0.941673, 'x6': 0.179818, 'x7': 0.068465, 'x8': 0.975333, 'x9': 0.185932, 'x11': 0.101813, 'x12': 0.072544, 'x13': 0.681805, 'x14': 0.805448, 'x15': 0.370917, 'x16': 0.912589, 'x17': 0.602512, 'x18': 0.006836, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:46] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.558743, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:46] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.808632, 'x3': 0.591535, 'x4': 0.315906, 'x5': 0.459622, 'x6': 0.424205, 'x7': 0.134111, 'x8': 0.515998, 'x9': 0.994069, 'x11': 0.69895, 'x12': 0.660543, 'x13': 0.049254, 'x14': 0.709081, 'x15': 0.028463, 'x16': 0.065018, 'x17': 0.778108, 'x18': 0.522347, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:48] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.371558, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:48] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.542702, 'x3': 0.031195, 'x4': 0.634466, 'x5': 0.796031, 'x6': 0.072266, 'x7': 0.372925, 'x8': 0.419066, 'x9': 0.590241, 'x11': 0.802957, 'x12': 0.906678, 'x13': 0.391659, 'x14': 0.922982, 'x15': 0.614904, 'x16': 0.548374, 'x17': 0.743563, 'x18': 0.187919, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:49] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.580947, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:49] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.095707, 'x3': 0.609674, 'x4': 0.158744, 'x5': 0.207645, 'x6': 0.22986, 'x7': 0.323692, 'x8': 0.482538, 'x9': 0.943064, 'x11': 0.415592, 'x12': 0.689776, 'x13': 0.994867, 'x14': 0.365831, 'x15': 0.306349, 'x16': 0.956077, 'x17': 0.934359, 'x18': 0.955941, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:50] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.636945, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:50] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.13374, 'x3': 0.298896, 'x4': 0.351069, 'x5': 0.062272, 'x6': 0.026114, 'x7': 0.110053, 'x8': 0.91185, 'x9': 0.288817, 'x11': 0.742108, 'x12': 0.289481, 'x13': 0.20469, 'x14': 0.499485, 'x15': 0.554486, 'x16': 0.567325, 'x17': 0.794285, 'x18': 0.76996, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:51] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.831753, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:51] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.997125, 'x3': 0.7, 'x4': 0.980818, 'x5': 0.87355, 'x6': 0.542925, 'x7': 0.532098, 'x8': 0.316443, 'x9': 0.786731, 'x11': 0.289812, 'x12': 0.839548, 'x13': 0.786784, 'x14': 0.859805, 'x15': 0.393585, 'x16': 0.25966, 'x17': 0.160415, 'x18': 0.118706, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:53] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.363027, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:53] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.40553, 'x3': 0.859724, 'x4': 0.669628, 'x5': 0.693611, 'x6': 0.469852, 'x7': 0.379129, 'x8': 0.024178, 'x9': 0.127177, 'x11': 0.760165, 'x12': 0.04343, 'x13': 0.362284, 'x14': 0.148691, 'x15': 0.093046, 'x16': 0.054611, 'x17': 0.696259, 'x18': 0.440428, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:54] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.292567, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:54] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.637551, 'x3': 0.526627, 'x4': 0.728976, 'x5': 0.065228, 'x6': 0.370005, 'x7': 0.846621, 'x8': 0.292454, 'x9': 0.827936, 'x11': 0.36533, 'x12': 0.2324, 'x13': 0.710869, 'x14': 0.719761, 'x15': 0.586327, 'x16': 0.118398, 'x17': 0.985412, 'x18': 0.056732, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:51:55] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.328702, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:55] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.901772, 'x3': 0.086971, 'x4': 0.281941, 'x5': 0.682919, 'x6': 0.126464, 'x7': 0.646954, 'x8': 0.646511, 'x9': 0.728803, 'x11': 0.136333, 'x12': 0.478451, 'x13': 0.863826, 'x14': 0.881056, 'x15': 0.047768, 'x16': 0.509895, 'x17': 0.520199, 'x18': 0.731049, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:51:56] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.47037, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:56] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.004293, 'x3': 0.224167, 'x4': 0.6078, 'x5': 0.26702, 'x6': 0.564376, 'x7': 0.497866, 'x8': 0.558659, 'x9': 0.510152, 'x11': 0.010552, 'x12': 0.109409, 'x13': 0.91758, 'x14': 0.375852, 'x15': 0.150751, 'x16': 0.203859, 'x17': 0.261857, 'x18': 0.320268, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:58] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.883973, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:58] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.860931, 'x3': 0.776677, 'x4': 0.2239, 'x5': 0.578286, 'x6': 0.109994, 'x7': 0.919674, 'x8': 0.216448, 'x9': 0.00808, 'x11': 0.958867, 'x12': 0.503747, 'x13': 0.093425, 'x14': 0.765468, 'x15': 0.811107, 'x16': 0.904133, 'x17': 0.630124, 'x18': 0.541054, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:51:59] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.425872, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:51:59] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.599762, 'x3': 0.337021, 'x4': 0.796431, 'x5': 0.16571, 'x6': 0.385984, 'x7': 0.587115, 'x8': 0.844584, 'x9': 0.419691, 'x11': 0.53944, 'x12': 0.757581, 'x13': 0.496864, 'x14': 0.602469, 'x15': 0.334103, 'x16': 0.483185, 'x17': 0.844359, 'x18': 0.246605, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:52:00] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.367525, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:52:00] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.273552, 'x3': 0.442807, 'x4': 0.770056, 'x5': 0.07561, 'x6': 0.730961, 'x7': 0.391367, 'x8': 0.365502, 'x9': 0.945513, 'x11': 0.185506, 'x12': 0.80331, 'x13': 0.380171, 'x14': 0.506727, 'x15': 0.06091, 'x16': 0.893172, 'x17': 0.767986, 'x18': 0.562015, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:52:01] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.449835, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:52:01] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.869459, 'x3': 0.119113, 'x4': 0.583381, 'x5': 0.489924, 'x6': 0.287431, 'x7': 0.550928, 'x8': 0.041556, 'x9': 0.108957, 'x11': 0.655617, 'x12': 0.06383, 'x13': 0.955183, 'x14': 0.483221, 'x15': 0.486449, 'x16': 0.668532, 'x17': 0.373844, 'x18': 0.879827, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:52:03] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.408831, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:52:03] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.631902, 'x3': 0.369071, 'x4': 0.088254, 'x5': 0.975889, 'x6': 0.043049, 'x7': 0.745521, 'x8': 0.465156, 'x9': 0.789162, 'x11': 0.059211, 'x12': 0.671329, 'x13': 0.338256, 'x14': 5.9e-05, 'x15': 0.145428, 'x16': 0.320779, 'x17': 0.010621, 'x18': 0.395434, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:52:04] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.36625, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:52:04] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.395051, 'x3': 0.018504, 'x4': 0.028889, 'x5': 0.347432, 'x6': 0.17953, 'x7': 0.028943, 'x8': 0.234295, 'x9': 0.224543, 'x11': 0.563294, 'x12': 0.608346, 'x13': 0.74931, 'x14': 0.618428, 'x15': 0.644327, 'x16': 0.256513, 'x17': 0.299895, 'x18': 0.105487, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:52:05] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.507735, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:52:05] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.720174, 'x3': 0.98065, 'x4': 0.647163, 'x5': 0.533702, 'x6': 0.631467, 'x7': 0.575976, 'x8': 0.514033, 'x9': 0.726371, 'x11': 0.406248, 'x12': 0.028494, 'x13': 0.261215, 'x14': 0.240527, 'x15': 0.303737, 'x16': 0.573974, 'x17': 0.681689, 'x18': 0.751932, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:52:06] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.420184, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:52:06] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.128145, 'x3': 0.578829, 'x4': 0.960302, 'x5': 0.900637, 'x6': 0.324508, 'x7': 0.477694, 'x8': 0.830647, 'x9': 0.312911, 'x11': 0.93489, 'x12': 0.854397, 'x13': 0.840011, 'x14': 0.779779, 'x15': 0.245385, 'x16': 0.864958, 'x17': 0.209684, 'x18': 0.682171, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:52:08] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.549282, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:52:08] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.777554, 'x3': 0.730692, 'x4': 0.149961, 'x5': 0.047255, 'x6': 0.887573, 'x7': 0.627453, 'x8': 0.992687, 'x9': 0.406515, 'x11': 0.808622, 'x12': 0.737309, 'x13': 0.87817, 'x14': 0.273997, 'x15': 0.080025, 'x16': 0.421227, 'x17': 0.951401, 'x18': 0.267484, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:52:09] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.330733, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:52:09] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.373513, 'x3': 0.828787, 'x4': 0.461334, 'x5': 0.383429, 'x6': 0.068402, 'x7': 0.287502, 'x8': 0.660436, 'x9': 0.507704, 'x11': 0.279953, 'x12': 0.379682, 'x13': 0.457455, 'x14': 0.734987, 'x15': 0.404002, 'x16': 0.141961, 'x17': 0.408721, 'x18': 0.166591, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:52:10] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.482091, None)}.\n",
- "[INFO 09-08 21:52:18] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.474296, 'x3': 0.831768, 'x4': 0.656426, 'x5': 0.651495, 'x6': 0.488086, 'x7': 0.396632, 'x8': 0.109825, 'x9': 0.255416, 'x11': 0.702364, 'x12': 0.099216, 'x13': 0.352629, 'x14': 0.19626, 'x15': 0.117192, 'x16': 0.162673, 'x17': 0.700051, 'x18': 0.474551, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:52:19] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.298101, None)}.\n",
- "[INFO 09-08 21:52:30] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.451093, 'x3': 0.885493, 'x4': 0.665341, 'x5': 0.674036, 'x6': 0.493071, 'x7': 0.406472, 'x8': 0.063523, 'x9': 0.199379, 'x11': 0.72246, 'x12': 0.023009, 'x13': 0.348685, 'x14': 0.147495, 'x15': 0.111165, 'x16': 0.111509, 'x17': 0.686775, 'x18': 0.47727, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:52:31] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.304103, None)}.\n",
- "[INFO 09-08 21:52:40] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.444574, 'x3': 0.792407, 'x4': 0.639571, 'x5': 0.674819, 'x6': 0.460453, 'x7': 0.354646, 'x8': 0.030178, 'x9': 0.19782, 'x11': 0.746466, 'x12': 0.138376, 'x13': 0.338228, 'x14': 0.199875, 'x15': 0.070554, 'x16': 0.077264, 'x17': 0.706004, 'x18': 0.411714, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:52:42] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.335368, None)}.\n",
- "[INFO 09-08 21:52:51] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.360981, 'x3': 0.84024, 'x4': 0.722473, 'x5': 0.673707, 'x6': 0.468318, 'x7': 0.397264, 'x8': 0.150655, 'x9': 0.100463, 'x11': 0.745052, 'x12': 0.064035, 'x13': 0.446754, 'x14': 0.182964, 'x15': 0.165463, 'x16': 0.148247, 'x17': 0.722604, 'x18': 0.490704, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:52:52] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.290792, None)}.\n",
- "[INFO 09-08 21:53:02] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.393272, 'x3': 0.860347, 'x4': 0.680261, 'x5': 0.669768, 'x6': 0.449892, 'x7': 0.418615, 'x8': 0.15346, 'x9': 0.124151, 'x11': 0.725347, 'x12': 0.062058, 'x13': 0.398509, 'x14': 0.157881, 'x15': 0.150418, 'x16': 0.08187, 'x17': 0.682551, 'x18': 0.460024, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:53:03] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.300911, None)}.\n",
- "[INFO 09-08 21:53:12] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.373586, 'x3': 0.850298, 'x4': 0.684595, 'x5': 0.724255, 'x6': 0.495723, 'x7': 0.350437, 'x8': 0.044395, 'x9': 0.150542, 'x11': 0.740612, 'x12': 0.055413, 'x13': 0.43226, 'x14': 0.177945, 'x15': 0.128012, 'x16': 0.170604, 'x17': 0.726029, 'x18': 0.538507, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:53:14] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.346232, None)}.\n",
- "[INFO 09-08 21:53:23] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.4351, 'x3': 0.83928, 'x4': 0.784552, 'x5': 0.586094, 'x6': 0.501755, 'x7': 0.433887, 'x8': 0.117631, 'x9': 0.116437, 'x11': 0.789812, 'x12': 0.017837, 'x13': 0.375335, 'x14': 0.18627, 'x15': 0.1314, 'x16': 0.146887, 'x17': 0.751481, 'x18': 0.396491, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:53:24] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.292805, None)}.\n",
- "[INFO 09-08 21:53:34] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.401075, 'x3': 0.851733, 'x4': 0.729057, 'x5': 0.637377, 'x6': 0.49866, 'x7': 0.420013, 'x8': 0.164313, 'x9': 0.145348, 'x11': 0.754423, 'x12': 0.045057, 'x13': 0.367189, 'x14': 0.177224, 'x15': 0.13473, 'x16': 0.136114, 'x17': 0.742095, 'x18': 0.421153, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:53:35] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.293142, None)}.\n",
- "[INFO 09-08 21:53:45] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.464894, 'x3': 0.81959, 'x4': 0.7419, 'x5': 0.582114, 'x6': 0.437345, 'x7': 0.4419, 'x8': 0.091242, 'x9': 0.123749, 'x11': 0.747958, 'x12': 0.051314, 'x13': 0.452946, 'x14': 0.199862, 'x15': 0.160356, 'x16': 0.151907, 'x17': 0.686837, 'x18': 0.453524, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:53:46] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.294811, None)}.\n",
- "[INFO 09-08 21:53:55] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.438926, 'x3': 0.835558, 'x4': 0.832832, 'x5': 0.632331, 'x6': 0.487584, 'x7': 0.383827, 'x8': 0.089535, 'x9': 0.014726, 'x11': 0.817326, 'x12': 0.051943, 'x13': 0.339494, 'x14': 0.145753, 'x15': 0.160989, 'x16': 0.032027, 'x17': 0.683284, 'x18': 0.483658, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:53:56] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.29413, None)}.\n",
- "[INFO 09-08 21:54:06] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.364702, 'x3': 0.856453, 'x4': 0.768562, 'x5': 0.648599, 'x6': 0.461517, 'x7': 0.420987, 'x8': 0.041806, 'x9': 0.0, 'x11': 0.813145, 'x12': 0.0, 'x13': 0.424525, 'x14': 0.123319, 'x15': 0.120993, 'x16': 0.052379, 'x17': 0.708736, 'x18': 0.397336, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:54:07] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.298272, None)}.\n",
- "[INFO 09-08 21:54:17] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.425642, 'x3': 0.889158, 'x4': 0.729244, 'x5': 0.598159, 'x6': 0.444754, 'x7': 0.385028, 'x8': 0.096088, 'x9': 0.080965, 'x11': 0.801996, 'x12': 0.0, 'x13': 0.36198, 'x14': 0.274613, 'x15': 0.163387, 'x16': 0.025061, 'x17': 0.758055, 'x18': 0.468775, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:54:18] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.322903, None)}.\n",
- "[WARNING 09-08 21:54:18] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:54:18] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:54:18] ax.service.ax_client: Random seed set to 1387. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:54:18] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:54:18] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:54:18] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:54:18] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:54:18] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:54:18] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:54:18] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:54:18] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:18] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.779072, 'x3': 0.704248, 'x4': 0.488542, 'x5': 0.508475, 'x6': 0.245524, 'x7': 0.322097, 'x8': 0.122399, 'x9': 0.015079, 'x11': 0.580674, 'x12': 0.358133, 'x13': 0.914121, 'x14': 0.981946, 'x15': 0.621331, 'x16': 0.195727, 'x17': 0.25237, 'x18': 0.252355, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:19] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.429007, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:19] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.215706, 'x3': 0.2107, 'x4': 0.960486, 'x5': 0.309374, 'x6': 0.906342, 'x7': 0.906243, 'x8': 0.548818, 'x9': 0.67071, 'x11': 0.188677, 'x12': 0.804328, 'x13': 0.494771, 'x14': 0.009477, 'x15': 0.030633, 'x16': 0.53251, 'x17': 0.749293, 'x18': 0.99497, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:20] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.364211, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:20] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.722678, 'x3': 0.414343, 'x4': 0.530591, 'x5': 0.196606, 'x6': 0.470279, 'x7': 0.080378, 'x8': 0.877393, 'x9': 0.417102, 'x11': 0.878247, 'x12': 0.165846, 'x13': 0.739824, 'x14': 0.576841, 'x15': 0.31243, 'x16': 0.812143, 'x17': 0.079437, 'x18': 0.572327, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:21] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.395271, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:22] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.910918, 'x3': 0.105777, 'x4': 0.151297, 'x5': 0.724532, 'x6': 0.038355, 'x7': 0.139029, 'x8': 0.664744, 'x9': 0.598984, 'x11': 0.027862, 'x12': 0.588136, 'x13': 0.275946, 'x14': 0.839564, 'x15': 0.214393, 'x16': 0.309873, 'x17': 0.436104, 'x18': 0.450445, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:23] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.548545, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:23] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.449437, 'x3': 0.628574, 'x4': 0.776184, 'x5': 0.663549, 'x6': 0.424949, 'x7': 0.945191, 'x8': 0.156438, 'x9': 0.173437, 'x11': 0.696168, 'x12': 0.845753, 'x13': 0.623452, 'x14': 0.496226, 'x15': 0.132831, 'x16': 0.68369, 'x17': 0.347921, 'x18': 0.831154, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:24] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.342488, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:24] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.675891, 'x3': 0.554908, 'x4': 0.085649, 'x5': 0.373409, 'x6': 0.551253, 'x7': 0.209243, 'x8': 0.056148, 'x9': 0.119189, 'x11': 0.520826, 'x12': 0.515552, 'x13': 0.654658, 'x14': 0.670046, 'x15': 0.075025, 'x16': 0.406359, 'x17': 0.536689, 'x18': 0.348148, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:25] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.445453, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:25] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.364486, 'x3': 0.061395, 'x4': 0.613746, 'x5': 0.572508, 'x6': 0.358433, 'x7': 0.50042, 'x8': 0.615073, 'x9': 0.714548, 'x11': 0.13182, 'x12': 0.084927, 'x13': 0.200153, 'x14': 0.322355, 'x15': 0.546581, 'x16': 0.821514, 'x17': 0.461647, 'x18': 0.902531, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:26] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.398522, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:26] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.137677, 'x3': 0.820013, 'x4': 0.405696, 'x5': 0.136481, 'x6': 0.115185, 'x7': 0.777296, 'x8': 0.385685, 'x9': 0.874872, 'x11': 0.335162, 'x12': 0.392208, 'x13': 0.392028, 'x14': 0.227767, 'x15': 0.355838, 'x16': 0.186478, 'x17': 0.136289, 'x18': 0.207307, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:28] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.565696, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:28] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.849303, 'x3': 0.859656, 'x4': 0.198203, 'x5': 0.498832, 'x6': 0.468368, 'x7': 0.53163, 'x8': 0.522148, 'x9': 0.836668, 'x11': 0.807861, 'x12': 0.480798, 'x13': 0.986614, 'x14': 0.696228, 'x15': 0.23888, 'x16': 0.735007, 'x17': 0.030351, 'x18': 0.281766, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:29] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.358484, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:29] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.536551, 'x3': 0.676087, 'x4': 0.577436, 'x5': 0.955525, 'x6': 0.024708, 'x7': 0.746522, 'x8': 0.809006, 'x9': 0.147432, 'x11': 0.161053, 'x12': 0.781027, 'x13': 0.028622, 'x14': 0.96671, 'x15': 0.266573, 'x16': 0.236605, 'x17': 0.485223, 'x18': 0.663904, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:30] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.439452, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:30] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.028847, 'x3': 0.949068, 'x4': 0.882393, 'x5': 0.53898, 'x6': 0.586692, 'x7': 0.298587, 'x8': 0.640511, 'x9': 0.893715, 'x11': 0.975146, 'x12': 0.126677, 'x13': 0.76806, 'x14': 0.401317, 'x15': 0.047163, 'x16': 0.481083, 'x17': 0.842533, 'x18': 0.772582, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:31] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.822036, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:31] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.965504, 'x3': 0.450436, 'x4': 0.410509, 'x5': 0.269088, 'x6': 0.253628, 'x7': 0.976491, 'x8': 0.19071, 'x9': 0.299394, 'x11': 0.364396, 'x12': 0.711595, 'x13': 0.313309, 'x14': 0.623802, 'x15': 0.581219, 'x16': 0.755395, 'x17': 0.160077, 'x18': 0.484069, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:32] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.348062, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:32] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.075756, 'x3': 0.089509, 'x4': 0.452602, 'x5': 0.891509, 'x6': 0.387873, 'x7': 0.427542, 'x8': 0.301695, 'x9': 0.564674, 'x11': 0.609912, 'x12': 0.538608, 'x13': 0.868853, 'x14': 0.369618, 'x15': 0.315878, 'x16': 0.862422, 'x17': 0.291051, 'x18': 0.056209, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:34] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.507192, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:34] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.4261, 'x3': 0.783963, 'x4': 0.53553, 'x5': 0.329199, 'x6': 0.148272, 'x7': 0.17023, 'x8': 0.699016, 'x9': 0.974938, 'x11': 0.907486, 'x12': 0.969609, 'x13': 0.535338, 'x14': 0.212226, 'x15': 0.500634, 'x16': 0.1297, 'x17': 0.118395, 'x18': 0.861296, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:35] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.511757, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:35] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.263005, 'x3': 0.405951, 'x4': 0.823029, 'x5': 0.433958, 'x6': 0.07419, 'x7': 0.353388, 'x8': 0.029474, 'x9': 0.387196, 'x11': 0.483735, 'x12': 0.207135, 'x13': 0.147161, 'x14': 0.10878, 'x15': 0.163154, 'x16': 0.361282, 'x17': 0.193127, 'x18': 0.936399, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:36] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.608811, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:36] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.802454, 'x3': 0.218968, 'x4': 0.627024, 'x5': 0.072021, 'x6': 0.510196, 'x7': 0.660577, 'x8': 0.419557, 'x9': 0.634458, 'x11': 0.669188, 'x12': 0.822666, 'x13': 0.899902, 'x14': 0.539551, 'x15': 0.382455, 'x16': 0.108504, 'x17': 0.605338, 'x18': 0.513756, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:37] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.403705, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:37] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.716674, 'x3': 0.195941, 'x4': 0.221276, 'x5': 0.944562, 'x6': 0.282624, 'x7': 0.87434, 'x8': 0.075028, 'x9': 0.998343, 'x11': 0.106888, 'x12': 0.154672, 'x13': 0.833864, 'x14': 0.247565, 'x15': 0.142817, 'x16': 0.124479, 'x17': 0.529995, 'x18': 0.524801, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:39] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.340379, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:39] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.412088, 'x3': 0.112511, 'x4': 0.921823, 'x5': 0.029407, 'x6': 0.662317, 'x7': 0.108339, 'x8': 0.208603, 'x9': 0.802585, 'x11': 0.172636, 'x12': 0.487806, 'x13': 0.92757, 'x14': 0.921399, 'x15': 0.084874, 'x16': 0.847115, 'x17': 0.343154, 'x18': 0.04589, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:40] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.440314, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:40] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.903434, 'x3': 0.262441, 'x4': 0.600741, 'x5': 0.479994, 'x6': 0.226314, 'x7': 0.909425, 'x8': 0.349693, 'x9': 0.046915, 'x11': 0.986942, 'x12': 0.607367, 'x13': 0.182516, 'x14': 0.477145, 'x15': 0.365581, 'x16': 0.622659, 'x17': 0.985829, 'x18': 0.404499, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:41] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.414612, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:41] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.950214, 'x3': 0.653129, 'x4': 0.046691, 'x5': 0.090387, 'x6': 0.799156, 'x7': 0.788382, 'x8': 0.715913, 'x9': 0.469828, 'x11': 0.598269, 'x12': 0.199032, 'x13': 0.204283, 'x14': 0.257902, 'x15': 0.005265, 'x16': 0.220842, 'x17': 0.380573, 'x18': 0.672508, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:42] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.321107, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:42] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.011856, 'x3': 0.150552, 'x4': 0.511728, 'x5': 0.852478, 'x6': 0.102689, 'x7': 0.485721, 'x8': 0.142285, 'x9': 0.813129, 'x11': 0.241242, 'x12': 0.643391, 'x13': 0.628438, 'x14': 0.730592, 'x15': 0.599626, 'x16': 0.510753, 'x17': 0.617795, 'x18': 0.070396, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:44] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.996127, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:44] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.490125, 'x3': 0.971944, 'x4': 0.475667, 'x5': 0.415105, 'x6': 0.363149, 'x7': 0.229484, 'x8': 0.857996, 'x9': 0.723423, 'x11': 0.287869, 'x12': 0.833728, 'x13': 0.966912, 'x14': 0.827197, 'x15': 0.286956, 'x16': 0.496872, 'x17': 0.792643, 'x18': 0.750414, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:45] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.392407, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:45] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.176885, 'x3': 0.53844, 'x4': 0.846358, 'x5': 0.880531, 'x6': 0.176802, 'x7': 0.053646, 'x8': 0.566741, 'x9': 0.291565, 'x11': 0.680739, 'x12': 0.412289, 'x13': 0.047958, 'x14': 0.587973, 'x15': 0.189162, 'x16': 0.998174, 'x17': 0.691774, 'x18': 0.132069, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:46] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.702927, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:46] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.840293, 'x3': 0.516251, 'x4': 0.553898, 'x5': 0.735007, 'x6': 0.280652, 'x7': 0.26318, 'x8': 0.460978, 'x9': 0.263604, 'x11': 0.208103, 'x12': 0.464751, 'x13': 0.580318, 'x14': 0.120965, 'x15': 0.337219, 'x16': 0.422304, 'x17': 0.579084, 'x18': 0.363229, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:47] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.390161, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:48] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.348215, 'x3': 0.858569, 'x4': 0.999918, 'x5': 0.755108, 'x6': 0.842697, 'x7': 0.688287, 'x8': 0.104998, 'x9': 0.508043, 'x11': 0.897947, 'x12': 0.567953, 'x13': 0.34088, 'x14': 0.559349, 'x15': 0.119126, 'x16': 0.170505, 'x17': 0.248923, 'x18': 0.190655, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:49] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.335736, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:49] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.661825, 'x3': 0.353314, 'x4': 0.464996, 'x5': 0.0482, 'x6': 0.005468, 'x7': 0.022352, 'x8': 0.538269, 'x9': 0.165535, 'x11': 0.25473, 'x12': 0.027887, 'x13': 0.765281, 'x14': 0.461864, 'x15': 0.525987, 'x16': 0.570062, 'x17': 0.753716, 'x18': 0.558148, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:50] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.774297, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:50] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.528045, 'x3': 0.957754, 'x4': 0.174371, 'x5': 0.214956, 'x6': 0.212607, 'x7': 0.454521, 'x8': 0.237104, 'x9': 0.691075, 'x11': 0.823044, 'x12': 0.789507, 'x13': 0.434796, 'x14': 0.358181, 'x15': 0.184737, 'x16': 0.92443, 'x17': 0.936712, 'x18': 0.738907, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:51] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.480957, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:51] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.113561, 'x3': 0.307883, 'x4': 0.799514, 'x5': 0.154846, 'x6': 0.326012, 'x7': 0.649232, 'x8': 0.744419, 'x9': 0.022871, 'x11': 0.404952, 'x12': 0.515843, 'x13': 0.712649, 'x14': 0.946606, 'x15': 0.233058, 'x16': 0.050583, 'x17': 0.849511, 'x18': 0.104475, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:52] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.472087, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:52] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.301313, 'x3': 0.249375, 'x4': 0.428762, 'x5': 0.674039, 'x6': 0.135746, 'x7': 0.56715, 'x8': 0.953648, 'x9': 0.962084, 'x11': 0.501462, 'x12': 0.222331, 'x13': 0.303487, 'x14': 0.715126, 'x15': 0.260509, 'x16': 0.548, 'x17': 0.634934, 'x18': 0.982095, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:54:54] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.519428, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:54] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.200484, 'x3': 0.881054, 'x4': 0.589945, 'x5': 0.113075, 'x6': 0.392559, 'x7': 0.843134, 'x8': 0.046556, 'x9': 0.622316, 'x11': 0.953796, 'x12': 0.285901, 'x13': 0.104852, 'x14': 0.874416, 'x15': 0.571355, 'x16': 0.444245, 'x17': 0.96201, 'x18': 0.161939, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:55] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.40926, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:55] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.762134, 'x3': 0.375811, 'x4': 0.124847, 'x5': 0.819978, 'x6': 0.697786, 'x7': 0.384231, 'x8': 0.596707, 'x9': 0.215814, 'x11': 0.315524, 'x12': 0.872898, 'x13': 0.556595, 'x14': 0.151679, 'x15': 0.041447, 'x16': 0.796687, 'x17': 0.035349, 'x18': 0.5912, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:56] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.417993, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:56] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.191873, 'x3': 0.251454, 'x4': 0.086517, 'x5': 0.910422, 'x6': 0.054472, 'x7': 0.514653, 'x8': 0.200952, 'x9': 0.501843, 'x11': 0.73564, 'x12': 0.840314, 'x13': 0.61374, 'x14': 0.209068, 'x15': 0.439376, 'x16': 0.205067, 'x17': 0.099547, 'x18': 0.261638, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:54:57] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.500967, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:57] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.310283, 'x3': 0.617257, 'x4': 0.925296, 'x5': 0.349348, 'x6': 0.29418, 'x7': 0.770127, 'x8': 0.799695, 'x9': 0.911679, 'x11': 0.781756, 'x12': 0.651439, 'x13': 0.790907, 'x14': 0.364476, 'x15': 0.627169, 'x16': 0.787301, 'x17': 0.303568, 'x18': 0.565993, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:54:59] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.450792, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:54:59] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.746696, 'x3': 0.123984, 'x4': 0.39092, 'x5': 0.579936, 'x6': 0.615537, 'x7': 0.44013, 'x8': 0.373323, 'x9': 0.254094, 'x11': 0.424973, 'x12': 0.189489, 'x13': 0.370396, 'x14': 0.641656, 'x15': 0.220063, 'x16': 0.452227, 'x17': 0.699163, 'x18': 0.182753, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:55:00] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.349042, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:55:00] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.379609, 'x3': 0.192766, 'x4': 0.715977, 'x5': 0.383779, 'x6': 0.485417, 'x7': 0.706124, 'x8': 0.475615, 'x9': 0.452774, 'x11': 0.35803, 'x12': 0.421786, 'x13': 0.401846, 'x14': 0.440478, 'x15': 0.03668, 'x16': 0.706123, 'x17': 0.38491, 'x18': 0.637434, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:55:01] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.430905, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:55:01] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.980739, 'x3': 0.541613, 'x4': 0.340899, 'x5': 0.447692, 'x6': 0.099071, 'x7': 0.401062, 'x8': 0.983902, 'x9': 0.776758, 'x11': 0.932589, 'x12': 0.148094, 'x13': 0.749535, 'x14': 0.84824, 'x15': 0.115244, 'x16': 0.330351, 'x17': 0.329051, 'x18': 0.018444, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:55:02] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.432653, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:55:02] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.457646, 'x3': 0.833085, 'x4': 0.146294, 'x5': 0.062442, 'x6': 0.536111, 'x7': 0.585081, 'x8': 0.589882, 'x9': 0.029984, 'x11': 0.242794, 'x12': 0.759612, 'x13': 0.485075, 'x14': 0.28468, 'x15': 0.334661, 'x16': 0.07489, 'x17': 0.998948, 'x18': 0.408365, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:55:04] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.276242, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:55:04] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.668475, 'x3': 0.98293, 'x4': 0.961588, 'x5': 0.97543, 'x6': 0.409806, 'x7': 0.31908, 'x8': 0.692649, 'x9': 0.208135, 'x11': 0.036302, 'x12': 0.597863, 'x13': 0.266128, 'x14': 0.610847, 'x15': 0.39297, 'x16': 0.828776, 'x17': 0.186739, 'x18': 0.896189, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:55:05] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.460284, None)}.\n",
- "[INFO 09-08 21:55:13] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.512693, 'x3': 0.785469, 'x4': 0.225163, 'x5': 0.170508, 'x6': 0.510842, 'x7': 0.544365, 'x8': 0.576179, 'x9': 0.090109, 'x11': 0.242341, 'x12': 0.717298, 'x13': 0.51442, 'x14': 0.274526, 'x15': 0.331371, 'x16': 0.133941, 'x17': 0.929248, 'x18': 0.410469, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:55:15] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.282904, None)}.\n",
- "[INFO 09-08 21:55:24] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.438842, 'x3': 0.838583, 'x4': 0.206341, 'x5': 0.090328, 'x6': 0.55216, 'x7': 0.585091, 'x8': 0.608582, 'x9': 0.128899, 'x11': 0.265396, 'x12': 0.767068, 'x13': 0.532306, 'x14': 0.349713, 'x15': 0.321757, 'x16': 0.116256, 'x17': 0.967865, 'x18': 0.458735, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:55:25] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.294888, None)}.\n",
- "[INFO 09-08 21:55:35] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.474042, 'x3': 0.786993, 'x4': 0.191146, 'x5': 0.108544, 'x6': 0.549562, 'x7': 0.61882, 'x8': 0.537014, 'x9': 0.060805, 'x11': 0.274737, 'x12': 0.716548, 'x13': 0.459618, 'x14': 0.262869, 'x15': 0.323711, 'x16': 0.094372, 'x17': 0.958737, 'x18': 0.395141, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:55:37] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.286694, None)}.\n",
- "[INFO 09-08 21:55:46] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.49978, 'x3': 0.829827, 'x4': 0.155161, 'x5': 0.111073, 'x6': 0.50024, 'x7': 0.543576, 'x8': 0.587887, 'x9': 0.041689, 'x11': 0.239155, 'x12': 0.733177, 'x13': 0.513178, 'x14': 0.281962, 'x15': 0.33998, 'x16': 0.095896, 'x17': 0.973717, 'x18': 0.400079, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:55:47] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.279819, None)}.\n",
- "[INFO 09-08 21:55:56] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.461807, 'x3': 0.761214, 'x4': 0.222133, 'x5': 0.107276, 'x6': 0.55402, 'x7': 0.557162, 'x8': 0.631662, 'x9': 0.025747, 'x11': 0.161664, 'x12': 0.802699, 'x13': 0.479169, 'x14': 0.210093, 'x15': 0.32855, 'x16': 0.112233, 'x17': 0.981515, 'x18': 0.440728, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:55:57] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.277886, None)}.\n",
- "[INFO 09-08 21:56:07] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.45373, 'x3': 0.801306, 'x4': 0.257572, 'x5': 0.130431, 'x6': 0.559083, 'x7': 0.526815, 'x8': 0.643644, 'x9': 0.002225, 'x11': 0.207887, 'x12': 0.790576, 'x13': 0.424764, 'x14': 0.337156, 'x15': 0.375294, 'x16': 0.088085, 'x17': 0.952282, 'x18': 0.336178, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:56:08] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.283697, None)}.\n",
- "[INFO 09-08 21:56:17] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.464875, 'x3': 0.782923, 'x4': 0.195746, 'x5': 0.11052, 'x6': 0.534199, 'x7': 0.553354, 'x8': 0.619109, 'x9': 0.031198, 'x11': 0.202657, 'x12': 0.767563, 'x13': 0.466661, 'x14': 0.276592, 'x15': 0.333843, 'x16': 0.0996, 'x17': 0.974829, 'x18': 0.396957, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:56:18] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.276646, None)}.\n",
- "[INFO 09-08 21:56:27] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.497612, 'x3': 0.872736, 'x4': 0.263336, 'x5': 0.103436, 'x6': 0.580516, 'x7': 0.556908, 'x8': 0.57557, 'x9': 0.0, 'x11': 0.230434, 'x12': 0.80706, 'x13': 0.512882, 'x14': 0.210121, 'x15': 0.396304, 'x16': 0.08178, 'x17': 0.962336, 'x18': 0.412918, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:56:28] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.29077, None)}.\n",
- "[INFO 09-08 21:56:37] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.490577, 'x3': 0.800388, 'x4': 0.167294, 'x5': 0.058219, 'x6': 0.519367, 'x7': 0.579741, 'x8': 0.633593, 'x9': 0.0, 'x11': 0.218601, 'x12': 0.769877, 'x13': 0.436272, 'x14': 0.268155, 'x15': 0.385643, 'x16': 0.165553, 'x17': 0.949653, 'x18': 0.457222, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:56:39] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.286714, None)}.\n",
- "[INFO 09-08 21:56:48] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.893886, 'x3': 0.479116, 'x4': 0.209845, 'x5': 0.256854, 'x6': 0.689529, 'x7': 0.716598, 'x8': 0.546854, 'x9': 0.371388, 'x11': 0.529845, 'x12': 0.274982, 'x13': 0.279275, 'x14': 0.413174, 'x15': 0.126415, 'x16': 0.351566, 'x17': 0.450442, 'x18': 0.522883, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:56:49] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.320878, None)}.\n",
- "[INFO 09-08 21:56:59] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.852106, 'x3': 0.41324, 'x4': 0.411648, 'x5': 0.37351, 'x6': 0.501699, 'x7': 0.782702, 'x8': 0.335244, 'x9': 0.272316, 'x11': 0.478473, 'x12': 0.49093, 'x13': 0.361158, 'x14': 0.553347, 'x15': 0.29477, 'x16': 0.549122, 'x17': 0.396955, 'x18': 0.494835, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:57:00] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.334581, None)}.\n",
- "[INFO 09-08 21:57:09] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.943566, 'x3': 0.646532, 'x4': 0.197174, 'x5': 0.142707, 'x6': 0.625752, 'x7': 0.905079, 'x8': 0.538482, 'x9': 0.401017, 'x11': 0.561878, 'x12': 0.431459, 'x13': 0.266642, 'x14': 0.35361, 'x15': 0.165789, 'x16': 0.404502, 'x17': 0.277193, 'x18': 0.69808, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model BoTorch.\n",
- "[INFO 09-08 21:57:10] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.316635, None)}.\n",
- "[WARNING 09-08 21:57:10] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n",
- "[INFO 09-08 21:57:10] ax.service.ax_client: Starting optimization with verbose logging. To disable logging, set the `verbose_logging` argument to `False`. Note that float values in the logs are rounded to 6 decimal points.\n",
- "[WARNING 09-08 21:57:10] ax.service.ax_client: Random seed set to 1685. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c1' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:352: AxParameterWarning:\n",
- "\n",
- "Changing `is_ordered` to `True` for `ChoiceParameter` 'c2' since there are only two possible values.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter c3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 21:57:10] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='c1', parameter_type=STRING, values=['c1_0', 'c1_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c2', parameter_type=STRING, values=['c2_0', 'c2_1'], is_ordered=True, sort_values=False), ChoiceParameter(name='c3', parameter_type=STRING, values=['c3_0', 'c3_1', 'c3_2'], is_ordered=False, sort_values=False)], parameter_constraints=[ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n",
- "[INFO 09-08 21:57:10] ax.core.experiment: The is_test flag has been set to True. This flag is meant purely for development and integration testing purposes. If you are running a live experiment, please set this flag to False\n",
- "[INFO 09-08 21:57:10] ax.modelbridge.dispatch_utils: Using Models.BOTORCH_MODULAR since there are more ordered parameters than there are categories for the unordered categorical parameters.\n",
- "[INFO 09-08 21:57:10] ax.modelbridge.dispatch_utils: Calculating the number of remaining initialization trials based on num_initialization_trials=None max_initialization_trials=None num_tunable_parameters=19 num_trials=None use_batch_trials=False\n",
- "[INFO 09-08 21:57:10] ax.modelbridge.dispatch_utils: calculated num_initialization_trials=38\n",
- "[INFO 09-08 21:57:10] ax.modelbridge.dispatch_utils: num_completed_initialization_trials=0 num_remaining_initialization_trials=38\n",
- "[INFO 09-08 21:57:10] ax.modelbridge.dispatch_utils: `verbose`, `disable_progbar`, and `jit_compile` are not yet supported when using `choose_generation_strategy` with ModularBoTorchModel, dropping these arguments.\n",
- "[INFO 09-08 21:57:10] ax.modelbridge.dispatch_utils: Using Bayesian Optimization generation strategy: GenerationStrategy(name='Sobol+BoTorch', steps=[Sobol for 38 trials, BoTorch for subsequent trials]). Iterations after 38 will take longer to generate due to model-fitting.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:11] ax.service.ax_client: Generated new trial 0 with parameters {'x2': 0.234832, 'x3': 0.078805, 'x4': 0.797295, 'x5': 0.140769, 'x6': 0.096473, 'x7': 0.808277, 'x8': 0.969226, 'x9': 0.659365, 'x11': 0.087406, 'x12': 0.542941, 'x13': 0.136322, 'x14': 0.521051, 'x15': 0.288823, 'x16': 0.574862, 'x17': 0.641801, 'x18': 0.085148, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:12] ax.service.ax_client: Completed trial 0 with data: {'y1': (0.453593, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:12] ax.service.ax_client: Generated new trial 1 with parameters {'x2': 0.349417, 'x3': 0.691922, 'x4': 0.167792, 'x5': 0.979599, 'x6': 0.333377, 'x7': 0.742506, 'x8': 0.192228, 'x9': 0.837998, 'x11': 0.319599, 'x12': 0.77161, 'x13': 0.261077, 'x14': 0.7552, 'x15': 0.610642, 'x16': 0.130555, 'x17': 0.862569, 'x18': 0.813668, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:13] ax.service.ax_client: Completed trial 1 with data: {'y1': (0.492125, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:13] ax.service.ax_client: Generated new trial 2 with parameters {'x2': 0.686896, 'x3': 0.455139, 'x4': 0.503, 'x5': 0.461663, 'x6': 0.553199, 'x7': 0.195657, 'x8': 0.54593, 'x9': 0.31046, 'x11': 0.650483, 'x12': 0.447637, 'x13': 0.959068, 'x14': 0.471837, 'x15': 0.220779, 'x16': 0.926506, 'x17': 0.087494, 'x18': 0.421915, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:14] ax.service.ax_client: Completed trial 2 with data: {'y1': (0.378408, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:14] ax.service.ax_client: Generated new trial 3 with parameters {'x2': 0.396632, 'x3': 0.269526, 'x4': 0.365779, 'x5': 0.842597, 'x6': 0.457498, 'x7': 0.947664, 'x8': 0.631127, 'x9': 0.385149, 'x11': 0.575809, 'x12': 0.106768, 'x13': 0.849991, 'x14': 0.912281, 'x15': 0.066151, 'x16': 0.417996, 'x17': 0.914288, 'x18': 0.963352, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:16] ax.service.ax_client: Completed trial 3 with data: {'y1': (0.458176, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:16] ax.service.ax_client: Generated new trial 4 with parameters {'x2': 0.003525, 'x3': 0.882613, 'x4': 0.731633, 'x5': 0.037047, 'x6': 0.222486, 'x7': 0.509362, 'x8': 0.409108, 'x9': 0.11258, 'x11': 0.83144, 'x12': 0.328662, 'x13': 0.725265, 'x14': 0.678656, 'x15': 0.770691, 'x16': 0.848755, 'x17': 0.572548, 'x18': 0.199691, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:17] ax.service.ax_client: Completed trial 4 with data: {'y1': (0.925502, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:17] ax.service.ax_client: Generated new trial 5 with parameters {'x2': 0.906877, 'x3': 0.679558, 'x4': 0.646031, 'x5': 0.780389, 'x6': 0.052757, 'x7': 0.15118, 'x8': 0.031977, 'x9': 0.907084, 'x11': 0.476021, 'x12': 0.398371, 'x13': 0.10031, 'x14': 0.154731, 'x15': 0.046501, 'x16': 0.752104, 'x17': 0.759049, 'x18': 0.35175, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:18] ax.service.ax_client: Completed trial 5 with data: {'y1': (0.570441, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:18] ax.service.ax_client: Generated new trial 6 with parameters {'x2': 0.694294, 'x3': 0.988841, 'x4': 0.206459, 'x5': 0.204995, 'x6': 0.375696, 'x7': 0.104532, 'x8': 0.318865, 'x9': 0.134333, 'x11': 0.987618, 'x12': 0.954356, 'x13': 0.88603, 'x14': 0.294751, 'x15': 0.324104, 'x16': 0.221225, 'x17': 0.547163, 'x18': 0.724094, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:19] ax.service.ax_client: Completed trial 6 with data: {'y1': (0.469955, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:19] ax.service.ax_client: Generated new trial 7 with parameters {'x2': 0.831359, 'x3': 0.34439, 'x4': 0.82113, 'x5': 0.916825, 'x6': 0.17883, 'x7': 0.414994, 'x8': 0.595883, 'x9': 0.359997, 'x11': 0.732025, 'x12': 0.73106, 'x13': 0.511247, 'x14': 0.059624, 'x15': 0.528735, 'x16': 0.542542, 'x17': 0.955301, 'x18': 0.487778, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:21] ax.service.ax_client: Completed trial 7 with data: {'y1': (0.388483, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:21] ax.service.ax_client: Generated new trial 8 with parameters {'x2': 0.864321, 'x3': 0.567183, 'x4': 0.006736, 'x5': 0.022394, 'x6': 0.513505, 'x7': 0.619423, 'x8': 0.952885, 'x9': 0.788713, 'x11': 0.504481, 'x12': 0.080127, 'x13': 0.541539, 'x14': 0.345815, 'x15': 0.407131, 'x16': 0.659154, 'x17': 0.012379, 'x18': 0.627092, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:22] ax.service.ax_client: Completed trial 8 with data: {'y1': (0.349233, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:22] ax.service.ax_client: Generated new trial 9 with parameters {'x2': 0.306666, 'x3': 0.943764, 'x4': 0.302342, 'x5': 0.342245, 'x6': 0.087297, 'x7': 0.384511, 'x8': 0.500693, 'x9': 0.181141, 'x11': 0.194391, 'x12': 0.925375, 'x13': 0.366228, 'x14': 0.645241, 'x15': 0.098832, 'x16': 0.838793, 'x17': 0.691462, 'x18': 0.848751, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:23] ax.service.ax_client: Completed trial 9 with data: {'y1': (0.461171, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:23] ax.service.ax_client: Generated new trial 10 with parameters {'x2': 0.447194, 'x3': 0.016663, 'x4': 0.227318, 'x5': 0.480221, 'x6': 0.211421, 'x7': 0.183129, 'x8': 0.064591, 'x9': 0.60256, 'x11': 0.951094, 'x12': 0.196171, 'x13': 0.775602, 'x14': 0.554465, 'x15': 0.585713, 'x16': 0.612652, 'x17': 0.530704, 'x18': 0.998375, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:24] ax.service.ax_client: Completed trial 10 with data: {'y1': (0.469797, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:24] ax.service.ax_client: Generated new trial 11 with parameters {'x2': 0.090179, 'x3': 0.630024, 'x4': 0.86277, 'x5': 0.641119, 'x6': 0.484222, 'x7': 0.367646, 'x8': 0.850156, 'x9': 0.890782, 'x11': 0.706232, 'x12': 0.489476, 'x13': 0.651339, 'x14': 0.788179, 'x15': 0.251252, 'x16': 0.181899, 'x17': 0.997078, 'x18': 0.226893, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:26] ax.service.ax_client: Completed trial 11 with data: {'y1': (0.682289, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:26] ax.service.ax_client: Generated new trial 12 with parameters {'x2': 0.99945, 'x3': 0.926943, 'x4': 0.761482, 'x5': 0.416446, 'x6': 0.306646, 'x7': 0.979619, 'x8': 0.723498, 'x9': 0.066145, 'x11': 0.100805, 'x12': 0.299176, 'x13': 0.026264, 'x14': 0.265231, 'x15': 0.558494, 'x16': 0.216291, 'x17': 0.685607, 'x18': 0.324326, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:27] ax.service.ax_client: Completed trial 12 with data: {'y1': (0.433874, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:27] ax.service.ax_client: Generated new trial 13 with parameters {'x2': 0.036879, 'x3': 0.15982, 'x4': 0.40919, 'x5': 0.900228, 'x6': 0.587007, 'x7': 0.46402, 'x8': 0.014661, 'x9': 0.535456, 'x11': 0.932023, 'x12': 0.982523, 'x13': 0.694973, 'x14': 0.978405, 'x15': 0.164773, 'x16': 0.980922, 'x17': 0.395376, 'x18': 0.93471, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:28] ax.service.ax_client: Completed trial 13 with data: {'y1': (0.549803, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:28] ax.service.ax_client: Generated new trial 14 with parameters {'x2': 0.60433, 'x3': 0.282248, 'x4': 0.141106, 'x5': 0.704401, 'x6': 0.013338, 'x7': 0.539914, 'x8': 0.437957, 'x9': 0.43222, 'x11': 0.369128, 'x12': 0.015149, 'x13': 0.400555, 'x14': 0.030539, 'x15': 0.356845, 'x16': 0.519911, 'x17': 0.840327, 'x18': 0.588009, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:29] ax.service.ax_client: Completed trial 14 with data: {'y1': (0.496416, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:29] ax.service.ax_client: Generated new trial 15 with parameters {'x2': 0.649654, 'x3': 0.740709, 'x4': 0.325321, 'x5': 0.598163, 'x6': 0.137401, 'x7': 0.776261, 'x8': 0.877832, 'x9': 0.854429, 'x11': 0.612402, 'x12': 0.864224, 'x13': 0.991306, 'x14': 0.183816, 'x15': 0.84336, 'x16': 0.810383, 'x17': 0.881838, 'x18': 0.688804, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:31] ax.service.ax_client: Completed trial 15 with data: {'y1': (0.39815, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:31] ax.service.ax_client: Generated new trial 16 with parameters {'x2': 0.762223, 'x3': 0.095983, 'x4': 0.70959, 'x5': 0.280985, 'x6': 0.432723, 'x7': 0.712014, 'x8': 0.162403, 'x9': 0.644301, 'x11': 0.857287, 'x12': 0.57147, 'x13': 0.617031, 'x14': 0.41885, 'x15': 0.008869, 'x16': 0.48906, 'x17': 0.599066, 'x18': 0.460292, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:32] ax.service.ax_client: Completed trial 16 with data: {'y1': (0.429454, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:32] ax.service.ax_client: Generated new trial 17 with parameters {'x2': 0.195591, 'x3': 0.442919, 'x4': 0.275241, 'x5': 0.634683, 'x6': 0.239797, 'x7': 0.010522, 'x8': 0.245864, 'x9': 0.091299, 'x11': 0.518897, 'x12': 0.505741, 'x13': 0.419836, 'x14': 0.306386, 'x15': 0.050724, 'x16': 0.022282, 'x17': 0.191571, 'x18': 0.037715, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:33] ax.service.ax_client: Completed trial 17 with data: {'y1': (0.483677, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:33] ax.service.ax_client: Generated new trial 18 with parameters {'x2': 0.420019, 'x3': 0.131593, 'x4': 0.842988, 'x5': 0.319452, 'x6': 0.315669, 'x7': 0.24513, 'x8': 0.40427, 'x9': 0.863439, 'x11': 0.007301, 'x12': 0.065724, 'x13': 0.562581, 'x14': 0.134887, 'x15': 0.335499, 'x16': 0.990717, 'x17': 0.497209, 'x18': 0.917814, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:34] ax.service.ax_client: Completed trial 18 with data: {'y1': (0.513377, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:34] ax.service.ax_client: Generated new trial 19 with parameters {'x2': 0.05824, 'x3': 0.518514, 'x4': 0.191923, 'x5': 0.558716, 'x6': 0.113859, 'x7': 0.305654, 'x8': 0.680978, 'x9': 0.637714, 'x11': 0.275132, 'x12': 0.373617, 'x13': 0.938334, 'x14': 0.401134, 'x15': 0.500977, 'x16': 0.311914, 'x17': 0.0306, 'x18': 0.18538, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:36] ax.service.ax_client: Completed trial 19 with data: {'y1': (0.707194, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:36] ax.service.ax_client: Generated new trial 20 with parameters {'x2': 0.969786, 'x3': 0.25428, 'x4': 0.605731, 'x5': 0.015158, 'x6': 0.773005, 'x7': 0.758745, 'x8': 0.080618, 'x9': 0.229431, 'x11': 0.692266, 'x12': 0.909015, 'x13': 0.278902, 'x14': 0.871799, 'x15': 0.142944, 'x16': 0.514084, 'x17': 0.802276, 'x18': 0.575123, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:37] ax.service.ax_client: Completed trial 20 with data: {'y1': (0.39849, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:37] ax.service.ax_client: Generated new trial 21 with parameters {'x2': 0.899029, 'x3': 0.784061, 'x4': 0.183837, 'x5': 0.256659, 'x6': 0.157475, 'x7': 0.917618, 'x8': 0.807623, 'x9': 0.342375, 'x11': 0.919598, 'x12': 0.431607, 'x13': 0.313258, 'x14': 0.924082, 'x15': 0.30828, 'x16': 0.3363, 'x17': 0.340192, 'x18': 0.275019, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:38] ax.service.ax_client: Completed trial 21 with data: {'y1': (0.338994, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:38] ax.service.ax_client: Generated new trial 22 with parameters {'x2': 0.460499, 'x3': 0.656504, 'x4': 0.389905, 'x5': 0.076455, 'x6': 0.740178, 'x7': 0.086255, 'x8': 0.738728, 'x9': 0.687801, 'x11': 0.357619, 'x12': 0.586361, 'x13': 0.528607, 'x14': 0.067283, 'x15': 0.248532, 'x16': 0.156539, 'x17': 0.895481, 'x18': 0.248677, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:39] ax.service.ax_client: Completed trial 22 with data: {'y1': (0.395781, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:39] ax.service.ax_client: Generated new trial 23 with parameters {'x2': 0.748819, 'x3': 0.595383, 'x4': 0.744992, 'x5': 0.695456, 'x6': 0.273386, 'x7': 0.838262, 'x8': 0.591047, 'x9': 0.616957, 'x11': 0.431195, 'x12': 0.999371, 'x13': 0.66917, 'x14': 0.501832, 'x15': 0.093574, 'x16': 0.680608, 'x17': 0.098954, 'x18': 0.645353, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:41] ax.service.ax_client: Completed trial 23 with data: {'y1': (0.435176, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:41] ax.service.ax_client: Generated new trial 24 with parameters {'x2': 0.854922, 'x3': 0.239842, 'x4': 0.345095, 'x5': 0.424911, 'x6': 0.0316, 'x7': 0.650021, 'x8': 0.368714, 'x9': 0.889587, 'x11': 0.163387, 'x12': 0.689954, 'x13': 0.79488, 'x14': 0.766836, 'x15': 0.759144, 'x16': 0.111243, 'x17': 0.381977, 'x18': 0.377763, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:42] ax.service.ax_client: Completed trial 24 with data: {'y1': (0.410731, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:42] ax.service.ax_client: Generated new trial 25 with parameters {'x2': 0.825378, 'x3': 0.955038, 'x4': 0.546215, 'x5': 0.514776, 'x6': 0.650942, 'x7': 0.323369, 'x8': 0.207512, 'x9': 0.462804, 'x11': 0.076477, 'x12': 0.121174, 'x13': 0.762665, 'x14': 0.576347, 'x15': 0.176601, 'x16': 0.242679, 'x17': 0.587595, 'x18': 0.737836, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:43] ax.service.ax_client: Completed trial 25 with data: {'y1': (0.336294, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:43] ax.service.ax_client: Generated new trial 26 with parameters {'x2': 0.252174, 'x3': 0.581387, 'x4': 0.777525, 'x5': 0.820047, 'x6': 0.201296, 'x7': 0.680504, 'x8': 0.276408, 'x9': 0.56952, 'x11': 0.638517, 'x12': 0.903858, 'x13': 0.079551, 'x14': 0.430212, 'x15': 0.360367, 'x16': 0.250572, 'x17': 0.141669, 'x18': 0.770205, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:44] ax.service.ax_client: Completed trial 26 with data: {'y1': (0.385696, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:44] ax.service.ax_client: Generated new trial 27 with parameters {'x2': 0.486154, 'x3': 0.379085, 'x4': 0.688906, 'x5': 0.986759, 'x6': 0.07737, 'x7': 0.88567, 'x8': 0.837506, 'x9': 0.147737, 'x11': 0.382029, 'x12': 0.225558, 'x13': 0.558861, 'x14': 0.277308, 'x15': 0.816365, 'x16': 0.040171, 'x17': 0.072691, 'x18': 0.890603, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:46] ax.service.ax_client: Completed trial 27 with data: {'y1': (0.359319, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:46] ax.service.ax_client: Generated new trial 28 with parameters {'x2': 0.098055, 'x3': 0.765732, 'x4': 0.338682, 'x5': 0.134089, 'x6': 0.367749, 'x7': 0.571363, 'x8': 0.122255, 'x9': 0.357804, 'x11': 0.150357, 'x12': 0.463993, 'x13': 0.934119, 'x14': 0.01091, 'x15': 0.020966, 'x16': 0.718972, 'x17': 0.414179, 'x18': 0.150366, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:47] ax.service.ax_client: Completed trial 28 with data: {'y1': (0.480916, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:47] ax.service.ax_client: Generated new trial 29 with parameters {'x2': 0.580972, 'x3': 0.176008, 'x4': 0.681429, 'x5': 0.195806, 'x6': 0.151294, 'x7': 0.275101, 'x8': 0.714633, 'x9': 0.817242, 'x11': 0.799948, 'x12': 0.032818, 'x13': 0.183938, 'x14': 0.800259, 'x15': 0.118503, 'x16': 0.076271, 'x17': 0.259162, 'x18': 0.542666, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:48] ax.service.ax_client: Completed trial 29 with data: {'y1': (0.422606, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:48] ax.service.ax_client: Generated new trial 30 with parameters {'x2': 0.657232, 'x3': 0.846934, 'x4': 0.848235, 'x5': 0.122357, 'x6': 0.027306, 'x7': 0.042538, 'x8': 0.149755, 'x9': 0.395152, 'x11': 0.056398, 'x12': 0.838801, 'x13': 0.704505, 'x14': 0.89066, 'x15': 0.57389, 'x16': 0.351248, 'x17': 0.4552, 'x18': 0.67283, 'c1': 'c1_0', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:50] ax.service.ax_client: Completed trial 30 with data: {'y1': (0.585209, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:50] ax.service.ax_client: Generated new trial 31 with parameters {'x2': 0.801496, 'x3': 0.491668, 'x4': 0.249178, 'x5': 0.756307, 'x6': 0.293332, 'x7': 0.476995, 'x8': 0.935494, 'x9': 0.10699, 'x11': 0.288107, 'x12': 0.600795, 'x13': 0.829736, 'x14': 0.625811, 'x15': 0.278461, 'x16': 0.920615, 'x17': 0.047298, 'x18': 0.413061, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:51] ax.service.ax_client: Completed trial 31 with data: {'y1': (0.468974, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:51] ax.service.ax_client: Generated new trial 32 with parameters {'x2': 0.812223, 'x3': 0.525109, 'x4': 0.611806, 'x5': 0.387281, 'x6': 0.246615, 'x7': 0.099683, 'x8': 0.85199, 'x9': 0.040201, 'x11': 0.218275, 'x12': 0.137096, 'x13': 0.478657, 'x14': 0.017193, 'x15': 0.72224, 'x16': 0.586866, 'x17': 0.812885, 'x18': 0.08712, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:52] ax.service.ax_client: Completed trial 32 with data: {'y1': (0.564406, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:52] ax.service.ax_client: Generated new trial 33 with parameters {'x2': 0.666068, 'x3': 0.138196, 'x4': 0.478282, 'x5': 0.741871, 'x6': 0.448371, 'x7': 0.412037, 'x8': 0.075055, 'x9': 0.453148, 'x11': 0.438746, 'x12': 0.423564, 'x13': 0.104412, 'x14': 0.25125, 'x15': 0.42688, 'x16': 0.142501, 'x17': 0.658287, 'x18': 0.827351, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:53] ax.service.ax_client: Completed trial 33 with data: {'y1': (0.35844, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:54] ax.service.ax_client: Generated new trial 34 with parameters {'x2': 0.378215, 'x3': 0.074637, 'x4': 0.652704, 'x5': 0.111095, 'x6': 0.540169, 'x7': 0.663938, 'x8': 0.224202, 'x9': 0.351117, 'x11': 0.272454, 'x12': 0.022031, 'x13': 0.213482, 'x14': 0.816659, 'x15': 0.270207, 'x16': 0.634099, 'x17': 0.331761, 'x18': 0.286405, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_0'} using model Sobol.\n",
- "[INFO 09-08 21:57:55] ax.service.ax_client: Completed trial 34 with data: {'y1': (0.412712, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:55] ax.service.ax_client: Generated new trial 35 with parameters {'x2': 0.949573, 'x3': 0.451965, 'x4': 0.921028, 'x5': 0.306004, 'x6': 0.122628, 'x7': 0.332185, 'x8': 0.291876, 'x9': 0.743477, 'x11': 0.958399, 'x12': 0.991297, 'x13': 0.881923, 'x14': 0.174702, 'x15': 0.204483, 'x16': 0.860611, 'x17': 0.901469, 'x18': 0.18993, 'c1': 'c1_1', 'c2': 'c2_1', 'c3': 'c3_2'} using model Sobol.\n",
- "[INFO 09-08 21:57:56] ax.service.ax_client: Completed trial 35 with data: {'y1': (0.520359, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:56] ax.service.ax_client: Generated new trial 36 with parameters {'x2': 0.494989, 'x3': 0.604429, 'x4': 0.074364, 'x5': 0.367763, 'x6': 0.406179, 'x7': 0.504452, 'x8': 0.886815, 'x9': 0.206958, 'x11': 0.124712, 'x12': 0.513354, 'x13': 0.132589, 'x14': 0.885468, 'x15': 0.184827, 'x16': 0.468156, 'x17': 0.807028, 'x18': 0.609578, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:57] ax.service.ax_client: Completed trial 36 with data: {'y1': (0.366265, None)}.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\modelbridge\\cross_validation.py:462: UserWarning:\n",
- "\n",
- "Encountered exception in computing model fit quality: RandomModelBridge does not support prediction.\n",
- "\n",
- "[INFO 09-08 21:57:57] ax.service.ax_client: Generated new trial 37 with parameters {'x2': 0.706639, 'x3': 0.667, 'x4': 0.806372, 'x5': 0.998997, 'x6': 0.622979, 'x7': 0.256582, 'x8': 0.786466, 'x9': 0.098029, 'x11': 0.164112, 'x12': 0.916601, 'x13': 0.0544, 'x14': 0.452873, 'x15': 0.028252, 'x16': 0.945185, 'x17': 0.199011, 'x18': 0.025663, 'c1': 'c1_0', 'c2': 'c2_1', 'c3': 'c3_1'} using model Sobol.\n",
- "[INFO 09-08 21:57:59] ax.service.ax_client: Completed trial 37 with data: {'y1': (0.428466, None)}.\n",
- "[INFO 09-08 21:58:07] ax.service.ax_client: Generated new trial 38 with parameters {'x2': 0.80359, 'x3': 0.893032, 'x4': 0.453044, 'x5': 0.488367, 'x6': 0.635252, 'x7': 0.389619, 'x8': 0.342169, 'x9': 0.444101, 'x11': 0.133638, 'x12': 0.157374, 'x13': 0.66549, 'x14': 0.602432, 'x15': 0.174091, 'x16': 0.285392, 'x17': 0.592101, 'x18': 0.707177, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:58:08] ax.service.ax_client: Completed trial 38 with data: {'y1': (0.3171, None)}.\n",
- "[INFO 09-08 21:58:18] ax.service.ax_client: Generated new trial 39 with parameters {'x2': 0.850296, 'x3': 0.899253, 'x4': 0.464231, 'x5': 0.440373, 'x6': 0.631989, 'x7': 0.390095, 'x8': 0.325388, 'x9': 0.520113, 'x11': 0.1741, 'x12': 0.1086, 'x13': 0.7339, 'x14': 0.5375, 'x15': 0.211957, 'x16': 0.302266, 'x17': 0.485878, 'x18': 0.710654, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:58:19] ax.service.ax_client: Completed trial 39 with data: {'y1': (0.316725, None)}.\n",
- "[INFO 09-08 21:58:29] ax.service.ax_client: Generated new trial 40 with parameters {'x2': 0.843618, 'x3': 0.884832, 'x4': 0.51381, 'x5': 0.503263, 'x6': 0.590168, 'x7': 0.392564, 'x8': 0.302766, 'x9': 0.476761, 'x11': 0.207405, 'x12': 0.173646, 'x13': 0.712359, 'x14': 0.547096, 'x15': 0.216394, 'x16': 0.286118, 'x17': 0.56167, 'x18': 0.683743, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:58:30] ax.service.ax_client: Completed trial 40 with data: {'y1': (0.312587, None)}.\n",
- "[INFO 09-08 21:58:40] ax.service.ax_client: Generated new trial 41 with parameters {'x2': 0.837354, 'x3': 0.742273, 'x4': 0.180884, 'x5': 0.269844, 'x6': 0.272524, 'x7': 0.786995, 'x8': 0.790587, 'x9': 0.38279, 'x11': 0.707471, 'x12': 0.387223, 'x13': 0.346566, 'x14': 0.823961, 'x15': 0.291912, 'x16': 0.385605, 'x17': 0.392457, 'x18': 0.39421, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:58:42] ax.service.ax_client: Completed trial 41 with data: {'y1': (0.335276, None)}.\n",
- "[INFO 09-08 21:58:51] ax.service.ax_client: Generated new trial 42 with parameters {'x2': 0.848515, 'x3': 0.958173, 'x4': 0.461311, 'x5': 0.431157, 'x6': 0.555211, 'x7': 0.445524, 'x8': 0.304871, 'x9': 0.447979, 'x11': 0.233544, 'x12': 0.14291, 'x13': 0.695442, 'x14': 0.666237, 'x15': 0.196003, 'x16': 0.247029, 'x17': 0.496912, 'x18': 0.647151, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:58:52] ax.service.ax_client: Completed trial 42 with data: {'y1': (0.334126, None)}.\n",
- "[INFO 09-08 21:59:02] ax.service.ax_client: Generated new trial 43 with parameters {'x2': 0.810156, 'x3': 0.872712, 'x4': 0.4814, 'x5': 0.454094, 'x6': 0.584415, 'x7': 0.367132, 'x8': 0.345642, 'x9': 0.479644, 'x11': 0.153057, 'x12': 0.184237, 'x13': 0.699306, 'x14': 0.557176, 'x15': 0.231579, 'x16': 0.317068, 'x17': 0.540127, 'x18': 0.705382, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:59:03] ax.service.ax_client: Completed trial 43 with data: {'y1': (0.313417, None)}.\n",
- "[INFO 09-08 21:59:13] ax.service.ax_client: Generated new trial 44 with parameters {'x2': 0.837697, 'x3': 0.855831, 'x4': 0.480948, 'x5': 0.471471, 'x6': 0.632882, 'x7': 0.395634, 'x8': 0.33177, 'x9': 0.48924, 'x11': 0.19645, 'x12': 0.168142, 'x13': 0.68773, 'x14': 0.552156, 'x15': 0.199892, 'x16': 0.305126, 'x17': 0.551386, 'x18': 0.700636, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:59:14] ax.service.ax_client: Completed trial 44 with data: {'y1': (0.324149, None)}.\n",
- "[INFO 09-08 21:59:23] ax.service.ax_client: Generated new trial 45 with parameters {'x2': 0.806315, 'x3': 0.964937, 'x4': 0.446613, 'x5': 0.555578, 'x6': 0.527826, 'x7': 0.389686, 'x8': 0.38887, 'x9': 0.459525, 'x11': 0.123221, 'x12': 0.101269, 'x13': 0.741662, 'x14': 0.505462, 'x15': 0.249954, 'x16': 0.292191, 'x17': 0.558176, 'x18': 0.683448, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:59:24] ax.service.ax_client: Completed trial 45 with data: {'y1': (0.335153, None)}.\n",
- "[INFO 09-08 21:59:33] ax.service.ax_client: Generated new trial 46 with parameters {'x2': 0.800048, 'x3': 0.878963, 'x4': 0.476777, 'x5': 0.452134, 'x6': 0.535517, 'x7': 0.362354, 'x8': 0.259846, 'x9': 0.462283, 'x11': 0.133524, 'x12': 0.128384, 'x13': 0.70826, 'x14': 0.561574, 'x15': 0.217714, 'x16': 0.282658, 'x17': 0.535189, 'x18': 0.696148, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:59:34] ax.service.ax_client: Completed trial 46 with data: {'y1': (0.333704, None)}.\n",
- "[INFO 09-08 21:59:43] ax.service.ax_client: Generated new trial 47 with parameters {'x2': 0.847641, 'x3': 0.987593, 'x4': 0.53968, 'x5': 0.477867, 'x6': 0.65443, 'x7': 0.366106, 'x8': 0.399381, 'x9': 0.485741, 'x11': 0.161272, 'x12': 0.240526, 'x13': 0.755092, 'x14': 0.609302, 'x15': 0.242477, 'x16': 0.30585, 'x17': 0.538133, 'x18': 0.71203, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:59:44] ax.service.ax_client: Completed trial 47 with data: {'y1': (0.346441, None)}.\n",
- "[INFO 09-08 21:59:53] ax.service.ax_client: Generated new trial 48 with parameters {'x2': 0.890665, 'x3': 0.884293, 'x4': 0.49224, 'x5': 0.524948, 'x6': 0.590952, 'x7': 0.330496, 'x8': 0.38948, 'x9': 0.498876, 'x11': 0.137895, 'x12': 0.137659, 'x13': 0.613424, 'x14': 0.559272, 'x15': 0.22976, 'x16': 0.215897, 'x17': 0.500569, 'x18': 0.694188, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 21:59:55] ax.service.ax_client: Completed trial 48 with data: {'y1': (0.337432, None)}.\n",
- "[INFO 09-08 22:00:03] ax.service.ax_client: Generated new trial 49 with parameters {'x2': 0.773348, 'x3': 0.780489, 'x4': 0.281413, 'x5': 0.366409, 'x6': 0.472132, 'x7': 0.550351, 'x8': 0.61636, 'x9': 0.45358, 'x11': 0.348144, 'x12': 0.25633, 'x13': 0.544703, 'x14': 0.614696, 'x15': 0.263848, 'x16': 0.416957, 'x17': 0.493496, 'x18': 0.598299, 'c1': 'c1_1', 'c2': 'c2_0', 'c3': 'c3_1'} using model BoTorch.\n",
- "[INFO 09-08 22:00:04] ax.service.ax_client: Completed trial 49 with data: {'y1': (0.333681, None)}.\n",
- "[WARNING 09-08 22:00:04] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n"
- ]
- }
- ],
- "source": [
- "random_seed_list = [17, 23, 42, 87, 115, 131, 463, 845, 1387, 1685]\n",
- "result_list = []\n",
- "for exp_i in range(len(random_seed_list)): \n",
- "\n",
- " ax_client = AxClient(random_seed=random_seed_list[exp_i])\n",
- " ax_client.create_experiment(\n",
- " parameters=[\n",
- " # {\"name\": \"x1\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x2\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x3\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x4\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x5\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x6\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x7\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x8\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x9\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " # {\"name\": \"x10\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x11\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x12\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x13\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x14\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x15\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x16\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x17\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x18\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " # {\"name\": \"x19\", \"type\": \"range\", \"bounds\": [0.0, 1.0]}, \n",
- " # {\"name\": \"x20\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"c1\", \"type\": \"choice\", \"is_ordered\": False, \"values\": [\"c1_0\", \"c1_1\"]},\n",
- " {\"name\": \"c2\", \"type\": \"choice\", \"is_ordered\": False, \"values\": [\"c2_0\", \"c2_1\"]},\n",
- " {\"name\": \"c3\", \"type\": \"choice\", \"is_ordered\": False, \"values\": [\"c3_0\", \"c3_1\", \"c3_2\"]},\n",
- " ],\n",
- " parameter_constraints=[\n",
- " # \"x19 <= x20\",\n",
- " \"x6 + x15 <= 1.0\",\n",
- " ],\n",
- " objectives={\n",
- " \"y1\": ObjectiveProperties(minimize=True),\n",
- " },\n",
- " overwrite_existing_experiment=True,\n",
- " is_test=True,\n",
- " )\n",
- " for _ in range(round): \n",
- " parameterization, trial_index = ax_client.get_next_trial()\n",
- "\n",
- " #x1 = parameterization[\"x1\"]\n",
- " x2 = parameterization[\"x2\"]\n",
- " x3 = parameterization[\"x3\"]\n",
- " x4 = parameterization[\"x4\"]\n",
- " x5 = parameterization[\"x5\"]\n",
- " x6 = parameterization[\"x6\"]\n",
- " x7 = parameterization[\"x7\"]\n",
- " x8 = parameterization[\"x8\"]\n",
- " x9 = parameterization[\"x9\"]\n",
- " #x10 = parameterization[\"x10\"]\n",
- " x11 = parameterization[\"x11\"]\n",
- " x12 = parameterization[\"x12\"]\n",
- " x13 = parameterization[\"x13\"]\n",
- " x14 = parameterization[\"x14\"]\n",
- " x15 = parameterization[\"x15\"]\n",
- " x16 = parameterization[\"x16\"]\n",
- " x17 = parameterization[\"x17\"]\n",
- " x18 = parameterization[\"x18\"]\n",
- " #x19 = parameterization[\"x19\"]\n",
- " #x20 = parameterization[\"x20\"]\n",
- " c1 = parameterization[\"c1\"]\n",
- " c2 = parameterization[\"c2\"]\n",
- " c3 = parameterization[\"c3\"]\n",
- "\n",
- " #results = adv_opt(x1, x2, x3, x4, x5, x6, x7, x8, x9, x10, x11, x12, x13, x14, x15, x16, x17, x18, x19, x20, c1, c2, c3)\n",
- " results = adv_opt(c1, c2, c3, x2, x3, x4, x5, x6, x7, x8, x9, x11, x12, x13, x14, x15, x16, x17, x18)\n",
- " ax_client.complete_trial(trial_index=trial_index, raw_data=results) \n",
- "\n",
- " df = ax_client.get_trials_data_frame()\n",
- " result_list.append(df['y1'].values) "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "10"
- ]
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "len(result_list)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [],
- "source": [
- "dff = pd.DataFrame(result_list)\n",
- "np.savetxt('AdvOpt-Ax.csv', dff)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 13,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- ""
- ]
- },
- "execution_count": 13,
- "metadata": {},
- "output_type": "execute_result"
- },
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "import matplotlib.pyplot as plt\n",
- "ax_data = np.loadtxt('AdvOpt-Ax.csv')\n",
- "data = [ax_data] \n",
- "means = {}\n",
- "stds = {}\n",
- "for m, d in enumerate(data):\n",
- " x = d.copy()\n",
- " best_obj = np.array([np.minimum.accumulate(obj_i) for obj_i in x])\n",
- " means[m] = best_obj.mean(axis=0)\n",
- " stds[m] = best_obj.std(axis=0) / np.sqrt(best_obj.shape[0])\n",
- "\n",
- "fig = plt.figure(figsize=(10, 6))\n",
- "ax = fig.add_subplot(111)\n",
- "x = np.arange(1, len(means[0]) + 1)\n",
- "colors = ['steelblue']\n",
- "methods = ['Ax']\n",
- "for i, algo in enumerate(methods):\n",
- " ax.plot(x, means[i], label=algo, c=colors[i])\n",
- " ax.fill_between(x, means[i] - 2 * stds[i], means[i] + 2 * stds[i], color=colors[i], alpha=0.3)\n",
- "ax.axhline(y = 0.2, c = 'r', ls = '--', label = \"Good threshold\")\n",
- "ax.set_xlabel('# of iteration')\n",
- "ax.set_ylabel('Best observed value')\n",
- "ax.set_title('AC Hugging Face Advanced Optimization, Ax, 10 repeats')\n",
- "ax.set_ylim(0.18, 0.67)\n",
- "ax.legend()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "(49,\n",
- " {'x2': 0.843617661699682,\n",
- " 'x3': 0.8848322551603883,\n",
- " 'x4': 0.5138101708090401,\n",
- " 'x5': 0.5032631800217858,\n",
- " 'x6': 0.5901684134654586,\n",
- " 'x7': 0.39256395948698575,\n",
- " 'x8': 0.3027655919073459,\n",
- " 'x9': 0.47676099240883674,\n",
- " 'x11': 0.2074045945980981,\n",
- " 'x12': 0.1736463100279958,\n",
- " 'x13': 0.7123592839535469,\n",
- " 'x14': 0.5470960398716934,\n",
- " 'x15': 0.2163937319784434,\n",
- " 'x16': 0.2861183216520867,\n",
- " 'x17': 0.5616695495431285,\n",
- " 'x18': 0.6837430074838851,\n",
- " 'c1': 'c1_1',\n",
- " 'c2': 'c2_0',\n",
- " 'c3': 'c3_1'},\n",
- " ({'y1': 0.31660899247362645}, {'y1': {'y1': 5.403464758733553e-05}}))"
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "best_paramters, metrics = ax_client.get_best_parameters()\n",
- "ax_client.get_best_trial()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "[WARNING 09-08 22:00:07] ax.service.utils.report_utils: Column reason missing for all trials. Not appending column.\n"
- ]
- }
- ],
- "source": [
- "df = ax_client.get_trials_data_frame()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoQAAAHYCAYAAADUE/leAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/TGe4hAAAACXBIWXMAABJ0AAASdAHeZh94AACsYUlEQVR4nOzdeViUVfsH8O8MDJuIiAgM6qCA+567KIpLqbSguKWGFmRJZfpmgYWo4Ea+WbaQC74qSmWKWqaVS+CCiW1WmKaggCm47yKMcH5/8JvJcYZlmBlmgO/nuryK85znPPes3JznLBIhhAARERER1VlScwdARERERObFhJCIiIiojmNCSERERFTHMSEkIiIiquOYEBIRERHVcUwIiYiIiOo4JoREREREdRwTQiIiIqI6jgkhERERUR3HhJCIiIiojmNCSERERFTHMSEkqsGmTJkCiUSC7Oxsc4disebNmweJRILU1FRzh1IlqampkEgkmDdvnsmukZ2dDYlEgilTppjsGvpq3rw5mjdvbu4wiOoMJoREZrJw4UJIJBJIJBL8/fff5g6HHnHv3j28//778Pf3h6urK2xsbCCXy/HUU09h8+bNEEIY5TqWmIxVh4EDB0IikZg7DKO7d+8enJ2dIZFIMGHCBHOHQ1Rp1uYOgKguEkIgISEBEokEQgisXr0a//3vf80dFv2/48eP46mnnsLZs2fh5eWF4OBgNGrUCLm5udi5cye++eYbDB06FF9++SWcnZ1NGkvPnj1x4sQJuLq6muwaTZo0wYkTJ9CgQQOTXUNf+/btM3cIVbJp0ybcvHkTEokEW7duxdWrV9GoUSNzh0VUIfYQEpnB7t27kZ2djcmTJ8PDwwPr169HUVGRucMiAPn5+Rg6dCjOnj2L2bNnIzMzEytXrsSiRYuwceNGZGVl4YknnsCePXswduxYlJSUmDQeBwcHtGnTxqQJoUwmQ5s2bSCXy012DX35+PjAx8fH3GHobdWqVZBKpXjzzTdRWFiI9evXmzskokphQkhkBqtXrwYAvPjii5g4cSKuXLmCbdu2lVl/79696N+/P+rVqwcXFxcEBQXh5MmTWvWOHDkCiUSCkSNHltlW27ZtYWtri2vXrgEAioqK8PHHH2PEiBHw8vKCra0tXFxcMGTIEHz77bc621CN77p79y7efPNNKBQK2NrawtfXF3FxcWXeTj169CjGjRuHJk2awNbWFnK5HI8//ji+/PJLrbrp6ekYPXo0PDw8YGNjg2bNmuGll17ChQsXdLb9yy+/YNiwYahfvz6cnJwwZMgQ/Pjjj2U+D2WJiopCXl4exo8fj0WLFsHaWvNGiouLC5KTk+Ht7Y09e/bg888/1/nc3Lx5E6+++iqaNGkCOzs7tGvXDh9++KHGczNv3jy0aNECALB+/Xr1EAKJRIJ169YBKHsMoeqWq1KpRExMDHx8fGBnZ4fWrVur318AsGLFCnTs2BH29vZo2rQp5s6dq5XE6rptvW7dOo14dP17eOzqunXrEBwcDG9vb9jb28PJyQl+fn7YuHGjzmvt378fADTaGzhwoNbz+KjCwkIsWbIEHTt2hIODA5ycnNC/f3+d76GHH1d2djbGjx8PV1dX2NnZoXv37vjmm2+0zjFERkYGjhw5gsGDByMiIgI2NjZISEjQWff111+HRCLBf/7zH61ja9asgUQiwdChQ03+BweRmiCiapWfny9kMplo1aqVEEKIP//8UwAQgwYN0ll/8+bNQiqVCjs7OzF58mQRGRkp+vXrJ5ydnYW/v78AIM6ePauu37p1a2FjYyOuXLmi1VZ6eroAIIKDg9VleXl5QiqVin79+onQ0FARGRkpJk+eLFxcXAQAsXr1aq12vLy8hKenp/Dz8xMtWrQQU6dOFeHh4cLT01MAEPPmzdM6Z9WqVcLKykrY2NiI0aNHi9mzZ4vQ0FDRuXNnMWDAAI26a9asEVZWVsLBwUGMHz9evPnmmyIoKEhIpVIhl8tFTk6ORv20tDRhb28vrKysxJgxY8Ts2bPF8OHDhY2NjRg2bJgAIFJSUsp6SdTu3bsnbG1tBQDx119/lVv3k08+EQCEv7+/1nMjl8tF9+7dha+vr/jPf/4jXn31VSGXywUAER4erq6bkpIiXn/9dQFAdO7cWcydO1f977ffflPXASDmzp2rcZ0BAwYIAGLUqFGiSZMm4sUXXxTh4eHCzc1NABBr164VM2fOFC4uLiIkJES8/vrrokWLFgKAWLJkiUZbZ8+eFQDE5MmT1WW//fabRjyqfzNmzBASiURIpVKRl5enrm9nZye6deumfo+++OKLokmTJgKAiIqKUte7fv26mDt3rvDy8lI/LtW/tWvXajyPXl5eGnEWFhaqH3ebNm3ErFmzNB7z7NmzdT6ugQMHisaNG4tevXqJGTNmiJCQEGFrayukUqn44Ycfyn2d9fHaa68JACIpKUkIIURwcLAAIA4cOKBVt7CwUDz22GNCIpGIb775Rl2ekZEhHBwchIeHh8jPzzdabEQVYUJIVM0WL14sAIhFixapy7p16yYkEok4ffq0Rt3bt28LFxcXYW1tLX766SeNYzNmzBAAtBLCRYsWCQDio48+0rp2eHi4ACC+/vprddn9+/fFuXPntOreuHFDtG/fXjRs2FDcu3dP45jql/nw4cM1jl28eFE0aNBANGjQQBQVFanLjx8/LqytrUXDhg1FRkaG1rUevv7ff/8tZDKZ8PHxEf/8849Gvb179wqpVCqCgoLUZSUlJaJ169YCgNi+fbtG/Q8++ED9HFUmITxw4IAAIDw9PSuse+rUKQFA2NjYiAcPHqjLVc+Nn5+fuH//vrr86tWrwtvbWwAQ+/fvV5frSsYeVlFC2L17d3H9+nV1eVZWlpDJZMLZ2Vk0b95c4zm8fv26aNSokXB1dRVKpbLSMagUFRWJwYMHCwDigw8+0DiWmZmpVb+wsFAMGjRIWFtba72WqvjLoishVL23hw8frhH/xYsX1c97Wlqa1uPS9UfKd999p27LGAoKCkTDhg1FgwYN1J+JHTt2CABi0qRJOs85ffq0qF+/vnB1dRX//POPuHv3rmjfvr2QSqVi7969RomLqLKYEBJVo5KSEuHj4yOkUqnGL8iPPvpIABBvvfWWRv2NGzcKACIkJESrrRs3bogGDRpoJYTnzp0TUqlUdO/eXaN+YWGhcHFxEW5ubhq/TMvz3nvvaSUwQvyb9DyawAohREhIiAAg/vzzT3XZq6++KgCIZcuWVXhNVaL7cK/Jw4KCgoSVlZW4deuWEEKIQ4cO6eypE0KIBw8eCB8fn0onhJs2bRIARK9evSqsW1BQoE42Ll68qC5XPTe6eoXWrl0rAIgpU6aoywxNCHUlDgEBAQKAWLNmjdaxKVOmCAAiOzu70jGoPP/88wKAeO2118qt97Dk5GQBQKxfv15n/GXRlRD6+voKiUQiTpw4oVU/ISFBABDPP/+8ukz1uLy8vDSSdhWFQiEaNWpU6cdSnsTERAFATJ06VV2mVCqFh4eHsLOzE9euXdN53ueff65+/6qe33feeccoMRHpg2MIiarRDz/8gKysLAwdOhRNmjRRl0+YMAE2NjZYt24dlEqluvzXX38FAAwYMECrrQYNGqBLly5a5U2bNsXgwYPx888/46+//lKX79ixA9euXcPEiRO1xsUdP34cU6ZMUY//Uo3peuONNwAA58+f13l9X19frfJmzZoBAK5fv64uO3LkCABg+PDh2k/KI1Tj/vbv34958+Zp/bt06RKKi4tx6tQpAOU/R1ZWVujXr1+F1zQ2a2tr9O3bV6tcNUbut99+M9q1unfvrlXm6ekJAOjWrZvWMdX77p9//tHrOgsXLsTatWvx1FNP4YMPPtA6npubi1deeQVt2rSBg4OD+j0UHBwMQPd7SB+3b99GZmYmPD090aZNG63jgwYNAqD7ue3SpQusrKy0yps1a6bxPjXEqlWrAADPP/+8usza2hoTJ07E/fv3sWHDBp3njR8/HmFhYThw4ADWrl2Lfv36Yf78+UaJiUgfXHaGqBqpfmk8uuaci4sLnnrqKSQnJ+Orr77C6NGjAQA3b94EALi7u+tsz8PDQ2f5lClTsGfPHqxfvx5xcXEAoJ7tOHnyZI26R44cwaBBg/DgwQMMHjwYTz/9NJycnCCVSnHs2DF89dVXKCws1LpGWcutqJLN4uJiddmNGzcAQCMJLsvVq1cBAEuXLi233p07dwBU/Tkqr+65c+cqrKuqY2Njo7WsiKurq84ERNW+KmZj0LVUjOo1KO/Yw394VOTzzz/HnDlz0K1bN3z++eeQSjX7Es6cOYOePXvi+vXr6N+/Px5//HE0aNAAVlZWyM7Oxvr163W+h/Shes7KmgmtKle91x5W3nvVGJM2Tpw4gUOHDqFNmzbo3bu3xrEpU6bgvffew+rVqzF9+nSd548ePVo9+eS1117T+d4hMjUmhETV5PLly9i+fTsA4Nlnn8Wzzz6rs96qVavUCaHqF/rFixd11s3Pz9dZPnLkSDg5OWHjxo1YtGgRrl69im+//RadO3dG586dNeouWLAABQUFSElJ0ZjlCQCLFy/GV199VdmHWCbVL+Tz58/r7N15mOox37x5E05OThW2XdXnSJcePXrA1tYWFy5cwIkTJ9C2bdsy6+7duxcA0Lt3b61f4FeuXEFxcbFWuSoWS1rvryIHDx7E888/j2bNmmHHjh2oV6+eVp1ly5bh6tWrWLt2rdYfO59//rlRll5RPWdlvZ55eXka9aqT6g+9kydPlrnYdkZGBg4fPqzVc3zlyhWEhobCwcEBADBz5kwEBASgcePGpg2a6BFMCImqiWqtwW7duum81QsAX3/9Nfbu3YuzZ8+iRYsWeOyxxwCU3j594YUXNOrevHkTx44d09mOvb09xo4di4SEBOzduxcnTpzAgwcPtHoHASAzMxMuLi5ayaDqusbQu3dv/Pzzz/j2228rTAh79+6NX375BQcPHkRgYGCFbT/8HD2quLgYhw4dqnSc9vb2mDBhAtauXYsFCxYgKSlJZ72CggIsW7YMADB16lSt4w8ePMDhw4fRv39/jXLV9nldu3ZVl6mSxod7VC3FqVOnEBQUBFtbW+zcubPM3rnMzEwAUN8eflhZ76GHH3dlesTq168PHx8fnDlzBqdPn0bLli01jqekpAD49/1QXQoLC7FhwwZIpVL1VpKP+ueff/D9999j9erVGgmhEAKTJ0/G+fPnNZaiCgkJwa5du2rlTi5kwcw9iJGormjVqpUAINLT08usExUVJQCIt99+WwhROsu4YcOGes0yVlFNtpgwYYLo2rWrsLa21pj8oPLEE08IAOL333/XKFcN0sf/L2HyMF0D/lXmzp2rNYnj4VnGx48f1zrn4VnGJ06cEDKZTLRs2VL8/fffWnULCws1JmwYc5axEEKcP39euLu7q5dLeXQCzrVr18SIESMEADFkyBBRXFyscby8WcaqCS4PT9K5ffu2kEgkOifFCFHxpBJdJk+eXOb7Qtfro2tSyeXLl4WPj4+wtrYWu3fv1nkdlZdeeklr9roQpTN5raysdMY/ZswYAUCcOXNGZ5u63mMLFy4UAMQzzzyjMUnk8uXLonnz5gKAOHjwYLmP62FlPYeq11DX8/eopKSkCmcr37x5U9SrV084ODiIGzduqMv/+9//CgBi3Lhx6rJx48YJACIuLq7CaxMZE3sIiapBamoqTp06hY4dO6Jnz55l1gsNDVUP3p8/fz4cHR2xatUqjBs3Dv3798e4ceMgl8tx6NAhZGRkwN/fHwcOHNDZlp+fH3x9fbF582YolUo89dRTcHNz06o3Y8YMfP/99+jXrx/Gjh2LBg0a4Oeff8ahQ4cwevRobNmyxeDH365dO8THx+Pll19G165d8cwzz6Bly5a4evUqfvrpJzg5Oal7eNq0aYP//e9/eOGFF9C+fXsMGzYMrVq1glKpRG5uLg4ePIjGjRurF+aWSCRYs2YNhg4diuDgYIwaNQq+vr44duwY9u3bh2HDhuG7776rdKyenp7YvXs3nn76aSxYsAAbN27EsGHD4OLiot667vr16xgyZAg2b96sNZ4OKB3PVlhYiA4dOuDpp5+GUqnEli1bkJeXh/DwcPj7+6vrOjo6olevXjh48CAmTpyIVq1awcrKCk8//TQ6depk4DNfddHR0cjKysJjjz2GtLQ0pKWladWZMWMGnJ2dER4ejrVr12LMmDEYPXo0PD09kZGRge+++w5jx47Fpk2btM4dPHgwNm/ejFGjRmHEiBGwt7eHl5cXnnvuuTJjmjVrFr799lt89dVX6Ny5M0aMGIF79+5h8+bNuHTpEt566y2jTCJSjSt8dPKVLqrbxWFhYWXWcXJywpgxY7Bu3Tps3LgRr7zyCn766SfMnj0bLVq0wMqVKzXa++mnn/DOO+/A399fa0wikcmYOyMlqgsmTJggAIjly5dXWHfo0KECgNi6dau6bPfu3cLPz0/Y29sLZ2dn8fTTT4sTJ06U2xMkhBCxsbHqHrItW7aUec0dO3aIXr16CUdHR9GgQQMxdOhQsX//fvUyKYb2EKocPnxYjBo1SjRu3FjIZDIhl8vFE088ITZv3qxV948//hCTJ08WCoVC2NjYiIYNG4r27duLqVOnin379mnV//nnn8UTTzwhHB0dhaOjoxg8eLA4fPhwufGU586dO+K9994Tfn5+omHDhkImkwl3d3cRGBgoNm3aJEpKSnSep3pubty4oV6s28bGRrRp00YsX75c53mnT58WTz75pHBxcRESiUTjOTdXD6GqjfL+Pdx+WlqaCAgIEM7OzsLR0VH4+fmJbdu2lRn/gwcPxOzZs0WLFi2EtbW1AKCxQHlZ77GCggKxcOFC0b59e2FnZ6e+1meffaZVtyo9hNeuXRNSqVT4+fnpPOdhf//9twAg3N3dNdbd1CUtLU0ApQuQ37hxQ7Ro0ULIZDKddwx++uknYWNjI5o3b66xxiSRKUmEKGOPKSIi0ptqu7WHt3WjmuPrr7/GM888g507d2LEiBHmDoeo2nAdQiIiov+3f/9+dOnShckg1TnsISQiMiL2EBJRTcQeQiIiIqI6jj2ERERERHUcewiJiIiI6jgmhERERER1HBNCIiIiojqOO5VU0o0bN7B//340a9YMtra25g6HiIiIqEyFhYU4d+4cBgwYAGdn5wrrMyGspP379yMoKMjcYRARERFV2vbt2/HMM89UWI8JYSU1a9YMQOkT6+vra+ZoiIiIiMqWmZmJoKAgdf5SESaElaS6Tezr64v27dubORoiIiKiilV2mBsnlRARERHVcUwIiYiIiOo4JoREREREdRwTQiIiIqI6jpNKiIiIDCCEwN27d3Hr1i0UFhZCCGHukKiWkkgkcHR0RMOGDWFtbdwUjgkhERFRFQkhcOnSJVy7dg0AIJPJIJXy5huZhlKpxJUrV3Dv3j0oFApIJBKjtc2EkIiIqIru3r2La9euwcHBAXK5HDY2NuYOiWoxIQTy8vJw8+ZN3L59G05OTkZrm3/GEBERVdGtW7cAgMkgVQuJRAI3NzcA/773jIU9hFRpSqUSaWlpuHbtGlxcXODn5weZTGbusIiIzKawsBAymYzJIFUba2trWFtbQ6lUGrddo7ZGtZJSqcSSJUsQHx+P/Px8dblcLse0adMQGRnJxJCI6iQhBMcMUrWTSqVGn7zEhJDKpVQqERQUhF27dkGhUCAmJgY+Pj7IyspCQkICoqOjkZ6ejm3btjEpJCIiqgbGnEyiwoSQyrVkyRLs2rULISEhSEhI0Ej6IiMjERYWhsTERMTFxSEqKsqMkRIREVFVsZ+byqRUKhEfHw+FQqGVDAKlyyskJCRAoVAgPj7e6OMZiIiIqHowIaQypaWlIT8/H2FhYWXeDpbJZAgLC0NeXh7S0tKqOUIiIrI08+bNg0QiwZUrV8wdSrWTSCSYN2+eucOoEiaEVCbVQqs+Pj7l1vP29taoT0REhlMqlUhNTcXWrVuRmppq9rswx48fx6RJk9CkSRPY2trC09MTEydOxPHjx80aFxkHxxBSmVxcXAAAWVlZ5dY7c+aMRn0iIqo6S1zZYevWrXj22Wfh4uKC0NBQtGjRAtnZ2VizZg22bNmCL774AiNHjqzWmMi4mBBSmfz8/ODh4YGEhIQyv4CUSiUSEhIgl8vh5+dnhiiJiGoPS1zZISsrC8899xy8vb1x4MABNG7cWH3s9ddfR//+/fHcc8/hjz/+UN8xsgQlJSUoKiqCnZ2duUOpEXjLmMokk8kQHh6O3NxchIWFad2uUCqVCA0NRW5uLsLDw7nsDBGRgR5e2SEzMxNz5szBhAkTMGfOHGRmZiIkJAQ7d+5EXFxctcW0dOlS3Lt3D6tWrdJIBgHA1dUVK1euxN27d/Huu+9qHLty5QrGjh0LJycnNGrUCK+//jru37+vUWfPnj3o168fnJ2d4ejoiNatW+Ptt9/WqFNYWIi5c+fC19cXtra2aNasGd566y0UFhZq1JNIJHj11VeRlJSE9u3bw9bWFjt27ICLiwuef/55rcd169Yt2NnZYdasWXpfq7CwEDNnzkTjxo1Rv359PP300/jnn38q/6RaIPYQUrkiIyORnp6OxMREpKamIiwsDN7e3sjKysKaNWuQm5uLwMBAREREmDtUIqIarbIrO6SmpiI+Ph4RERHV8of4jh070Lx5c/Tv31/ncX9/fzRv3hw7d+7UKB87diyaN2+OxYsX48iRI/jwww9x/fp1JCYmAigdk/jkk0+iU6dOiImJga2tLTIzMzUmKJaUlODpp5/GoUOHMHXqVLRt2xZ//vkn3n//fZw6dQrbt2/XuOYPP/yAL7/8Eq+++ipcXV3RsmVLjBw5Elu3bsXKlSs1dpTZvn07CgsLMX78eL2vFRYWho0bN2LChAno27cvfvjhBwQGBhryNJufoErJyMgQAERGRoa5Q6l2RUVFIjY2VsjlcgFA/U8ul4vY2FhRVFRk7hCJiMwiKytLZGVlGaWtlJQUAUDExMSUWy8mJkYAECkpKUa5bnlu3LghAIhnnnmm3HpPP/20ACBu3bol5s6dKwCIp59+WqNOeHi4ACB+//13IYQQ77//vgAgLl++XGa7GzZsEFKpVBw8eFCjfMWKFQKASEtLU5cBEFKpVBw/flyj7vfffy8AiB07dmiUjxgxQnh7e+t9rWPHjgkAIjw8XKPehAkTBAAxd+7cMh+PsVTmfadv3sJbxlQhmUyGqKgo5OTkICUlBcnJyUhJSUFOTg6ioqJ4q5iIyAgscWWH27dvAwDq169fbj3V8Vu3bqnLXnnlFY06r732GgBg165dAABnZ2cAwFdffYWSkhKd7W7evBlt27ZFmzZtcOXKFfW/QYMGAQBSUlI06g8YMADt2rXTKBs0aBBcXV2xadMmddn169exZ88ejBs3Tu9rqeKfPn26xnVmzJih8zHUFLxlTJUmk8kwcOBAc4dBRFQrWeLKDqpET5UYlkVX4tiyZUuNOj4+PpBKpcjOzgYAjBs3DgkJCQgLC0NkZCQGDx6MUaNGYfTo0er9oU+fPo0TJ05ojV1UuXTpksbPLVq00KpjbW2N4OBgfPbZZygsLIStrS22bt0KpVKpkRBW9lo5OTmQSqVaiXvr1q11nldTMCEkIiKyAJa4skODBg0gl8vxxx9/lFvvjz/+QJMmTeDk5FRmnUf337W3t8eBAweQkpKCnTt34rvvvsOmTZswaNAg7N69G1ZWVigpKUHHjh2xbNkynW02a9ZMq01dxo8fj5UrV+Lbb79FUFAQvvzyS7Rp0wadO3dW19H3WrWNRd8yLiwsREREBDw9PWFvb49evXphz549lTr3iy++wGOPPQY7Ozs0btwYoaGhdXLVdCIiqhksdWWHJ598EmfPnsWhQ4d0Hj948CCys7Px5JNPapSfPn1a4+fMzEyUlJSgefPm6jKpVIrBgwdj2bJl+Ouvv7Bw4UL88MMP6tuzPj4+uHbtGgYPHowhQ4Zo/atsr5y/vz/kcjk2bdqEK1eu4IcfftDoHdTnWl5eXigpKdHqyf37778rFYulsuiEcMqUKVi2bBkmTpyI5cuXw8rKCiNGjCjzTany6aefqhfQXLZsGV588UV88cUXGDx4sNaUdyIiIksRGRmJwMBAJCYmwtfXF7GxsUhKSkJMTAx8fX2xYcOGal/Z4c0334S9vT1eeuklXL16VePYtWvX8PLLL8PBwQFvvvmmxrFPPvlE4+ePPvoIADB8+HD1uY/q0qULAKiXeRk7dizOnz+P1atXa9UtKCjA3bt3K/UYpFIpRo8ejR07dmDDhg148OCBVkJY2Wup4v/www816nzwwQeVisViGWO2iymkp6cLAGLp0qXqsoKCAuHj4yP69OlT5nmFhYXC2dlZ+Pv7i5KSEnX5jh07BADx4YcfVimeujzLmIiIdDPmLGMVS1zZ4csvvxQymUzI5XIRFRUl1qxZI+bMmSM8PT2FjY2NSE5OVtdVzTLu2LGjeOqpp8Qnn3wiJk2aJACICRMmqOu9/vrromvXriIqKkqsXr1aLFy4UDRp0kQ0bdpU3LhxQwghRHFxsRgxYoSQSCRi/Pjx4qOPPhIffPCBePnll4WLi4v46aef1O0BEK+88kqZj+HQoUMCgKhfv77o2LGj1nF9rvXss88KAGLixInik08+EaNGjRKdOnWq0bOMLTYhfPPNN4WVlZW4efOmRvmiRYsEAJGbm6vzvF9++UUAEJ988onWMUdHR9G3b98qxcOEkIiIHmWKhFClqKhIpKSkiOTkZJGSkmL2Jb7++OMP8eyzzwq5XC5kMpnw8PAQzz77rPjzzz816qkSwr/++kuMHj1a1K9fXzRs2FC8+uqroqCgQF1v37594plnnlEnlZ6enuLZZ58Vp06d0mivqKhIxMXFifbt2wtbW1vRsGFD0a1bNzF//nyNHKGihLCkpEQ0a9ZMABALFizQWaey1yooKBDTp08XjRo1EvXq1RNPPfWUOHfuXI1OCCVCCFGtXZKVNHToUJw/fx5//fWXRvm+ffswZMgQfP3113jqqae0zvvxxx/Rt29f/O9//9NamdzNzQ137tzBnTt31DOYdLl06RIuX76sUZaZmYmgoCBkZGSgffv2BjwyIiKqLVQzfi1pyzaq/Srzvjt+/Dg6dOhQ6bzFYmcZ5+XlQS6Xa5Wryi5cuKDzvJYtW0IikSAtLU0jIfz777/VSd7169fRqFGjMq8dHx+P+fPnGxI+ERERUY1hsQlhQUEBbG1ttcpVm1QXFBToPM/V1RVjx47F+vXr0bZtW4wcORLnz5/Ha6+9BplMBqVSWea5KuHh4RgzZoxGmaqHkIiIiKi2sdiE0N7eXmszaQDqWcJlrTUEACtXrkRBQQFmzZql3rR60qRJ8PHxwdatW+Ho6Fjutd3c3ODm5mZA9EREREQ1h8UmhHK5HOfPn9cqz8vLAwB4enqWeW6DBg3w1VdfITc3F9nZ2fDy8oKXlxf69u2Lxo0bq7fLISIiIiILTgi7dOmClJQU3Lp1S2Pl8/T0dPXxiigUCigUCgDAjRs38MsvvyA4ONgk8RIRERHVVBa7MPXo0aNRXFyMVatWqcsKCwuxdu1a9OrVS72FTG5uLk6ePFlhe7Nnz8aDBw8wc+ZMk8VMREREVBNZbA9hr169MGbMGMyePRuXLl2Cr68v1q9fj+zsbKxZs0ZdLyQkBPv378fDq+csWbIEGRkZ6NWrF6ytrbF9+3bs3r0bCxYsQI8ePczxcIiIiIgslsUmhACQmJiIOXPmYMOGDbh+/To6deqEb775Bv7+/uWe17FjR2zbtg1ff/01iouL0alTJ3z55ZdaM4eJiIiIyMITQjs7OyxduhRLly4ts05qaqpWWWBgIAIDA00YGREREVHtYbFjCImIiIioejAhJCIiIqrjmBASERERGdnAgQMxcODAKp0rkUgwb948o8ZTESaEREREpNO6desgkUg0/rm5uSEgIADffvutya577949zJs3T+c8AV3++usvzJs3D9nZ2UaL4dHHXda/ysZo6Sx6UgkRERGZX0xMDFq0aAEhBC5evIh169ZhxIgR2LFjB5588kmjX+/evXuYP38+AFSql+2vv/7C/PnzMXDgQDRv3twoMWzYsEHj58TEROzZs0ervG3btjrP3717t1HiqC5MCImIiKhcw4cPR/fu3dU/h4aGwt3dHZ9//rlJEkJLMGnSJI2fjxw5gj179miVP+revXtwcHCAjY2NKcMzOt4yJiIiIr04OzvD3t4e1taa/UolJSX44IMP0L59e9jZ2cHd3R0vvfQSrl+/rlHv559/xhNPPAFXV1fY29ujRYsWeOGFFwAA2dnZaNy4MQBg/vz56luzZY2pW7dunXqd4YCAAJ23cuPj49G+fXvY2trC09MTr7zyCm7cuGHw8zBw4EB06NABv/zyC/z9/eHg4IC3335bfezh3s2ioiJER0ejW7duaNCgAerVq4f+/fsjJSXF4DiMgT2EREREVK6bN2/iypUrEELg0qVL+Oijj3Dnzh2t3rKXXnoJ69atw/PPP4/p06fj7Nmz+Pjjj/Hbb78hLS0NMpkMly5dwuOPP47GjRsjMjISzs7OyM7OxtatWwEAjRs3xqeffopp06Zh5MiRGDVqFACgU6dOOmPz9/fH9OnT8eGHH+Ltt99W38JV/XfevHmYP38+hgwZgmnTpuHvv//Gp59+ip9++kkdkyGuXr2K4cOHY/z48Zg0aRLc3d111rt16xYSEhLw7LPP4sUXX8Tt27exZs0aPPHEEzh69Ci6dOliUByGYkJIRERkZPcLgax/zB2FJp+mgJ1t1c4dMmSIxs+2trb43//+h6FDh6rLDh06hISEBCQlJWHChAnq8oCAAAwbNgybN2/GhAkTcPjwYVy/fh27d+/WuA29YMECAEC9evUwevRoTJs2DZ06darwFq23tzf69++PDz/8EEOHDtXolbt8+TIWL16Mxx9/HN9++y2k0tIbo23atMGrr76KjRs34vnnn6/ak/L/8vPzsWLFCrz00kvl1mvYsCGys7M1biW/+OKLaNOmDT766CONbXnNgQkhERGRkWX9A3QYZ+4oNGVsAtr7VO3cTz75BK1atQIAXLx4ERs3bkRYWBjq16+v7sHbvHkzGjRogKFDh+LKlSvqc7t16wZHR0ekpKRgwoQJcHZ2BgB888036Ny5s8E9dOXZu3cvioqKMGPGDHUyCJQmYm+//TZ27txpcEJoa2tbqTasrKxgZWUFoPTW+o0bN1BSUoLu3bvj119/NSgGY2BCSEREROXq2bOnRm/es88+i65du+LVV1/Fk08+CRsbG5w+fRo3b96Em5ubzjYuXboEABgwYACCg4Mxf/58vP/++xg4cCCCgoIwYcIE2NpWsQuzDDk5OQCA1q1ba5Tb2NjA29tbfdwQTZo0qfQEkvXr1+O9997DyZMnoVQq1eUtWrQwOA5DMSEkIiIivUilUgQEBGD58uU4ffo02rdvj5KSEri5uSEpKUnnOaqJIhKJBFu2bMGRI0ewY8cOfP/993jhhRfw3nvv4ciRI3B0dKzOh2Iwe3v7StXbuHEjpkyZgqCgILz55ptwc3ODlZUVFi9ejKysLBNHWTEmhEREREbm07T0Fq0l8Wlq3PYePHgAALhz505p+z4+2Lt3L/z8/CqVJPXu3Ru9e/fGwoUL8dlnn2HixIn44osvEBYWBolEolcsZdX38vICAPz999/w9vZWlxcVFeHs2bNaYyNNacuWLfD29sbWrVs14p07d261xVAeJoRERERGZmdb9fF6NYFSqcTu3bthY2Ojns07duxYxMfHIzY2FosWLdKo/+DBA9y5cwfOzs64fv06nJ2dNZIi1QzbwsJCAICDgwMAVHppmHr16umsP2TIENjY2ODDDz/EsGHD1Ndcs2YNbt68icDAQL0etyFU4weFEOo40tPT8eOPP0KhUFRbHGVhQkhERETl+vbbb3Hy5EkApWMBP/vsM5w+fRqRkZFwcnICUDo28KWXXsLixYtx7NgxPP7445DJZDh9+jQ2b96M5cuXY/To0Vi/fj3i4+MxcuRI+Pj44Pbt21i9ejWcnJwwYsQIAKW3Ydu1a4dNmzahVatWcHFxQYcOHdChQwed8XXp0gVWVlaIi4vDzZs3YWtri0GDBsHNzQ2zZ8/G/PnzMWzYMDz99NP4+++/ER8fjx49elQ4g9mYnnzySWzduhUjR45EYGAgzp49ixUrVqBdu3bqXlZzYkJIRERE5YqOjlb/v52dHdq0aYNPP/1Ua6mVFStWoFu3bli5ciXefvttWFtbo3nz5pg0aRL8/PwAlCaOR48exRdffIGLFy+iQYMG6NmzJ5KSkjQmVyQkJOC1117DzJkzUVRUhLlz55aZEHp4eGDFihVYvHgxQkNDUVxcjJSUFLi5uWHevHlo3LgxPv74Y8ycORMuLi6YOnUqFi1aZNIZzo+aMmUK8vPzsXLlSnz//fdo164dNm7ciM2bN1vEfsgSIYQwdxA1wfHjx9GhQwdkZGSgffv25g6HiIgswJkzZwBAY3wakalV5n2nb97CreuIiIiI6jgmhERERER1HBNCIiIiojqOCSERERFRHceEkIiIiKiOY0JIREREVIOYYoEYJoRERERVJJFI8ODBA5P8gibSRQiB4uJiSKXGTeGYEBIREVWRo6MjiouLkZeXp97bl8hUhBC4dOkSiouLYWtra9S2uVMJERFRFTVs2BD37t3DzZs3cfPmTVhbW0MqlWrs00tkDKqeweLiYtjb28Pd3d2o7TMhJCIiqiJra2soFArcvn0bt27dglKp5O1jMgmJRAIbGxvY2trC3d3d6LeMmRASEREZQCKRwMnJCU5OTuYOhajKOIaQiIiIqI5jQkhERERUxzEhJCIiIqrjmBASERER1XFMCImIiIjqOCaERERERHUcE0IiIiKiOo4JIREREVEdx4SQiIiIqI5jQkhERERUxzEhJCIiIqrjmBASERER1XHWhjZw584dnDx5EleuXIFEIoGrqytatWqF+vXrGyM+IiIiIjKxKvUQnj17FvPmzUPXrl3RsGFD9OrVC4GBgRgxYgR69uwJFxcXdOnSBfPmzcOZM2eqHFxhYSEiIiLg6ekJe3t79OrVC3v27KnUuXv37kVAQABcXV3h7OyMnj17YsOGDVWOhYiIiKi20quH8K+//kJ0dDS2bdsGZ2dnDBw4EGPGjIG3tzcaNmwIIQSuX7+Os2fP4pdffsHHH3+M2NhYjBw5ErGxsWjbtq1ewU2ZMgVbtmzBjBkz0LJlS6xbtw4jRoxASkoK+vXrV+Z5X3/9NYKCgtCnTx/MmzcPEokEX375JUJCQnDlyhXMnDlTrziIiIiIajOJEEJUtrJMJkNgYCBefvllDBkyBNbW5eeTDx48wN69e7FixQrs2rULRUVFlQ7s6NGj6NWrF5YuXYpZs2YBAO7fv48OHTrAzc0Nhw8fLvPcxx9/HMePH8eZM2dga2urjqVNmzaoV68efv/990rHoXL8+HF06NABGRkZaN++vd7nExEREVUXffMWvXoI//jjD716+aytrTFs2DAMGzYMJ0+e1OdS2LJlC6ysrDB16lR1mZ2dHUJDQ/H222/j3LlzaNasmc5zb926hYYNG6qTQVUsrq6uesVAREREVBfolRA+nAwqlUqcOHECLi4uaNq0aYXntmnTRq/AfvvtN7Rq1QpOTk4a5T179gQAHDt2rMyEcODAgYiLi8OcOXMwefJkSCQSfPbZZ/j555/x5ZdfVnjtS5cu4fLlyxplmZmZesVPREREVFNUeZaxVCpFt27d8N5772H69OnGjAkAkJeXB7lcrlWuKrtw4UKZ586ZMwdnz57FwoULsWDBAgCAg4MDkpOT8cwzz1R47fj4eMyfP7+KkRMRERHVLFVOCK2srODl5YXCwkJjxqNWUFCgcctXxc7OTn28LLa2tmjVqhVGjx6NUaNGobi4GKtWrcKkSZOwZ88e9O7du9xrh4eHY8yYMRplmZmZCAoK0v+BEBEREVk4g9YhfO211/Dxxx8jNDQULi4uxooJAGBvb68z2bx//776eFleffVVHDlyBL/++iuk0tKVdcaOHYv27dvj9ddfR3p6ernXdnNzg5ubmwHRExEREdUcBiWExcXFsLW1hY+PD0aPHo3mzZtrJWoSiaRKy7zI5XKcP39eqzwvLw8A4OnpqfO8oqIirFmzBm+99ZY6GQRKZ0gPHz4cH3/8MYqKimBjY6N3TERERES1kUEJoWo5GABYs2aNzjpVTQi7dOmClJQU3Lp1S2Niiap3r0uXLjrPu3r1Kh48eIDi4mKtY0qlEiUlJTqPEREREdVVBu1lfPbs2Qr/VXWnktGjR6vH/qkUFhZi7dq16NWrl3qGcW5ursaSNm5ubnB2dsa2bds01j28c+cOduzYgTZt2pR7u5mIiIiorjGoh9DLy8tYcWjp1asXxowZg9mzZ+PSpUvw9fXF+vXrkZ2drdEbGRISgv3790O1vraVlRVmzZqFqKgo9O7dGyEhISguLsaaNWvwzz//YOPGjSaLmYiIiKgmMighVDl//jwOHDiAS5cuITg4GE2bNkVxcTFu3ryJBg0awMrKqkrtJiYmYs6cOdiwYQOuX7+OTp064ZtvvoG/v3+5573zzjto0aIFli9fjvnz56OwsBCdOnXCli1bEBwcXKVYiIiIiGorvbaue5QQAm+88QY+/vhjPHjwABKJBHv27MGgQYNw8+ZNNGvWDDExMZgxY4YRQzYPbl1HRERENYW+eYtBYwiXLl2K5cuXY9asWdizZw8ezi0bNGiAUaNGITk52ZBLEBEREZGJGZQQrl69GiEhIVi0aJHOWb+dOnXCqVOnDLkEEREREZmYQQnhuXPn0Ldv3zKP16tXD7du3TLkEkRERERkYgYlhG5ubjh37lyZx3/55RcoFApDLkFEREREJmZQQjhq1CisWLFCY61BiUQCANi9ezfWrVuntScwEREREVkWgxLC+fPnQy6Xo0uXLggJCYFEIkFcXBz69euH4cOHo1OnTnj77beNFSsRERERmYBBCWGDBg1w5MgRvPXWWzh//jzs7Oywf/9+3LhxA3PnzsXBgwfh4OBgrFiJiIiIyAQMXpja3t4eUVFRiIqKMkY8RERERFTNDOohHDRoEPbt21fm8ZSUFAwaNMiQSxARERGRiRmUEKampuLixYtlHr906RL2799vyCWIiIiIyMQMSgiBf2cV65KZmYn69esbegkiIiIiMiG9xxCuX78e69evV/+8YMECrF69WqvejRs38Mcff2DEiBGGRUhEREREJqV3Qnjv3j1cvnxZ/fPt27chlWp2NEokEtSrVw8vv/wyoqOjDY+SiIiIiExG74Rw2rRpmDZtGgCgRYsWWL58OZ5++mmjB0ZERERE1cOgMYTr169Hnz59yjx+5coVHDhwwJBLEBEREZGJGZQQBgQEYM+ePWUe37dvHwICAgy5BBERERGZmEEJoRCi3OOFhYWwsrIy5BJEREREZGJ6jyHMzc1Fdna2+ueTJ0/qvC1848YNrFy5El5eXgYFSERERESmpXdCuHbtWsyfPx8SiQQSiQQLFy7EwoULteoJIWBlZYWVK1caJVAiIiIiMg29E8KxY8eiQ4cOEEJg7NixmD59Ovr3769RR7XsTJcuXeDu7m60YImIiIjI+PROCNu2bYu2bdsCKO0t9Pf3R4sWLYweGBERERFVD70TwodNnjxZ/f95eXm4dOkSfH19Ua9ePYMDIyIiIqLqYfBexl999RXatGmDpk2b4rHHHkN6ejqA0jUIu3btiu3btxt6CSIiIiIyIYMSwh07dmDUqFFwdXXF3LlzNZahcXV1RZMmTbB27VqDgyQiIiIi0zEoIYyJiYG/vz8OHTqEV155Ret4nz598NtvvxlyCSIiIiIyMYMSwoyMDIwdO7bM4+7u7rh06ZIhlyAiIiIiEzMoIXRwcMDdu3fLPH7mzBk0atTIkEsQERERkYkZvJfx+vXr8eDBA61j+fn5WL16NR5//HFDLkFEREREJmZQQrhw4UL8888/6NGjB1auXAmJRILvv/8eUVFR6NixI4QQmDt3rrFiJSIiIiITMCghbN26NQ4dOoRGjRphzpw5EEJg6dKlWLRoETp27IiDBw+iefPmRgqViIiIiEzBoIWpAaB9+/bYu3cvrl+/jszMTJSUlMDb2xuNGzc2RnxEREREZGIGJ4QqDRs2RI8ePYzVHBERERFVkyonhFlZWbC2toaXlxcAoLCwEAkJCThw4ADu3LmDLl264NVXX4VcLjdasERERERkfHonhNevX8fw4cPx008/AQAGDBiA5ORkPPXUUzh8+LC63rfffos1a9bgxx9/RIsWLYwXMREREREZld6TShYvXoxff/0Vb7zxBt59912cOnUKzzzzDP766y9s2bIF169fx+XLl7FmzRrcvHkT0dHRpoibiIiIiIxE7x7C7du348UXX8S7774LAGjVqhWeeeYZLFq0CKNGjVLXe/7553Hs2DF8+eWXxouWiIiIiIxO7x7Cc+fOoVu3buqfH3vsMQBA586dtep26dIFV65cMSA8IqqrlEolUlNTsXXrVqSmpkKpVJo7JCKiWkvvHsLCwkLY2dmpf1b9v62trVZdGxsblJSUGBAeEdU1SqUSS5YsQXx8PPLz89Xlcrkc06ZNQ2RkJGQymRkjJCKqfao0y1gikVSqjIhIH0qlEkFBQdi1axcUCgViYmLg4+ODrKwsJCQkIDo6Gunp6di2bRuTQiIiI6pSQvjf//4Xn3/+OQCob+O88847cHV11ah3/vx5A8MjorpkyZIl2LVrF0JCQpCQkKCR9EVGRiIsLAyJiYmIi4tDVFSUGSMlIqpdJEIIoc8JzZs317s38OzZs3rVVyksLER0dDQ2bNiA69evo1OnTliwYAGGDh1aYYw5OTk6j/n6+uL06dN6x3L8+HF06NABGRkZaN++vd7nE1H5lEolFAoFbGxskJmZqbMHUKlUwtfXF0qlEjk5OewlJCIqg755i949hNnZ2VWJq0qmTJmCLVu2YMaMGWjZsiXWrVuHESNGICUlBf369SvzvA8++AB37tzRKMvJyUFUVBQef/xxU4dNRFWQlpaG/Px8xMTElJnoyWQyhIWFITo6GmlpaRg4cGD1BklEVEsZbes6Yzt69Ci++OILLF26FLNmzQIAhISEoEOHDnjrrbc0FsF+VFBQkFbZggULAAATJ040SbxEZJhr164BAHx8fMqt5+3trVGfiIgMp/eyM9Vly5YtsLKywtSpU9VldnZ2CA0NxY8//ohz587p1d5nn32GFi1aoG/fvsYOlYiMwMXFBUDptpjlOXPmjEZ9IiIynMUmhL/99htatWoFJycnjfKePXsCAI4dO6ZXWydOnMCECRMqVf/SpUs4fvy4xr/MzMxKX4+I9Ofn5wcPDw8kJCSUueagUqlEQkIC5HI5/Pz8qjlCIqLay2ITwry8PMjlcq1yVdmFCxcq3VZSUhKAyt8ujo+PR4cOHTT+6boNTUTGI5PJEB4ejtzcXISFhWklhUqlEqGhocjNzUV4eDgnlBARGZHFjiEsKCjQudi1aiHsgoKCSrVTUlKCL774Al27dkXbtm0rdU54eDjGjBmjUZaZmcmkkMjEIiMjkZ6ejsTERKSmpiIsLAze3t7IysrCmjVrkJubi8DAQERERJg7VCKiWsViE0J7e3sUFhZqld+/f199vDL279+P8+fPY+bMmZW+tpubG9zc3Cpdn4iMQyaTYdu2bYiLi0N8fDyio6PVx+RyOWJjYxEREcHeQSIiIzN6QiiEQEpKCgoLC9GvXz/Ur1+/Su3I5XKdC1vn5eUBADw9PSvVTlJSEqRSKZ599tkqxUFE1UsmkyEqKgoRERFIS0vDtWvX4OLiAj8/PyaCREQmYlBC+M477+Dw4cNISUkBUJoMPv744/jhhx8ghIBCocC+ffsqXEZCly5duiAlJQW3bt3SmFiSnp6uPl6RwsJCJCcnY+DAgZVOIIkMoVQqmcQYiUwm4zqDRETVxKBJJcnJyepZv0DpUjH79u3DggUL8M0336C4uBjz5s2rUtujR49GcXExVq1apS4rLCzE2rVr0atXLzRr1gwAkJubi5MnT+psY9euXbhx4wbXHiSTUyqViI2NhUKhQEBAAIKDgxEQEAAvLy/ExsaWOWuWiIjIEhjUQ3j+/Hn4+vqqf966dSvatWuH2bNnAwCmTZuGTz/9tEpt9+rVC2PGjMHs2bNx6dIl+Pr6Yv369cjOzsaaNWvU9UJCQrB//37o2oEvKSkJtra2CA4OrlIMRJWhVCoRFBSEXbt2QaFQICYmBj4+PsjKykJCQgKio6ORnp6Obdu2sbeQiIgskkEJobW1tXrihxAC+/btQ0hIiPq4u7s7rly5UuX2ExMTMWfOHI29jL/55hv4+/tXeO6tW7ewc+dOBAYGokGDBlWOgagiS5Yswa5duxASEoKEhASNpC8yMhJhYWFITExEXFwcoqKizBgpERGRbhKhq2utkvr37w+lUolvv/0W27Ztw4svvoi9e/ciICAAABAdHY21a9fqvauIJdJ3k2iqG5RKJRQKBWxsbJCZmamzB1CpVMLX1xdKpRI5OTnsJSQiIpPTN28xaAxhdHQ0jh07BldXV7z44ovw8/NTJ4MAsHPnTvTo0cOQSxBZtLS0NOTn5yMsLKzMRE8mkyEsLAx5eXlIS0ur5giJiIgqZtAt46FDh+LXX3/Fnj174OzsjHHjxqmPXb9+Hf7+/njmmWcMDpLIUl27dg0AKpxJ7+3trVGfiIjIkhi8DmG7du3Qrl07rfKGDRvi/fffN7R5Iovm4uICAMjKyiq33pkzZzTqExERWRKL3cuYqCbw8/ODh4cHEhISylxaRqlUIiEhAXK5HH5+ftUcIRERUcX0SgilUimsra1RVFSk/tnKyqrcf9bWFrs7HpHBZDIZwsPDkZubi7CwMK2kUKlUIjQ0FLm5uQgPD+eEEiIiskh6ZWvR0dGQSCTqJE/1M1FdFhkZifT0dCQmJiI1NRVhYWHw9vZGVlYW1qxZg9zcXAQGBiIiIsLcoRIREelk0LIzdQmXnaHyKJVKxMXFIT4+Xr3fNlC6J3d4eDgiIiLYO0hERNVG37yF93OJjEAmkyEqKgoRERHcy5iIiGocJoRERiSTyTBw4EBzh0FERKQXzjImIiIiquOYEBIRERHVcUwIiYiIiOq4KieEBQUF+M9//oMdO3YYMx4iIiIiqmZVTgjt7e2xcuVKXLx40ZjxEBEREVE1M+iWcbdu3ZCRkWGsWIiIiIjIDAxKCD/44AN88cUXSEhIwIMHD4wVExERERFVI4PWIZwyZQqkUileeuklTJ8+HU2aNIG9vb1GHYlEgt9//92gIImIiIjIdAxKCF1cXNCoUSO0bt3aWPEQERERUTUzKCFMTU01UhhEREREZC5ch5CIiIiojjM4Ibx16xaWLFmCJ554Al27dsXRo0cBANeuXcOyZcuQmZlpcJBEREREZDoG3TL+559/MGDAAJw7dw4tW7bEyZMncefOHQCl4wtXrlyJnJwcLF++3CjBEhEREZHxGZQQvvnmm7h9+zaOHTsGNzc3uLm5aRwPCgrCN998Y1CARERERGRaBt0y3r17N6ZPn4527dpBIpFoHff29sa5c+cMuQQRERERmZhBCWFBQQEaN25c5vHbt28b0jwRERERVQODEsJ27drhwIEDZR7fvn07unbtasgliIiIiMjEDEoIZ8yYgS+++AJxcXG4efMmAKCkpASZmZl47rnn8OOPP2LmzJlGCZSIiIiITMOgSSWTJk1CTk4OoqKi8M477wAAhg0bBiEEpFIpFi1ahKCgIGPESUREREQmYlBCCADvvPMOnnvuOSQnJyMzMxMlJSXw8fHBqFGj4O3tbYwYiYiIiMiEDE4IAUChUPDWMBEREVENZdAYwmeffRYrVqxARkaGseIhIiIiompmUA/hsWPHsGnTJkgkEjg7O8PPzw/9+/eHv78/unXrBmtro3RAEhEREZEJGZSxnThxAleuXMHBgwdx8OBBHDp0CG+//TZKSkpgb2+PXr16wd/fH3PnzjVWvERERERkZAbdMgYAV1dXjBw5EsuWLcPRo0dx48YNrFmzBk2bNkVKSgpiYmKMEScRERERmYhR7umeOnVK3Ut48OBBZGdnw9HREU888QT69+9vjEsQERERkYkYlBCOHj0ahw4dwuXLl9GoUSP0798fr732Gvz9/dGlSxdIpQZ3QBIRERGRiRmUEG7duhVSqRRjxozB1KlT0adPH9jb2xsrNiIiIiKqBgYlhFu2bFHfJn7iiScglUrx2GOPoX///ujfvz/69euHhg0bGitWIiIiIjIBgxLCUaNGYdSoUQCA27dv4/Dhwzh06BAOHjyITz75BIWFhWjbti3+/PNPowRLRERERMZntEF+9evXR8uWLeHj4wNvb280btwYJSUl+Ouvv4x1CSIiIiIyAYN6CDMyMnDgwAH1beO8vDwIIaBQKNS3jTnLmIiIiMiyGdRD2KlTJ7z22mvIyMjA008/jY0bNyInJwfZ2dnYsGEDpk6dirZt21a5/cLCQkRERMDT01O90PWePXsqff6mTZvQp08f1KtXD87Ozujbty9++OGHKsdDREREVBsZ1EP41VdfmXTiyJQpU7BlyxbMmDEDLVu2xLp16zBixAikpKSgX79+5Z47b948xMTEYPTo0ZgyZQqUSiUyMjJw/vx5k8RKREREVFNJhBDC3EHocvToUfTq1QtLly7FrFmzAAD3799Hhw4d4ObmhsOHD5d57pEjR9C3b1+89957mDlzplHiOX78ODp06ICMjAy0b9/eKG0SERERmYK+eYvBk0pu3bqF+fPno2fPnnB3d4e7uzt69uyJmJgY3Lp1q8rtbtmyBVZWVpg6daq6zM7ODqGhofjxxx9x7ty5Ms/94IMP4OHhgddffx1CCNy5c6fKcRARERHVdgYlhBcuXEDXrl0xf/583LlzB35+fvDz88Pdu3cxb948PPbYY8jLy6tS27/99htatWoFJycnjfKePXsCAI4dO1bmufv27UOPHj3w4YcfonHjxqhfvz7kcjk+/vjjSl370qVLOH78uMa/zMzMKj0OIiIiIktn0BjCiIgI5Ofn45tvvsGIESM0jn377bcYM2YMIiMjsX79er3bzsvLg1wu1ypXlV24cEHnedevX8eVK1eQlpaGH374AXPnzoVCocDatWvx2muvQSaT4aWXXir32vHx8Zg/f77eMRMRERHVRAYlhN999x1mzJihlQwCwPDhwzF9+nSsXr26Sm0XFBTA1tZWq9zOzk59XBfV7eGrV6/iiy++wLhx4wCU7rvcsWNHLFiwoMKEMDw8HGPGjNEoy8zMRFBQkL4Pg4iIiMjiGZQQ3r17F+7u7mUe9/DwwN27d6vUtr29PQoLC7XK79+/rz5e1nkAIJPJMHr0aHW5VCrFuHHjMHfuXOTm5kKhUJR5bTc3N7i5uVUpbiIi+pdSqURaWhquXbsGFxcX+Pn5QSaTmTssInqEQWMI27Vrh88//xxFRUVax5RKJT7//HO0a9euSm3L5XKd4w9VZZ6enjrPc3FxgZ2dHRo1agQrKyuNY6ok7/r161WKiYiIKkepVCI2NhYKhQIBAQEIDg5GQEAAvLy8EBsbC6VSae4QieghBo8hHDduHHr27Inw8HC0atUKAPD3339jxYoV+OOPP7Bp06Yqtd2lSxekpKTg1q1bGhNL0tPT1cd1kUql6NKlC3766ScUFRXBxsZGfUw17rBx48ZViomIiCqmVCoRFBSEXbt2QaFQICYmBj4+PsjKykJCQgKio6ORnp6Obdu2sbeQyFIIA61du1a4u7sLiUQipFKpkEqlQiKRCHd3d7Fu3boqt3vkyBEBQCxdulRddv/+feHr6yt69eqlLsvJyREnTpzQOPf9998XAMSqVavUZQUFBcLb21u0a9euSvFkZGQIACIjI6NK5xMR1RUxMTECgAgJCRFFRUUax4qKikRISIgAIGJjY80UIVHtp2/eYpSFqR88eICff/4ZOTk5AAAvLy90794d1tYGdUBi7Nix2LZtG2bOnAlfX1+sX78eR48exb59++Dv7w8AGDhwIPbv34+HH0ZBQQF69OiBU6dO4fXXX4dCocCGDRvw66+/YseOHRg+fLjesXBhaiKiiimVSigUCtjY2CAzM1NnD6BSqYSvry+USiVycnLYS0hkAtW+MDUAWFtbo3fv3hg3bhzGjRuH3r17w9raGp9++qn6NnJVJCYmYsaMGdiwYQOmT58OpVKJb775Rp0MlsXe3h4//PADJkyYgP/973948803IZVKsXPnziolg0REVDlpaWnIz89HWFhYmYmeTCZDWFgY8vLykJaWVs0REpEuhnXhVeDatWvIysqq8vl2dnZYunQpli5dWmad1NRUneVubm5Yt25dla9NRET6u3btGgDAx8en3Hre3t4a9YnIvIzSQ0hERASUrvQAoMLOgDNnzmjUJyLzYkJIRERG4+fnBw8PDyQkJJS5tIxSqURCQgLkcjn8/PyqOUIi0oUJIZmEUqlEamoqtm7ditTUVK45RlRHyGQyhIeHIzc3F2FhYVqffaVSidDQUOTm5iI8PJwTSogshEnHEFLdo1QqsWTJEsTHxyM/P19dLpfLMW3aNERGRvIXAFEtFxkZifT0dCQmJiI1NRVhYWHw9vZGVlYW1qxZg9zcXAQGBiIiIsLcoRLR/9M7Iaxfvz4kEkml6urawYRqLy5GS0RAaS/htm3bEBcXh/j4eERHR6uPyeVyxMbGIiIigt8DRBZE74QwODi40gkh1S1LlizBrl27EBISgoSEBI0v+8jISISFhSExMRFxcXGIiooyY6REZGoymQxRUVGIiIgw6l7G3BuZyDSMsjB1XcCFqcvHxWiJyJQ4HIVIP2ZZmJqIi9ESkamohqNER0fDxsYGMTExSEpKQkxMDGQyGaKjozFy5EhOXiMygF4J4Y8//ljlCxlyLlk+LkZLRKby8HCUzMxMzJkzBxMmTMCcOXOQmZmJkJAQ7Ny5E3FxceYOlajG0ishHDRoEAICAvDll1/i3r17Fda/c+cOPvvsM/j7+2Pw4MFVDpIsHxejJSJTUCqViI+Ph0Kh0BqbDJTeeUhISIBCoUB8fDx7CYmqSK9JJadOnUJMTAyee+45yGQy9OrVC4899hhatGiBhg0bQgiB69ev4+zZs/j5559x9OhRPHjwACEhIUhKSjLVYyAL8PBitGWN5eFitESkL9VwFNXtYV1Uw1Gio6ORlpaGgQMHVm+QRLWAXglhs2bNsHr1aixevBgbNmzAV199hfj4eBQUFGjUs7e3R/fu3bFgwQI899xzaNy4sVGDJsujWow2OjoaYWFhWn/JP7wYbWxsLAd/E1GlcDgKUfWo0sLUrq6umDlzJmbOnIkHDx4gNzcXV69eBQA0atQICoUC1tZc87qu4WK0RGRsHI5CVD247EwlcdmZylEqlerFaPPy8tTlcrkc4eHhXIy2CrjuGtVlXNKKqGq47AyZlWox2pycHKSkpCA5ORkpKSnIyclBVFQUv6j1oFQqERsbC4VCgYCAAAQHByMgIABeXl6IjY3l4HmqE7g3MlH14H1dMgmZTMaB3QbgNoBE/+JwFCLTY0JIZIG4DSDRv7g3MpHpcQxhJXEMIVUXjpkiKhvH1BJVDscQEtVw3AaQqGyq4SijRo3CwIEDmQwSGYnREsK8vDz8/vvvuHv3rrGaJKqTuO4aERFVN4MTwq+++gpt2rRB06ZN8dhjjyE9PR0AcOXKFXTt2hXbt2839BJEdQrXXSMioupmUEK4Y8cOjBo1Cq6urpg7dy4eHo7o6uqKJk2aYO3atQYHSVSXPLwNYFlLy3AbQCIiMiaDEsKYmBj4+/vj0KFDeOWVV7SO9+nTB7/99pshlyCqc7juGhERVTeDlp3JyMjAsmXLyjzu7u6OS5cuGXIJojqJ664REVF1MighdHBwKHcSyZkzZ9CoUSNDLkFUJ3HdNSIiqk4GJYQBAQFYv349ZsyYoXUsPz8fq1evxpNPPmnIJYjqLNU2gBEREVx3jYiITMqghHDhwoXo3bs3evTogTFjxkAikeD777/HDz/8gJUrV0IIgblz5xorVqI6idsAEhGRqRk0qaR169Y4dOgQGjVqhDlz5kAIgaVLl2LRokXo2LEjDh48iObNmxspVCIiIiIyBYP3Mm7fvj327t2L69evIzMzEyUlJfD29kbjxo2NER8RERERmZjBCaFKw4YN0aNHD2M1R0REZFG4jzLVZgYlhImJiZWqFxISYshliIiIzEapVGLJkiWIj49Hfn6+ulwul2PatGmIjIxkYkg1nkEJ4ZQpU8o8JpFI1P/PhJCIiGoipVKJoKAg7Nq1CwqFAjExMfDx8UFWVhYSEhIQHR2N9PR0bNu2jUkh1WgGJYRnz57VKisuLkZ2djbi4+ORm5uL9evXG3IJIiIis1myZAl27dqFkJAQJCQkaCR9kZGRCAsLQ2JiIuLi4hAVFWXGSIkMIxEPb0BsZIGBgWjevDk++eQTU12i2hw/fhwdOnRARkYG2rdvb+5wiGokjsGimkSpVEKhUMDGxgaZmZk636tKpRK+vr5QKpXIycnh+5kshr55i0HLzlTkySefxKZNm0x5CSKqAZRKJWJjY6FQKBAQEIDg4GAEBATAy8sLsbGxWvs1E1mCtLQ05OfnIywsrMxETyaTISwsDHl5eUhLS6vmCImMx2izjHXJyspCYWGhKS9BRBaOY7Coprp27RoAwMfHp9x63t7eGvWJaiKDEsIDBw7oLL9x4wYOHDiADz/8EEFBQYZcgohqOI7BoprKxcUFQGnnRnnOnDmjUZ+oJjJoDKFUKtWYTawihICVlRXGjBmDjz76CI0aNTIoSEvAMYRE+uMYLKrJ+P6lmkzfvMWgHsKUlBStMolEgoYNG8LLywtOTk6GNE9ENZxqDFZMTEyFY7Cio6ORlpbGfZvJYshkMoSHhyM6OhphYWFaPdxKpRKhoaHIzc1FbGwsk0Gq0QxKCAcMGGCsOIioFuIYLKrpIiMjkZ6ejsTERKSmpiIsLAze3t7IysrCmjVrkJubi8DAQERERJg7VCKDmHRSCRHVbRyDRTWdTCbDtm3bEBcXh/j4eERHR6uPyeVyxMbGIiIigr2DVOPpNYawRYsWOscMlnsBiaTCXwZlKSwsRHR0NDZs2IDr16+jU6dOWLBgAYYOHVruefPmzcP8+fO1ym1tbXH//v0qxcIxhET64xgsqk24jibVJCYdQzhgwAC9E0JDTJkyBVu2bMGMGTPQsmVLrFu3DiNGjEBKSgr69etX4fmffvopHB0d1T9bWVmZMlwis7LEX1Ycg0W1iUwm4xhXqrX0SgjXrVtnojC0HT16FF988QWWLl2KWbNmASjdE7lDhw546623cPjw4QrbGD16NFxdXU0dKpFZKZVKLFmyBPHx8cjPz1eXy+VyTJs2DZGRkWZNtDgGi4jI8lnsGMItW7bAysoKU6dOVZfZ2dkhNDQUb7/9Ns6dO4dmzZqV24YQArdu3UL9+vWrtWfTlCyxF4jMpyYs+swxWEREls8oCaFSqcTJkydx8+ZNlJSUaB339/fXu83ffvsNrVq10lq6pmfPngCAY8eOVZgQent7486dO6hXrx6CgoLw3nvvwd3dvcJrX7p0CZcvX9Yoy8zM1PMRGJel9wKRedSURZ9lMhmioqIQERHBP2iIiCyQQQtTl5SUYPbs2YiPj8e9e/fKrFdcXKx32x06dIC7uzv27dunUf7XX3+hffv2WLFiBV566SWd5y5fvhyZmZno06cPbG1tcfDgQXzyySdo0aIFfv755wrXRyxrUgoAs0wqebQXKCwsTKMXSHXLjVt/1S2csEFERGXRezKsMEBsbKyQSCTi5ZdfFhs3bhQSiUS8++67YtWqVaJLly6ia9euYs+ePVVq29vbWwwfPlyrPCsrSwAQ77//vl7tJSUlCQBi8eLFFda9ePGiyMjI0Pi3fft2AUBkZGTodV1jiImJEQBESEiIKCoq0jhWVFQkQkJCBAARGxtb7bGR+aSkpAgAIiYmptx6qvdPSkpK9QRGRERml5GRoVfeIjUk+1y3bh3Gjh2LTz/9FMOGDQMAdOvWDS+++CLS09MhkUjwww8/VKlte3t7FBYWapWrlo2xt7fXq70JEybAw8MDe/furbCum5sb2rdvr/HP19dXr+sZi1KpRHx8PBQKhdYtQaD0VlxCQgIUCgXi4+OhVCrNEidVPy76TERExmJQQvjPP/9g0KBBAErX+AP+TdhsbGwwadIkbNiwoUpty+Vy5OXlaZWryjw9PfVus1mzZjXul6Jq66+wsLAKt/7Ky8tDWlpaNUdI5mJJiz4rlUqkpqZi69atSE1N5R8mREQ1jEEJYaNGjXDnzh0AgKOjI5ycnNS/fFSuX79epba7dOmCU6dO4datWxrl6enp6uP6EEIgOzsbjRs3rlI85sJeICqLn58fPDw8kJCQUGYCplQqkZCQALlcDj8/P6PHoFQqERsbC4VCgYCAAAQHByMgIABeXl6IjY1lYkhEVEMYlBB27doVP/30k/rngIAAfPDBB0hLS8PBgwfx4YcfonPnzlVqe/To0SguLsaqVavUZYWFhVi7di169eqlnmGcm5uLkydPapz76AxhoHSR6suXL6tvbdcUltQLRJZFtehzbm4uwsLCtJKvhxd9Dg8PN/qEEtVkp+joaNjY2CAmJgZJSUmIiYmBTCZDdHQ0Ro4cyaSwBmFPL1EdZsiAxa+++kqMHDlS3L9/XwghxPHjx0WjRo2EVCoVEolEuLi4iB9//LHK7Y8ZM0ZYW1uLN998U6xcuVL07dtXWFtbi/3796vrDBgwQDz6MOzt7cWUKVPEe++9Jz755BPx7LPPColEIrp06SLu3r1bpVj0HZxpLEVFRcLDw0MoFAqtCSUP11EoFEIul5dZh2qnoqIiERgYKAAIhUIhYmJixMaNG8X8+fOFQqEQAERgYKBJ3hec7FR7FBUViZiYGOHh4SEAqP/J5XIRExPD7xWiGkjfvMWghFCXGzduiO3bt4sdO3aIq1evGtRWQUGBmDVrlvDw8BC2traiR48e4rvvvtOooyshDAsLE+3atRP169cXMplM+Pr6ioiICHHr1q0qx2KuhFCIin/xPvfcc/zFW4cVFRWJ2NhYIZfLtX6Zx8bGmuSXOf9QqT2KiorEiBEjNP6oSEpKEjExMSb/o4KITKdaE8KSkhJDTq9RzJkQmrMXiGqOoqIikZKSIpKTk0VKSopJ3w9c8qb2YE8vUe2kb95i0E4lTZo0wZgxYzBu3Dj07dvXkKaoHNz6iypDJpNh4MCB1XItTnaqHSq7rFVqairi4+P5PUNUixk0qWTAgAH43//+h/79+0OhUGDWrFk4evSosWKjh6i2/srJyUFKSgqSk5ORkpKCnJwcREVF8UuaqhUnO9UOXNaKiFQM6iH8/PPPUVBQgG+++QabNm3Cp59+ivfffx/NmzfHuHHjMHbsWL2Xh6HyVWcvUHVQKpU1Ym/bmhJndXl4yZuy9tE29ZI3ZDhL6unlZ4zIvAzqIQRKdwwZM2YMtmzZgkuXLmHjxo3o2LEj3n//fXTr1g1t2rQxRpxUy9SU9etqSpzVzdxL3pBxWEJPLz9jRJZBIoQQxm70zp07WLduHd555x3cuXMHxcXFxr5EtdN7k2gqk2r9ul27dkGhUCAsLAw+Pj7IyspCQkICcnNzERgYiG3btpk1kagpcZqLUqnEyJEjsXPnTvXz4+3tjaysLKxZs6bOPz81gVKphEKhgI2NDTIzM8vs6fX19YVSqUROTo5RX0t+xohMR++8xVizWe7evSs+//xzMXLkSGFvby+kUqlo2bKliIqKMtYlzMqcs4xrm5oyq7GmxGlO5ljyhozLnMta8TNGZDr65i0G9RDev38fO3fuxKZNm7Br1y7cu3cPzZs3x9ixYzFu3Dh07dq1qk1bHPYQGoe5eyQevU5ZY5YsKc6agOO/ai5z9fTyM0ZkWtXaQ+jo6CikUqlo2rSpmDlzpjhy5IghzVk09hAahyWsX1eZXRksIU6i6mKOnl5+xohMq1rXIZwyZQrGjRuHfv36GdIMmVl19u6Ye1bjo2OWYmJiNMYsRUdHIz09HSEhIWaNk6g6qZa1ioiIqDPfBUSkyaCE8KOPPjJWHGQGSqUSS5YsQXx8PPLz89Xlcrkc06ZNK3M5EUOYe1bjkiVLsGvXLoSEhGgtxBsZGYmwsDAkJibC3d3drHESmUN1Lmtl7u8CItJkklnGtVFtG0Nortl95hw3pM+1i4qKAIDjm4hMhGMIiUxL37zF4HUIyTiUSiVSU1OxdetWpKammnztrYd7yjIzMzFnzhxMmDABc+bMQWZmJkJCQrBz507ExcUZ9brmXL9On10Z8vPzMXz4cK6zR2QiXMuSyMKYdERjLWKqSSWVmeBgbEVFRcLDw0MoFIoy2y8qKhIKhULI5XKjx1BUVCQCAwMFAKFQKERMTIzYuHGjmD9/vlAoFAKACAwMNPp1k5OTBQCRlJRUbr2NGzcKAGLTpk1miZOorjDXdwFRXaBv3sKEsJJMkRAWFRWJESNGaHwZJiUliZiYGJN+GVrC7L6aMquR6+wRmRY/Y0SmUa3rENYlphhDGBsbi+joaISEhOC9DxKgLP73lohSqcQbb7yBLZs3462ICMyYMUPjXAc7oIFj1a67detWBAcHIykpCRMmTCizXlJSEiZNmoTk5GSMGjWqaherQHXOcDZkzBLX2SMyLX7GiIxL37zFoFnGVHVKpRLx8fFQKBRISEjAa0tlWLn14RoyAB8CnT/Eu98B736neb5UCrw+Hlj2H/2vbUmz+6pzVqNqzFJ0dDTCwsK0Zhk/PGYpNjZW41h1xklUF/EzRmReJp1UsnDhQlhbM+fUpTITHMpTUgK8/xmQfUH/a/v5+cHDwwMJCQllTl5RKpVISEiAXC6Hn5+f/hexUJGRkQgMDERiYiJ8fX0RGxuLpKQkxMTEwNfXFxs2bEBgYCAiIiLMHSoREVG1MfksY96R1q2yi7JWJPUX/c+py7P7ZDIZtm3bhtjYWCiVSkRHR2PSpEmYO3culEolYmNjjb7UDhERkaXTu/vuwIEDla579uxZfZuvMx69bTvrOWDSCO1669atw5qEBHz40UfqvaFfWgT8VXo3F6m/AFOe0v/6kZGRSE9PR2JiIlJTU8vcv7Q29pSZY1cGIiIiS6b3pBKpVAqJRFKpukIISCQSFBcXVyk4S2LsSSWGTHCY+R7wweeldbzkQPaOqscQFxeH+Ph45OXlqcvlcjnCw8MRERHBBImIiKgGMvmkEkdHR3Tq1AkzZ86ssG5ycjI2bdqk7yXqBEMmOAzs9m9CmJMHnD0PtGhStRjYU0ZERER6J4Tdu3fHhQsXEBwcXGHdkydPVimouqKqt239HwMkEkDVt5v6S9USQhXO7qt+XGKjduDrSES1hd6TSnr27InTp0/jxo0bFdYVpQtfVyWuOqGqExwaOgFdWv37c1UmlpB5qF5XhUKBgIAABAcHIyAgAF5eXur3AVk+vo5EVNvoPYYwPz8ff//9N7p374569eqZKi6LY4qFqR+mb0/Df5aVLjsDAM3cgZxvSnsNyXIplUoEBQVh165dUCgUCAsLg4+PD7KyspCQkKDuEeYsZ8vG15GIagK98xaT7JdSC5lqL+Oq+ipVCHT791/WOXNHRBVRbYkXEhKitR1XUVGRCAkJEQBEbGysmSLUVlRUJFJSUkRycrJ6K7+6ria+jmS5+BkjU6nWrevS09PRq1evqp5eo5i6h1Bf128BjQb/O45wzRzghWfMGxOVzZBZ5eagVCqxZMkSxMfHIz8/X10ul8sxbdo0REZG1sner5r2OpLl4meMTE3fvMWghan79OmDVq1aITY2Vr3NGVWPhk5A19b//pzys/lioYpVZmcamUyGsLAw5OXlIS0trZoj/Jfqlmh0dDRsbGwQExOj3s1FJpMhOjoaI0eOrJPj5GrS60iWi58xskQGJYQbN25Ey5YtERsbi5YtW8LPzw8rVqxQ78JBpjWw27//n/rrv72FZHkquzONt7e3Rn1zWLJkCXbt2oWQkBBkZmZizpw5mDBhAubMmYPMzEyEhIRg586diIuLM1uM5lKTXkeyXPyMkSUyKCGcMGECdu7ciQsXLmD58uUQQiA8PByenp4ICgrCli1bUFRUZKxY6REPJ4T/XATOnDdfLFS+R3emKYuqp11Vv7oplUrEx8dDoVBorY0JlPZ+JSQkQKFQID4+vs71YNSU19HUlEolUlNTsXXrVqSmpta594Eh+BkjS2WUvYxdXV3x6quv4vDhwzh9+jTeeecdnDx5EuPGjYOHhwemTp2KQ4cOGeNS9JD+XQHpQ68gbxtbLj8/P3h4eCAhIaHML3ilUomEhATI5XL4+flVc4SleEu0fDXldTQVLrdjOH7GyFIZJSF8mL29PRwcHGBnZ6feuu6rr77CgAED0KNHD/z111/GvmSd5Vxfcxwh1yO0XKqdaXJzcxEWFqb1i/PhnWnCw8PNNpict0TLV1NeR1PguDfj4GeMLJXeO5Xocvv2bWzZsgVJSUnYv38/pFIphg8fjujoaDz11FOQSqXYtm0b3njjDTz//PNIT083xmUJpbeNfzlR+v+pv5SOI+R6hJapqjvTVCfeEq1YTXgdTeHhcW+P3uqMjIxEWFgYEhMTERcXh6ioKDNGatn4GSOLZcgaN9u3bxdjxowR9vb2QiKRiJ49e4qPP/5YXLlyRWf9VatWCZlMZsglzcbS1iFU+eag5nqEp3LMHRGVp6ioSMTGxgq5XC4AqP/J5XIRGxtr9jXIioqKhIeHh1AoFGXGUlRUJBQKhZDL5WaP11ws/XU0Nr4vjIfPJVUXffMWg24Zjxw5Eunp6Zg5cyZOnDiB9PR0vPLKK2jUqJHO+p07d8bEiRMNuSQ9ol8XzXGEvG1s2WQyGaKiopCTk4OUlBQkJycjJSUFOTk5iIqKMvstxrp8S1Qflv46GlttH/dWnZNk+BkjS2XQLeMffvgBAwcOrHT9nj17omfPnoZckh7RwBF4rA3w8/8PzUz9BXhxpHljoorJZDK9PjvVqa7eEq0KfV5HfbentCS1ddybuRaH5meMLJFBCaGl/kKrawZ2+zchTPmZ4wjJMDKZDNu2bUNcXBzi4+MRHR2tPiaXyxEbG4uIiIgak8yYW23YkaI2jnt7dE/qmJgYjT2po6OjkZ6ebpI9qfkZI0tk0NZ1dYmlbV33sF2HgMAZ//78dzLQysts4VAtUpN7tSzBo0lHWFiYRtKh6gkyRdJhTLVxy77Y2FhER0frnCSjVCrVk2RiY2NNOkmGnzEyFb3zFpOOaKxFLHVSiRBC3LwthLTHvxNLViabOyIiEkKImJgYAUCEhIRoTQ4oKioSISEhAoCIjY01U4SVV9Fjee6552rMY+HEDqoLqnVSCVkGJ0egW5t/f+YC1UTmV9t2pIiMjERgYCASExPh6+uL2NhY9TqEvr6+2LBhQ40Z91bbJ8kQVQUTwloioPu//69aj5CIzKe2JR2qcW+qHUmio6MxadIkzJ07V72DiaXf+laprZNkiAxhlIWpyfwGdgPeTSz9//yrwKkcoHVzs4ZEVKfVxqRDtdxOREREjR73VhsnyRAZyqJ7CAsLCxEREQFPT0/Y29ujV69e2LNnj97tDB06FBKJBK+++qoJorQMfp0BK6t/f+Z6hFSW6lxzrTpY6uOpzUmHarmdUaNGYeDAgTUqGQS4JzWRLhadEE6ZMgXLli3DxIkTsXz5clhZWWHEiBE4dOhQpdvYunUrfvzxRxNGaRk4jpAqorqtp1AoEBAQgODgYAQEBMDLy0t9G7AmMeXjMUaSyaTDcnFxaCIdTDzJpcrS09MFALF06VJ1WUFBgfDx8RF9+vSpVBsFBQWiefPm6tlxr7zySpXjseRZxioRH/4709j9cSFKSswdEVmKoqIiMWLECAFAKBQKERMTI5KSkkRMTIxQKBQCgAgMDKwxsylN9XiKiopETEyM8PDw0NqSLiYmRu/2atPM3NqmqKhIBAYGaryHNm7cKObPn18jPxNEj9I3b7HYhPDNN98UVlZW4ubNmxrlixYtEgBEbm5uhW2oPtj37t2rEwnht2ma+xqfOGvuiMhS1KblT4QwzeMxRZLJpMOy1bU9qaluqTUJ4ZAhQ0Tbtm21yvfu3SsAiK+//rrc83NycoS9vb34/PPPhRBCr4Tw4sWLIiMjQ+Pf9u3bLT4hvHVHCKue/yaE8ZvNHRFZgtq25pqpHo+pkmYmHZavqKhIpKSkiOTkZJGSksLXhGqFWrMOYV5eHuRyuVa5quzChQvlnv/GG2+ga9euGD9+vN7Xjo+PR4cOHTT+BQUF6d1OdatfD+jR7t+fa9vEEkudPGDpatvyJ6Z4PKZcM1A1MzcnJwcpKSlITk5GSkoKcnJyEBUVxfFpFqCmT5IhMgaLXXamoKAAtra2WuV2dnbq42VRfemmp6dX6drh4eEYM2aMRllmZmaNSAoHdgOO/Fn6/6r1CGv6vsa1YS9Yc6pty5+Y4vGoksyYmJgKk8zo6GikpaXpvZe7KukgIrJEFpsQ2tvbo7CwUKv8/v376uO6PHjwANOnT8dzzz2HHj16VOnabm5ucHNzq9K55jawG7BkXen/X7oGnDgLtPM2a0gGMecG9LVFbVv+xBSPpyYmzdwDl4iMyWJvGcvlcuTl5WmVq8o8PT11npeYmIi///4bL730ErKzs9X/AOD27dvIzs7GvXv3TBa3ufl1Bqxr0XqES5Yswa5duxASEoLMzEzMmTMHEyZMwJw5c5CZmYmQkBDs3LkTcXFx5g7VYtW25U9M8XhqUtJc25YPIiLLYLEJYZcuXXDq1CncunVLo1x1G7hLly46z8vNzYVSqYSfnx9atGih/geUJostWrTA7t27TRq7OTk6AD3a//tzTU4Ia9tesOZS29ZcM8XjqSlJs6rHPDo6GjY2NoiJiVHvJyyTyRAdHY2RI0fys0BE+jPxJJcqO3LkiNY6hPfv3xe+vr6iV69e6rKcnBxx4sQJ9c8nTpwQ27Zt0/oHQIwYMUJs27ZNXLhwQe94asKyMyqzP/53pnHjITV3PcKUlBQBQMTExJRbTzU7NCUlpXoCq4Fq2/Inpng8NWHNwNq2fBARmU6tWXZGCCHGjBkjrK2txZtvvilWrlwp+vbtK6ytrcX+/fvVdQYMGCAqk9eiDqxDqPL9j5rrEb6/YneNXEohOTlZABBJSUnl1tu4caMAIJKTk6spspqpti1/YuzHY+lJc21bPoiITEvfvMViJ5UApbd458yZgw0bNuD69evo1KkTvvnmG/j7+5s7NIvWs50SUokUJaJ0MOHMOduBy/E1blZuTRrXVROolj+JiIioFZMRjP14ZDIZtm3bhri4OMTHxyM6Olp9TC6XIzY2FhEREWZ7rqpjJjQR1V0SIYQwdxA1wfHjx9GhQwdkZGSgffv2FZ9gJupZuVlvA46l45x6tMzFU+3WIyEhAbm5uQgMDKwRs3KVSiUUCgVsbGyQmZmpM16lUglfX18olUrk5ORY/GOimsESZ/Bu3boVwcHBSEpKwoQJE8qsl5SUhEmTJiE5ORmjRo2qxgiJyJLom7dY7KQSqhrVrNyOza+qy85eVuCdd2rerNzaNhmCag5LXKiYPeZEZErsIaykmtBD+HCP2srPsjD89X9HBDRxA6QSABC4cOEChACaNPEEYOmrVgtcvnwZ9+/fh5WVFRo42SOg0zl0dP0K//vfmhrV40lkCPaYE5E+9M1bLHoMIenn4TFG/R+zhswaUD4oPXb+kqqWBLBqAgA4d9EsYepJAsANsAGKAVy7CyT/6ILkM4sgt1OafVwXUXVR9ZhHR0cjLCxMaymmh3vMY2Nj+ZkgIr0wIaxFHt5toZ49MP5xYMMuMwdlIs4dN+DXZAk8XPlLj+qOyMhIpKenIzExEampqQgLC4O3tzeysrKwZs2/PeYRERHmDrXOs8RxqETlYUJYizw6xmjF28DwvsCFK5r19uzZg++/+w7Tpk2Dj69vdYdZZecvAe9/Vvr/N+7a4K0PgcQY88ZEVJ0sfSY0ce91qrk4hrCSatoYwto4xkgIIOgN4OsD/5Z9+yEwrK/5YiIyF/ZAWZ5H914PCwvT2HudY56pOnGWcR1W22flSiRAfCTgVO/fspcWAbfvmi8mInOxxJnQdR33XqeajD2ElVQTegiB0qRv5MiR2Llzp/ovVF1jjGryX6irtwFTF/7786tjgY/eMl88RJaOvYmmV9vv0FDNwx7COk41xig2NhZKpRLR0dGYNGkS5s6dC6WydFZuTU4GASAsCBjY7d+fP9kMHDpmrmiILJfqM69QKBAQEIDg4GAEBATAy8tL/R1RmymVSqSmpmLr1q1ITU016eNVrfIQFhZW4U4yeXl5SEtLM1ksRFXBSSW1UG3bouxREgmwOgroOB64X1g6tjAsFjj2GWBna+7oiCzDo+PZYmJiNMazRUdHIz09vcb/gaiLOSZ2PLzKQ3m8vb016hNZCiaEtZhqjFFt5NsMiH0ZeHN56c9/5wAL1gALws0bF5GleHg826NrFkZGRiIsLAyJiYmIi4tDVFSUGSM1LnMlwtxJhmo6jiGspJoyhrAuefAA6P088MuJ0p+trYCfEoEurc0bF5G51eXxbLGxsYiOjtaZCCuVSnUiHBsba9REuC4/52SZOIaQ6gxra2DNnNJEEAAeFAOhsaWJIlFdVlfHsymVSsTHx0OhUGglg0DpY05ISIBCoUB8fLxRxxTW9lUeqPZjQkg1WudWQOSUf3/+9STw3w3F1TaQnMgS1dXxbOZOhCMjIxEYGIjExET4+voiNjYWSUlJiImJga+vLzZs2MCdZMhicQwh1XhRocCWfcDJ7NKfZ39cBBx/ESjMBMAdAqjuqavj2cydCHMnmdqnLi3ZxB5CqvFsbYCVsx8AKCktkNij+YA92LCx9C9zmUyG6OhojBw5kr2FVCf4+fnBw8MDCQkJZb7nlUolEhISIJfL4efnV80RmoYlJMKqVR5ycnKQkpKC5ORkpKSkICcnB1FRUbU2maht6uKSTUwIqVbYv2sxcOlj9c/ZV5vjrh13CKC6qa6OZ7OkRJg7ydRcqpnq0dHRsLGxQUxMjPrWf23uYOAs40riLGPLpZrdZ23jDGnHv5CbLwEAyKwBN1UHgBDIz8+HgIDcQ166mCHVKnJX4JUxwHMjACsrc0djfnVh1yJdKpplHBoaig0bNhh9ljHVHuaaqW5s+uYtTAgriQmh5UpNTUVAQABiYmLQc8gcDHvN3BGROXX0BZa8Cgz308z769JYIBWlUqkez5aXl6cul8vlCA8Pr5Xj2epqIkzGUZuWD+KyM1TnPDyQ/Ik+QOgzZg6IzOrPTCBwBjDoZeBoRt0cC6RSF8ez1YXtO8l0qjpTvTq3STQVzjKmGu/RgeQrZgNDegIXLmvW271nN77/7jtMCw+Hr49vdYdJJlSoBNZ8BWT9829Z6i9ArymAh+0R5P+yHgp3mxqxfZspejJr865FutT27TvNoSb0sBsjRn1nql+6dAmxsbHVuk2iyQiqlIyMDAFAZGRkmDsUekRRUZHw8PAQCoVCFBUVlVlHoVAIuVxeZh2q2QqLhPjoCyEaDxEC3TT/SbopxbRFD0T+lX/rFxUViZCQEAFAxMbGmi/wh+KJiYkRHh4eAoD6n1wuFzExMXzfklno+74sKioSKSkpIjk5WaSkpFTL+9aYMaakpAgAIiYmptxrxsTECACiV69eAoBQKBQiJiZGJCUliZiYGKFQKAQAERgYqNF+dT4/+uYtHENYSRxDaNk4kJxUbt0B/rsReG+jwL37mpOHHB2ANyYCfTqV/vzgwQM8//zzKC5+gMTEDbC2Nu1NE6kEaOYBtPAsXS5J5dH9d8PCwjR6MjnujcxBn/clULp/dnX3lBk7RgCVHkN47do13Llzp1KTTyIiIqr9+dE7bzFZalrLsIfQshUVFYnAwECNv9Q2btwo5s+fX+ZfalS7JX+VJqCIF9LuxVo9hub+J+0hRPOnhBgaLsS0xUIMm/y9QIMnxTPjIsTtO9q9GZbUk0l1h6oXLCQkRGcvm+p9OW/ePDFixAi9esosOcaK2nzuuecEAOHo6FipO1MeHh5i+PDh1f78sIfQRNhDaPnq4oxKKtvWrVsRHByMpR99jR9znsLWFHNHVDlSKaDwAFyc/p0lLUQJMv7MgBACHTt1hETC+YC1jbsLsPR1oJ23uSMppc9sW316yox5h8ZUMUZERFQ4U7137944cuQIYmJiMGfOnDJjVN29AlDtzw+XnTERJoQ1R00Y/Eym9/ByRHPmzMGRP4HZH5dONiGyRK7OQMoKoIMFzHl79PNTlnnz5mH+/Plwd3fHuXPnqnWZFlPGCKDcDoZWrVph3LhxSEpKwoQJE8q89vr16zFlyhS4urriwoUL1fr86Ju3cJYx1Tp1bUYl6fbwrhWRkZHo3VGGlJXAvfuA8kFpHaVSia5du0KpVCIjI8PkfzgUFgHZF4DT54DTuUDmP8DR36/hdK4ArBuZ9Npk+a7cAAaHA6krgbYtzBtLZWfbqpZXCQgIqHCZlujoaKSlpRnt+9nUMZY3Uz01NRVAxdsk7t+/HwDw1FNPVfvzoy8mhERUK6m2b4uOjkZYWJj6Vo2DXelxpVKJ0PBQ/JNzHLGxsXBtWD29yG4uQM8O//6cmvoHAgICEBn1LkaOexOnzwGZ54C7BZrnHf7xMNIOHcK48eOhaKaollipevx1Fth5qPT/L10rXUMzdSXQurn5YtJ3X+jKLtOiSuL0UdZdn+qIsawOhkf/4Cyr52/Hjh0AUGGSZ8jzYyxMCImo1oqMjER6ejoSExORmppa5q4VERERZotR9Yvls8SPERM9Az07lHFLadmzkJcosWHxTHAERO1SXAw8Px/YsKv05/yrQMDLwP5VQEsz5f6VTXh++OEHAKhwhr4qKVMlcZWhVCrLnZn7xhtvmC3Gsv7gfPi6oaGhuHLlCgCob0Mb49omY9QpLbUYZxkT1UxFRUUiNjZWyOVyrTXKYmNjLWLmeWVnNXKWce314IEQE97RnI3eZLgQmefMF5OxZ9vqsw5sUVFRpWYFz50716wxVrS6xfDhw822Tq6+eQsTwkpiQkhUs5ljwdzK4rJJJIQQSqUQYyM1k8JmI4Q484/5FnyuzPuyskmZPn/Q6LOcjLliVJ1b0R+c5vqDjwmhiTAhJCJTqgk9mWR6RUohgt/UTAqd+18TjZt0r/QONsZMHivzvjT2HzT67j519+7dao9RVzxlPefm+oOPCaGJMCEkoupgyT2ZVD2KlEIEvaGZFFp3yRZvzP6g3AWNTbn9YUXvS33/oDHm9nEpKSkmidGYzHFtLkxtIlyHkIiIqkuREugYdAqnLrZSl/k2K5193MRN92LK+m5/aIo1Wytqs6KJIpGRkdixYweCg4MrXOMvKSkJkyZNQnJyMkaNGmW0GE2pOq/NdQiJiIhqOAmUuPnrUNi5rsN92wAApcsRDXoZ+OgtwN5WhhdnrMHuQ1ewfFUK8m84Y9fekxg1fgbeX/Yu6tnL4FwfsLIqnW2vSh7j4uJMuq9ueevAPrrvcExMjEbSGh0djfT0dMyYMQNA5ZeT0XdmrjnXqrXkdXLZQ1hJ7CEkIqLqotqFY87chThy+W3sSde/jXr2QM/2QO+OQPe2DzD9hZ4oLsxD165d8e2331a6J9FYVNu4VbSF27x587BixYpKbUln7N09ahN98xZuiElERGRhVAsUt2nVHF+9BwzqoX8bdwuAlJ+BxWuB4Lescd71V+S7puHbk5PQIzARX3ydhYjIOZgwYQLmzJmDzMxMhISEYOfOnYiLizPq41EqlYiPj4dCodBKBoHSnrOEhAQoFAqsXLkSL730EnJzcxEWFqbeaeThtkJDQ5Gbm4vw8HAmg0bCW8ZEREQW5uFdOOztgB3vA+NnAzsOGtiwrTdg642f8oG+oYCtDdDaC7C2AgAZhFgHWadZmP+lwNYTAhKJxNCHAgC4ffs+8p2/gdzTE72fLyuBk0HpewR5Fy7gs99awqnXJCQevYnPu5+Eq6srbG1tUFhYiCtXrkJZ9DqcekVj6wkfbJtklBDN4uj60tv6loC3jCuJt4yJiKi6KJVKKBQKrdumd+4B94tK9+O+e08J/wGDca9AiZu37uLlaa9h8pQXoXwAFBQCf5wGjvwJ/PgncOGymR8Q6fQg3XQJIW8ZExER1XCqrdEevW3q6AC4OgOuDZSIiQpFXvZBzJw2DB4NLmPXlgXo1kaJ/l2Bx3sDs54DtrwLnP8WOPOVEvUvvwDk/xe+8kuwtTHv4yPLw1vGREREFqiye3G//fbbkEql5e6rO3d2KG7nbgAAhLxUgIjIOfj9VGkP4j+XNK97+PBhHDp0EOPHPwuFwjibKReXFGPFp59CamWFqVOnwkqq3S1WXFKMVatWoaS4BC9Pe1lnndrGSHfkjcPoKyEa0f3798Vbb70l5HK5sLOzEz179hS7d++u8LytW7eKxx9/XMjlcmFjYyOaNGkigoODxZ9//lnlWLgwNRERVbfKLmhs6fvqCsE9u6tbrdqpZPz48cLa2lrMmjVLrFy5UvTp00dYW1uLgwcPlnve/Pnzxbhx48SSJUtEQkKCWLBggfD29hb29vbi2LFjVYqFCSEREZlLZXawseR9dVXtc8/u6lNrdio5evQoevXqhaVLl2LWrFkAgPv376NDhw5wc3PD4cOH9Wrv4sWLaNq0KUJDQ7FixQq94+GkEiIiqgnK2w1DqVRi5MiR2Llzp3odQl23oU2xDqHq+nFxcYiPj0deXp66XC6XIzw8HBEREVxGxkhqzU4lW7ZsgdX/jzVQsbOzQ2hoKN5++22cO3cOzZo1q3R7bm5ucHBwwI0bN0wQLRERkWUobzcMmUyGbdu2qZOy6Oho9TG5XK7eBs9USZlMJkNUVBQiIiLMtn0c6WaxCeFvv/2GVq1awcnJSaO8Z8+eAIBjx45VmBDeuHEDSqUS+fn5+OCDD3Dr1i0MHjy4wmtfunQJly9rztHPzMzU8xEQERFZHktIyix5C7e6ymITwry8PMjlcq1yVdmFCxcqbKN37974+++/AQCOjo6IiopCaGhohefFx8dj/vz5ekZMRERUczApo4dZbEJYUFAAW1tbrXI7Ozv18YqsXbsWt27dwpkzZ7B27VoUFBSguLgYUmn5yy+Gh4djzJgxGmWZmZkICgqq/AMgIiIiqiEsNiG0t7dHYWGhVvn9+/fVxyvSp08f9f+PHz8ebdu2BQD897//Lfc8Nzc3uLm56RMuERERUY1lsTuVyOVyjRlIKqoyT09Pvdpr2LAhBg0ahKSkJKPER0RERFRbWGxC2KVLF5w6dQq3bt3SKE9PT1cf11dBQQFu3rxpjPCIiIiIag2LTQhHjx6N4uLSbWxUCgsLsXbtWvTq1Us9wzg3NxcnT57UOPfSpUf24QGQnZ2Nffv2oXv37qYNnIiIiKiGsdgxhL169cKYMWMwe/ZsXLp0Cb6+vli/fj2ys7OxZs0adb2QkBDs378fD6+v3bFjRwwePBhdunRBw4YNcfr0aaxZswZKpRJLliwxx8MhIiIislgWmxACQGJiIubMmYMNGzbg+vXr6NSpE7755hv4+/uXe960adOwc+dOfPfdd7h9+zbc3Nzw+OOP4+2330bHjh2rKXoiIiKimsFit66zNNy6joiIiGqKWrN1naVRLYHDHUuIiIjI0qnyFV1L+OnChLCSzp07BwBcnJqIiIhqjHPnzuGxxx6rsB5vGVfSjRs3sH//fjRr1kznDirGoNoNZfv27fD19TW4ninaNOe1a9vj4bXr1rVr2+PhtevWtWvb46kp1zZEYWEhzp07hwEDBsDZ2bnC+uwhrCRnZ2c888wz1XItX1/fSt3vr2w9U7Rpzmubok1em9euyW3y2rx2TW6T1zadyvQMqljsOoREREREVD2YEBIRERHVcUwIiYiIiOo4JoQWpHHjxpg7dy4aN25slHqmaNOc1zZFm7w2r12T2+S1ee2a3CavXfG1qxNnGRMRERHVcewhJCIiIqrjmBASERER1XFMCImIiIjqOCaERERERHUcE0IiIiKiOo4JoQUoLCxEREQEPD09YW9vj169emHPnj1a9e7cuYO5c+di2LBhcHFxgUQiwbp167Tq/fTTT3j11VfRvn171KtXDwqFAmPHjsWpU6c06h0/fhxjxoyBt7c3HBwc4OrqCn9/f+zYsaPCmBcuXAiJRIIOHTpolKempkIikej8d+TIEa12fv31Vzz99NNwcXGBg4MDOnTogA8//FCjzpQpU8psUyKR4Pz58+q6p0+fxvjx49G0aVM4ODigTZs2iImJwb179zTa/OWXXzBs2DA4OTmhfv36ePzxx3H48OFKPb937txBeHg4XF1d1TH07dsXly9f1qh39OhRvPjii5DL5ZBKpeq6j7ZZUlKCFStWoHXr1rCzs1PXGzVqFO7fv69R96OPPoKXlxdsbW3V9fr164fs7Gydcc6dOxdPPPEErKysIJFIMG7cOK16EydO1Pm8tmnTRqu96OhotG/fHtbW1pBIJHB0dMSgQYPw+++/q+uV91oNHTpUq83Ro0fD2dlZ/Ry1bt0aO3fu1Kj3008/wd/fX/24ra2t0apVKxw7dkyr3sSJE+Ho6AiJRAKpVAovLy+t9966devQsWNH2Nvbq2N79DNSUlKCdevWwd/fH46OjpBKpZBKpXB2dkZwcLDW5+mdd95BkyZN1M+NtbU1WrRogR9++EHrOVd9Rtu1a6d+3J07d9Zq88knn9T5PHp7e2u198orr8DT01P9Wtva2qJ3796Vfm369u2r1eawYcPg4OAAiUQCKysrNG7cGKtWrdKod/z4cXTt2hU2Njbqek2bNsXmzZu1HvfXX38NDw8P9WO2s7NDnz59tL5zvvjiC/j4+Gi8zx/9biopKcHChQvh6emp8Zw3b94cycnJGu2tXr0a3bt3V3++pFIp7Ozs0LNnT61rP/q9qGr7hRde0KhX1veSg4ODzjZHjx4NV1dX9WOXyWTo1KlTlT877733Hho1aqTRXocOHXR+f3/88cdo27YtbG1t4eTkBIlEgnbt2mnVO3z4MPr16wcHBwd4eHigT58+Or/nd+/ejdDQUHTo0AFWVlZo2LChVr179+7hk08+weOPPw65XI769etDLpfrbG/RokXo3bs3GjduDDs7O7Rs2RJ9+/bVWfdhN27cQL169SCRSKBQKDSODRw4sMznUlebRUVFWLRoEdq0aaN+zevXr49//vkHAJCdnV3u6/Piiy+q21J9p3fp0gWOjo5wd3dHq1atdF5bqVRi/vz58Pb2hq2tLby9vbFgwQI8ePCgzMdtMoLMbvz48cLa2lrMmjVLrFy5UvTp00dYW1uLgwcPatQ7e/asACAUCoUYOHCgACDWrl2r1V5wcLDw8PAQr732mli9erWIjY0V7u7uol69euLPP/9U19u5c6d44oknxLx588SqVavEBx98IPr37y8AiJUrV5YZ77lz54SDg4OoV6+eaN++vcaxlJQUAUBMnz5dbNiwQePf5cuXNep+//33wsbGRvTq1UssW7ZMrFq1SkRERIg333xTo97hw4e12kpMTBQODg6iXbt26nq5ubnC2dlZeHl5icWLF4uVK1eKKVOmCADi6aefVtf75ZdfhJ2dnWjZsqX473//K959913RvHlz4ejoWKnn9/DhwwKAsLa2Fr6+vgKAcHBwEJ07dxaFhYXqenPnzhXW1tbqugB0tnn79m31sQYNGohWrVoJAEIikYiBAweKkpISdd2JEycKAMLZ2Vm0bt1aABBOTk7C1dVVnD9/XqNd1fulYcOGQiqVCgBi7NixWo8nODhYABCNGjUSbdu2FQDEiy++KL7++mud7QEQHh4eAoB49tlnxeTJk8Xu3bvV9TZs2CCWLVum1SYA8e6772q0OXfuXAFA2Nvbqx93s2bNBACRnJysrqc65uvrKyZOnCh69+4tAAgrKyuN9/SIESOERCIRDRo0EOPHjxdDhgwREolESKVS8euvv6rrqWJq3LixcHd3FwC0PiOq18XFxUU4OjqKQYMGCT8/PyGRSIRMJtP6PHl7ewt7e3vRr18/MXnyZDFgwAD1875v3z6t59zDw0P069dP2NjYCADC0dFRq00vLy8BQAwdOlSEhoaK4OBg0aBBA2FnZ6dRLzg4WNjb2wuJRCL8/PzEM888I+rXry+sra01PssbNmwQPXr0EA0aNFC32adPHwFA2NjYaLTZuXNnAUA0b95cTJw4UQwfPlz9Pn7//fe13j/t2rUTEydOVH+HPPo9cu7cOeHk5CTs7e3FsGHDRFBQkLC3txf16tXTqjthwgQhkUiEXC4Xbm5uAoDWd5Pq9WnQoIEYNGiQeO6550TPnj3V116xYoW6vWnTponBgweL1q1bi6efflqMGDFC/fw8eu2HvxfHjBmjfn0erTd58mRhbW0tOnbsKEaOHCleeOEFMWnSJNGuXTudbXp6egqpVCr8/PzEuHHjhLe3twAgXn/9dXW9N954Q6s9T09PAUCMGjVKXe/DDz9Uv38DAwPF2LFj1fUevfZbb70lAIjRo0eLRYsWqR9zvXr1NN6Tv/32m7CzsxNdu3YVn376qXjttdfUn7FHv+cnT54s7OzsRN++fYWHh4eQSCRavw/+/PNPIZFIxJAhQ8S7774rFi9eLKysrNTfXw8bNWqUeOmll8T7778vEhISxNSpU9XfgW3bthVlef7559WPuVmzZhrHBgwYIJo2bar+nbF8+XJhY2Mj7OzstB5PUVGRGDJkiHBwcBAvvPCCsLGxETY2NsLJyUlkZGQIIYS4c+eOxu8gVXuq5/PLL79Ut/ef//xHABCTJk0SK1euFLNnzxYSiUQAEN7e3hrXHjt2rJBIJCI0NFR8+umnYvLkyerv4OrGhNDM0tPTBQCxdOlSdVlBQYHw8fERffr00ah7//59kZeXJ4QQ4qeffiozYUlLS9NITIQQ4tSpU8LW1lZMnDix3HgePHggOnfuLFq3bl1mnXHjxolBgwaJAQMGlJkQbt68udzr3Lx5U7i7u4uRI0eK4uLicuvqcvDgQQFALFy4UF22cOFCAUD9AVYJCQkRAMS1a9eEEKVJQ8OGDcWVK1fUdS5cuCDq1asnRowYIYQo//mdOnWqsLOzEzk5Oep6s2bN0voizs/PF9evXxd5eXnilVdeKTMhLCwsFCkpKVqvbVBQkAAg9uzZo66r6z2gSqoWL16s0e79+/fFn3/+KRo0aCBeeumlMhPCSZMmCXt7+wof98aNGwUAsXXr1nLrlRUnAHHu3DmNej4+PqJLly6ipKREXS8+Pl44Ojqqk/gLFy4IKysrMWHCBI1z58yZIwCIAQMGqMtGjhypfm1U1q5dKwCInj17qst27Nghbty4IYQQ6tfm0c9IYWGhSEtL0/o8zZ8/XwAQMplM4/Ok63O3detWAUB06dJFozwtLU2cO3dONGjQQMTExAgA4q233tL6jA4fPlw4ODhonKvrs6xqY+vWreXW0xVnaGioAKBVt2nTpqJbt24af5D8+uuvAoBo0qSJEKL0tbG2thbPPfecxjWWL1+uUU+I0qTM3t5e47XZs2ePACCaNm2q8Z2Tn58v7t27J4T49/V59LtJ9fo8SvV5eDRBeNTPP/8sAAi5XK7z++7ixYsar8+j9SZPnqyVVAmh+zt006ZNWq9PZb5rhfg36fHx8VGXtWzZUvTo0UPjtbl586aoV6+ecHJyUrf56Ouj+u5W/SH78B99w4cPF3K5XNy8eVNdt02bNgKA8PLy0ojp/PnzoqioSAghhFwuF3Z2dlq/Dy5fvqzxXay6tuqPydOnT5f5mMeNGyc6dOigfm/ooko4W7RoUWZC+HA85f3eiouLEzKZTKSnp5db79EYBw0aJJydnYVUKhUFBQVCCCGUSqWwt7cXo0eP1qir+sPLxcVFXX706FEBQMyZM0ej7TfeeENIJBLx+++/l3l9U+AtYzPbsmULrKysMHXqVHWZnZ0dQkND8eOPP+LcuXPqcltbW3h4eFTYZt++fWFjY6NR1rJlS7Rv3x4nTpwo91wrKys0a9YMN27c0Hn8wIED2LJlCz744IMK47h9+3aZ3d6fffYZLl68iIULF0IqleLu3bsoKSmpsM2Hz5dIJJgwYYK67NatWwAAd3d3jbqqW7aq5+TgwYMYMmQIGjVqpFFn4MCB2Lt3L+7cuVPutbdv346nnnpK4xZF+/bt0apVK3z55ZfqMnd3dzg7O1f4mtnY2GDgwIFa9bp16wYAGq+ZrveAq6srAGi9Zra2tli2bBlat26N4cOHl3l9KysrSKVSFBcXl/vYP/roI/Ts2RMjR46s8LV6OM6ioiIAQOvWrdG0aVONenfu3EGTJk0gkUjUZfb29nB0dIS9vT0A4Mcff0RxcTEmTpyoce706dMBAH/88Ye6LC0tTeu1mTJlCmxtbTWexyeffBINGjTQaO/Rz4iNjQ369u2r9XkaOXIkgNLX9+E2dX3u/P39AQB5eXka5X379kV0dDRat26NSZMmASjdveDRz6ibmxskEgmKi4vV729dn+WdO3dqvDZ3794t8zP/cJyFhYVITk7GwIEDteoqlUp4eHhovDZdu3aFtbW1egjGjz/+iAcPHmD8+PEa11B9Lq9evaouS05OxpNPPqnx2gwZMgStWrXC/fv3Nd6/7u7u6tdf5dHvJtXr86jg4GAA2p+HRzVv3hwA4ODgoLNuZGSkxuvj7Oyss97Dr42uOAFg2bJlWq9PRd+1QOnrs23bNjRq1Ejjs3nr1i31e0NFNfzF0dFR3ebDr8/D391ubm4ASm/Nq9rbs2cPJk2aBCcnJ3XdpKQkSKVS3Lx5UyMuT09PyGQyHDhwAPn5+WjYsKFW7K6urmjfvj0Azd8bqu+rsn4XqepGRUWpn19dQkJCAEBdrywPHjzAd999V+bvrZKSEixfvhwjR47E/fv3sWXLFixevLjcNlUxvvPOO7hx4wacnJxgZ2cHoPRzU1BQoP49pKr7/vvvAwCk0n/TroMHDwKA1udn/PjxEEJg06ZN5cZhbEwIzey3335Dq1at4OTkpFHes2dPANAaI1VVQghcvHhR/WF82N27d3HlyhVkZWXh/fffx7fffovBgwdr1SsuLsZrr72GsLAwdOzYsdzrPf/88+oPSUBAAH7++WeN43v37oWTkxPOnz+P1q1bw9HREU5OTpg2bZrWuLlHKZVKfPnll+jbt6/6Sx0oHTMCAKGhoTh27BjOnTuHTZs24dNPP8X06dNRr149AKVfso/+sgFKfzEUFRUhIyOjzGufP38ely5dQvfu3bWO9ezZE7/99lu5setD9SWs6zW7evUqrl27BgBYs2YNAGi9ZkePHsX69evxwQcfaPzi0OXevXtwcnJCQEAAAGDDhg1av4COHj2KHj164O2331Y/12+++aZGEqxLWloaAKBPnz5axwYOHIjvvvsOH330ES5cuKC+9s2bN/H66//X3pmHVVV1f/x77+UOXCYBARHEREFCUAaNwjRfI4FHMs2RokRKRVPzedRS82fmnMPzOpTTo+JESonmbKGmaK849VIOOYtphogMosy4fn/wnNM599x7oXJ4i/V5nvvHPWfdtfc+6+x91t177XXeB1BrLwAKmwnfhfOWbENE0Gg0KCsrs1pPa31ESm5uLoDaa2bJNnl5eTh58iQSExMBQOEIm7ONpfIF2zg5OcHFxQXDhw9Hbm6uKGdqGycnJ9jb26NFixbIycmx2p7du3ejqKgIb7zxhqJsqW1ycnJw/vx5DB8+HNXV1fDz8wMgt410HBHuSa1WC0BpG6msg4MD8vPzzY45Dx48EO1mbWyS6vv8888BwOwYdffuXVy7dg379u1Dv379AADXrl0z23fWrFmDKVOm4JdffgEAXLhwQSEntU2jRo2QkJCA2bNny+optc/YsWPh6OgIe3t7uLq6Yvfu3Vbbs3r1ahQVFaGwsFAmJ7XNuXPncPToUSQkJODu3bu4ffu2KCvYR6fTycZujUYDoDaWGgBOnz6N6upqtG/fXjbOh4WFwd7e3uyYLMg1a9ZM8UfInJxQtvAH0fS+FO7/YcOGoXv37mIsuTBuS0lLS0N2djbi4+MV8bRSLl68CKPRiNjYWOh0Onz55Zcgk5eznTt3Drdu3UJQUBB69eoFIkJERAROnjyJBw8eWG2PEP/ZqFEj8bywD2DNmjVYv349kpOT0atXL8ybNw82NjYy59nS2GY0GgH8bp8nxhOdj2QUtGnThrp27ao4fvbsWUUcjJS6luxMWb9+PQGgVatWKc4Jy4kASK1WU58+fcTlVSmfffYZOTk5UV5eHhEpp+SJapejevfuTatWraJt27bRrFmzyNXVlQwGgyyGq23btmQ0GsloNNLIkSMpPT1djFkZMGCA1bbs2LFDXFo0Zdq0aWRrayu2BwB99NFHMpng4GDy9/en6upq8VhFRQX5+PgQANq8ebPF6yscX7dunex7SkoKjRs3jgBQeXm5ol7WloxNEXQGBgaSo6MjFRYWKmT0er2oz87OjhYtWiQ7//DhQ3ruuecoPj6eiIi2bdtmccl4/Pjx9OGHH1JaWhpNnz5d1NuxY0eqqqoiot+XCl1dXcnDw4M+/PBDAkAtWrQglUpFe/bssdierl27EgD6/PPPFedu375NL7/8ssxe9vb29J///EeUOXXqFAGgadOmyX4rXG+9Xi+7boJtBIR7vy7bWOsjUqKioshgMFiUldpGiEuVypnaRojNHDBggEJWapuNGzeK8UUAaMWKFUSktM2SJUsoNTVVjFEbPXq0xbb07t2b9Ho9LVu2TFG2JdtI5aS2MR1HhHvTnG2kskJslRBiIKW+Y5NUDqiN2b127ZpV2whlm+oU7CMsqwqftm3byuSktjG9Tr179xZlpfYxHZsAeeyZpfa89tprsrLN2cbcNRLsExcXJxu7g4ODRXsSEX311VcEgDIzMxXjvJubG9nY2CjqKMhFRUVR8+bNLS6xSvVVVFSQ0WgkrVYrji0Cv/32m6wt3t7eFBgYqNBZWlpKzs7OpNfrKS8vTwxTMl0yTkpKoilTptC7775LRqORoqOjCaiNu5TqFMI67OzsSK1W08KFCyklJUWMyTVdtpW2Jzw8nHQ6naKOly5dorCwMFl7fH19qUOHDjLZ9PR0ceyRIvTHoKAgxfV8nLBD+JTx9fWl2NhYxfErV64QIA/elvJHHMKff/6ZHB0d6YUXXpA5QdLzGRkZtHbtWurevTv16tWLcnNzZTL5+fnk4uJC8+bNE4/VFWMhcOnSJbK1taXo6GjxmPCwSk5OlskKA+HFixct6ouPjyetViuLARRYv349RUdH04oVKyg9PZ2SkpJIpVLR4sWLRZmlS5cSABo4cCCdPXuWTp8+Tf379yetVit2TkvXNzMzkwBQWloaEcntIMS0mXPg/oxDaMnpJSI6cOAALViwgIDaTTCm8YOrV68mW1tb+uWXX4jIukNormxho8DGjRtl7QZAWVlZotzSpUupcePG1LFjR7P6iouLxaB8c+0uKSmh4cOH08CBA2n27Nnig6BJkyayGKOIiAiyt7en1atX07Vr12j58uWkUqnEDSPSOgq2Ifr93vf29q7TNtb6iIAQp2owGCzKHjhwgHbv3k0ffPABqdVq8vHxkcmZ2kZwCK3plLZHcGpSU1Nl7RZsI223jY0NRUZGmtVVXFxMBoOBoqKizLZdapuvvvqKZsyYQWq1mrRaLZ0/f16UE2wzY8YMWr9+PY0ZM0Z8mFqyjXTM8fPzIwB04cIFs+3t0aMHAbA4Nkn19enThwBQu3btzModOHCAli9fTkOHDiUfHx9q3bq1QqdgnwMHDlBGRgbNmzdPfDib02mu/A4dOoiyUvts2rRJbHd0dDTpdDrq0KGDWX1ff/01abVaMdZaWrbUNgsWLKAxY8aQt7c36fV6euWVV2SygmPSr18/unbtGu3evVu8hzQaDRERrVu3jgDQt99+qxjnPTw8RDsKSJ8H3bt3t+gQmj43Bg8eTIAyJpGoNt7RwcGBkpKSaOrUqRQSEkKtW7dW6Bw7diypVCoxftySQ2itfOnGDqHtAGjSpEnicWHjmjSuVqrvwoUL4nhlWsfc3Fzq168f6fV6GjhwIC1ZsoR8fHzI1taWAgICRLmysjJq3rw5eXh4UHp6OuXk5FBaWhq5urqSjY2NLG70ScAO4VPmcc8Q/vbbb+Tr60vNmjVT7EK1xCuvvKIIWE5OTqZWrVrJgtHr6xAS1e6k1ul04gOnTZs2BIAOHTokkzt06BABoLVr15rVU1JSQkajkeLi4hTnNm7cSLa2toqNC4mJiWQ0GmUO5MSJE0UHEAC1b9+ePvroIwJAW7dufaozhILT0alTJ6tyQtmffvopGQwG0ekVNuxMnjxZlP2jDuHy5ctJrVbTO++8IzveokULRbsHDRpk9h8/Ue3D1Vq7Y2JiRFsKOhcvXkwuLi6yut68eZM6duwo+8ft4OBAISEh5OTkJPu9YBvpvT9s2DCLthF2otfVRzZt2iSWW5esULanpyfp9XqrthECyxs1alQvnd7e3uKuRGm7BdtI2y380bFmGw8PD7PtkdpG0Onl5UWNGjWyahuNRkPjxo0jR0dH0mg0sg1DprO3RL/P9LZv31425ggIfYfI/NgksGnTJvG6WJMTuHz5MhkMBgoICBBlzdlHcNjNbeQwpbS0lNRqNTVt2lSUNbWPlKZNm5JKpRI3aEgR7LN582ZFe6S2Ebh79y65uLiQh4eHTPatt94SZ7QF+zRr1oxsbW3FviPMEL722muKcd7cDKH0eWDNIZTKzZkzh4DaXevmnhumz5jvv/9e/MMrtYVGoyF3d3dRzppDaKrz/PnzBIDc3d1FGaHttra2iuebnZ2dzG5SfZMnTyYAFBYWJmtPVVUVBQUFUVBQkKzsixcvkkqlosaNG8vqeObMGXFnOlC74rFw4UJyd3endu3aKdr0OOEYwqeMp6enIuAc+D0IvWnTpn9ad3FxMWJjY1FUVIS9e/fWW1efPn1w4sQJMSfapUuXsGLFCowaNQq3bt1CTk4OcnJyUF5ejqqqKuTk5IjxbJZo1qwZKisrxZgMoS6mG0CEYOfCwkKzer7++muUlpYqNhgAwJIlSxAaGqqI1+rRowdKS0tl8X0zZszA7du3cfjwYfz00084ceKEuFHC39/fYjs8PT0BKDcJCMdcXFyg1+st/r4uMjIy8PHHHwMABg4cWK/fuLu7IzQ0FKmpqQCAefPmobKyEv379xdtlZeXB6A25iknJ0eM47GETqeDq6uraFdL9hLKr6qqMhtvk5qaajYGCACuXr2KvXv3okePHrLj9vb2ePHFF8XYQwDw8vLCkSNHcOrUKfj5+cHZ2RlZWVm4ffu2aC+pbUzv/ZKSErO2KS4uxs6dOwHAah/JyMjAW2+9BUdHR2i1Wquy0rL37duHsLAwi7b56aefxHu5b9++qKysNGsbqc5vvvkGjRs3Nmsb03Y/88wzFm2zdu1aqNVqVFVVKdojtY1U57fffovOnTubtc3FixeRmZmJmzdvYs6cOeJmmIsXL9bZb4xGI06ePKnIw2iK6dgkkJGRgbfffhvdu3fHsmXLLMpJadmyJUJDQ1FRUSHKmus7Qh66Vq1a4cSJE1ZjjG1tbeHq6gp3d3dRp7W+ExwcDCKS5SIUSE1NhZOTE+Li4mTtsdRvXFxc8OKLL8rac+nSJaSmpmLOnDk4cOAA0tLScPToUTRt2hSVlZVo3rw5CgoKRPts377d7Div0WjEcd70eVBaWorq6mrF80Aqt2jRInzwwQd444034OHhoXhumHvGCBtXCgsLRdnRo0ejpqYGw4YNw/Hjx3HkyBGcPn0aQG083pEjR5Cfn29RpzDGS8sXNq08++yzinar1Wrk5+ebbffatWvh6+sLrVYr05eZmYkzZ87g3LlzsrK1Wi1sbW1x//59WdvbtGmDM2fO4MyZMzh8+DBu3bqFwYMHIz8/3+qz6LHwRN1PRsHYsWNJo9GIW/0FhFkiYVnJlLpmCMvKyqhTp05kNBpl8Vj1QViKPHbsGBH9/g/M2keaS8scvXv3JoPBIKaYGT9+PAHK/Gz79++XLYeZEhMTQ/b29vTgwQPFOX9/f4qIiFAcF1I+WItzIyLq0KEDeXt7U01NjdXr6+bmRn379iUiuR38/f3NzvYS1W+GMCsri+zs7Kht27Z/aGk5JSWFQkJCxHxd0jgzS5///ve/VnUuXbqUVCoVDRkyRDzXpEkT8V+4tGxhBsI0fdCtW7dIrVaLS36m7RHyOS5dulShMzY2ljw8PGTypve0MIs+YcIEUcbNzY1ef/11xb1vzjaCPiGPmCWysrLIaDSSo6Njnf3JXL/7q7Yx1Xnv3j2ztvH29laUbck2V69eJaA21s5cewTbLFq0SKHTnG1MEWwjHUek/UaKv7+/uGwsyEqRzhCajk1Ev/ebyMhIMVWNOTlzhISEiHkojx07Vi/7mMZ7SRFsI6QYEcqX9h0p7du3JwB09OhR2XGh7yQlJSnaY9pvpMTGxpKDg4MoW9+xu6ioSIz7rEu2vjr/yHOjvrJCbkxrHyEMqb46d+3a9Ujb88UXX9QpJ227OYQ6WcsH/Dhgh/Apk5WVRYA8D2F5eTm1atXKrHMjYM1hqa6uph49epCNjQ3t2rXLoo7bt28rjlVWVlJYWBjZ2tpSSUkJEdXmk9q6davi06ZNG/Lx8aGtW7fSTz/9REQkBiJLyc7OJq1WK0sOLQRam+aWi4+PJxsbG7NLZ3l5eWZzngnExcWRTqdTxCL17NmT1Gp1vZYDhVgTa9c3OTlZjAET5IRlL3ODNFHdDuG5c+fI1dWV2rRpIzrFpnJVVVWywHKh7P/7v/8jjUYjXpdTp04pbDVhwgQCajeKbN26VczBV1ZWRvfu3VPojI2NJUCeN+39998noDbOSJBbtGgROTo6ivkbpQjJqZcsWWK2PXl5eaRWq8Xk24LO+fPnk729PcXExIiypvd0TU0Nde/enYxGoyyv3ZAhQ0itVsvu/X379ilsI9XXvXt30eEwZxcXFxcxibGl/lRVVUV37txR9Ltjx46Ztc3mzZupQ4cOpNFoaMSIEQSAEhMTFbYpLCxU6BTuNaltpEmEBbk7d+6YtU11dbUYsjFz5kyz7cnLyyOVSiXGMgk6b9y4obCN6ThSU1NDsbGxpFKpyGAwiONIcnIyGQwG2Z9cwTbCEqYgK9Up9B1zY9Phw4fFfiP0DVM5od+Y1vPYsWOkVqvJxcVFlD116hSlpKTI+s7y5csJqN0UotPp6ObNm2K/MdUp2EZIUi7UU4hdkyZwF5w+tVqtaLfQd/bv369oj9BvIiMjZcvXN27cEPMQCrLmxu709HSyt7cnlUpFK1asEMfurl27krOzM33xxReirHDt3d3dxXHeVGd4eLi4UUP6PLhz5w5Nnz6dtFotBQUF0Zdffmn2uXH//n26fv26op5CQm0nJydRdseOHTR+/HjZJz4+noDaGODx48fTqVOnqLi4mG7evCnTt2XLFjG0oUmTJrJ6Pvfcc6RWq2nx4sWivLCpKCYmRtFuYcxYunSpoj1Cfst//etfsvKFWFR7e3vZM9OU0tJSCgsLI09PT9nY/CSwAfNUiYiIQN++fTFhwgTk5eWhVatWWLt2LXJycsTUDVI+++wzFBUViSk6duzYIS5pjBw5Ek5OThgzZgy2b9+OV199FQUFBdiwYYNMh5BXa+jQobh37x46d+4MLy8v5ObmIjU1FefPn8f8+fNhb28PoDY9QM+ePRV1EXI6Sc/1798ftra2iIyMhLu7O86dO4cVK1bAaDRi9uzZolxoaCiSkpKwevVqVFdX46WXXsLBgwfx1VdfYcKECWaX49LS0lBdXW12uRioTYGyZ88edOrUCSNGjICrqyt27tyJPXv24N133xV1ZmZmYurUqejWrRtcXV2RlZWFlJQUxMTEwMbGBtOnT7d6fSdOnIh169YhJCREfP3TggUL4OHhgdzcXBQXF8PJyQnXr1/H+vXrkZWVJVsSmjt3Lnbu3ImQkBCMHDkSarUa0dHRKCgoQFhYGGbOnAkA+Pzzz7Fz5064uLhg7ty5ICI0a9YMwcHBaNSokZgLbubMmeISb3FxMcLCwhAWFia7X4R8lsXFxeLyxMiRI1FYWIjQ0FAEBQXB0dFRTHWzZ88e+Pn54cyZM+jatSucnJwwYcIEpKSkIC4uDm3btgUATJw4EeXl5WjRooXYboF///vfcHBwEPMEml5LNzc3JCUlYeXKlWjZsiW8vLwA1OYVKy8vh5eXl6izffv2yM7ORnBwMDZu3IhRo0bhypUrGDp0KDIzM8V7urq6Gg8fPoTBYMCmTZuwZs0a7Nq1C97e3rLl4sGDB2P79u1o3bo1zp8/D6B2ORKovd+XLVuGkpIS0S7CPbtjxw7x1WDu7u7w8/NDQkIC7t+/D09PT1RXVyMwMFDMO5aZmQmDwSBeL8E2o0ePxokTJ/Dqq6+KaTPKy8tx//597NixAwkJCcjNzUXr1q1RWVmJoKAgbNy4ERMnTsSPP/6Itm3boqSkRGyPNC3IypUrkZqaigMHDqCsrAwdO3aU9ZMxY8bg7Nmz0Ov18PLyMjs+uLm5ITAwEGfPnoWrqyvS0tKwZs0a7Nu3Dw8ePBBzZAK16YTKy8sRGhoKBwcHHDlyRLTzjBkzxHFk4sSJWLVqFVq3bo0uXbrAYDBgz5490Ov1uHHjhmzMeeutt3D58mU0b95cfC1j06ZNkZ+fj/j4eNjb26OkpATdunVDWVkZQkNDMW7cOBQVFeHo0aO4desWRo4cKebka9asGVxdXaHT6RAQEIAHDx7gyJEjAICCggKx7LCwMEybNk02Ll64cAFAbcqa+fPnw8vLCzk5OQgNDYWzszNsbGzQsmVL/Prrrzh9+jTs7Oxw9epVWXtu3rwJnU6HuLg4REdHo7q6Gvv378fDhw8xZswYUU4Yk3/++Wc4OTnh+++/x3vvvScbk+3t7cV+4+LighdeeAEGgwH79+8XQwOkst999x3Ky8sREhKCqqoqfPHFF2L+T+nr1ubOnYvIyEjMnTsXQ4YMwc2bN7Fq1So4OzvDzc1NNs77+vpi+/btAGpziQphCcLycnBwMK5fv465c+fCxsYGw4YNQ0VFBSoqKlBTU4Oamhr4+voiODgY2dnZiIqKQv/+/REQEAC1Wo2TJ09iw4YN0Ov18PT0FMsODg5GXFyc7H49ePAgNm7cCCcnJzF/4MGDBxEfH4/4+Hi0atUKZWVl2Lp1K77//nt4enrCxcVF1p6UlBRERERg5syZYn7TX375BRqNBitXrhTHpp49e6KmpgbJycl4/vnnkZycLOZylOp75ZVXkJGRgUaNGqFbt2747bffsHjxYqjVall7AKBfv35o2rQpAgMDce/ePaxevRpXr17Frl274ODggCfKE3U/GbOUlZXR2LFjqUmTJqTX66lDhw60d+9es7LCq6zMfYQ0Cy+99JLVqWqBjRs3UlRUFHl4eJCNjQ05OztTVFQUbdu2rV71NhdEvHDhQnruuefIxcWFbGxsyNPTkxISEsxmpa+srKQpU6ZQ8+bNSavVUqtWrSzuqiaq3fXl7u5udRfmsWPHKDY2lpo0aUJarZb8/f1pxowZsqD6y5cvU7du3ahx48ak1+spICCAZs2aRRUVFfW6vkQke02UJbn6LDFcu3ZN9ko4a3IVFRX0/vvvyzbDWKsjUd33S2FhISUkJMherWdNp5eXV73khODtumSrqqrIxcWlTjnhNX113dP1vffrWnoionrZRZCtqKiwem1Mh9r61LOwsFB8bdujajdRbWhEfWQ7d+5cL7nk5GRxxgmoXYYODw83O47MmTNHZm+dTkedO3dWyAo79s19hDfT1GWfgQMHirZ5//33ycfHR3x1mlB2x44dFWWbjotOTk4E1M7gCgj9RtiBK+i0tbWll19+2azOjh07ytLeODs7y3bzCnKRkZEE1KaQsTQmV1VVUWJiYr2ue0pKCrVr147s7OzIwcGBXn75ZWrXrp3ZjR2HDx+myMhIMhgM5ObmRu+99x69+OKLClnh7T/Wrntd49/HH39MRLUz2UOGDKGAgACys7MjnU5Hfn5+NHr0aIqMjKxz46K5TSVXr16lvn370jPPPEMGg4GMRiOFh4fTsmXLLG6GPHXqFEVFRYnXydXVlfz8/BRye/fuJQBiqi9z+kpLS2nq1KkUGBgobt6Ji4uj8PBws29JCQgIIIPBQM7OztSjRw+LIT2PGxWRSZZGhmEYhmEYpkHBu4wZhmEYhmEaOOwQMgzDMAzDNHDYIWQYhmEYhmngsEPIMAzDMAzTwGGHkGEYhmEYpoHDDiHDMAzDMEwDhx1ChmEYhmGYBg47hAzDMAzDMA0cdggZhmEYhmEaOOwQMgzDMAzDNHDYIWQYpkHRpUsXdOnS5U/9VqVSYcqUKY+0Pk8alUqFESNGPO1qMAzzPwY7hAzD/K1QqVT1+hw8ePCp1C8nJ0esQ3p6uuL8lClToFKpkJ+f/xRqxzAMYx6bp10BhmGYP8L69etl39etW4eMjAzF8Weffdbs77/99tvHVjdTpk6ditdffx0qleqJlckwDPNnYIeQYZi/FQkJCbLvWVlZyMjIUBw3pbS0FEajETqd7nFWTyQkJATZ2dnYunUrXn/99SdS5v8K5eXl0Ol0UKt5EYph/i5wb2UY5h9Hly5dEBQUhFOnTqFz584wGo2YOHGieE4aQ1hZWYnJkycjPDwcTk5OsLOzQ6dOnfDdd9/9pToMGDAA/v7+mDp1KojIquwzzzyDxMREs+2Q1vXgwYNQqVT48ssv8cknn8DLywsODg7o06cPiouLUVFRgdGjR8Pd3R329vYYNGgQKioqzJaZmpqK1q1bw2AwIDw8HJmZmQqZX3/9FUlJSfDw8IBer0ebNm2wevVqmYxQp02bNmHSpEnw8vKC0WjEvXv36r5IDMP8z8AzhAzD/CO5e/cuYmNjMWDAACQkJMDDw8Os3L1797By5UrEx8dj8ODBKCkpwapVqxAdHY3jx48jJCTkT5Wv0WgwadIkvP322498lnDWrFmwtbXF+PHjcfnyZSxevBharRZqtRqFhYWYMmUKsrKysGbNGrRo0QKTJ0+W/f7QoUNIS0vDqFGjoNfrsWTJEsTExOD48eMICgoCANy+fRvPP/+8uAnFzc0Ne/bswTvvvIN79+5h9OjRMp3Tpk2DTqfD2LFjUVFR8cRmYhmGeTSwQ8gwzD+S3NxcLFu2DEOHDrUq5+zsjJycHJkDM3jwYAQEBGDx4sVYtWrVn67DG2+8gWnTpmHq1Kno1avXI4slrK6uxqFDh6DVagEAd+7cwaZNmxATE4Pdu3cDAIYPH47Lly9j9erVCofwzJkzOHnyJMLDwwHUzma2bt0akydPxpYtWwAAH330EWpqanD69Gm4uroCAJKTkxEfH48pU6Zg6NChsLW1FXWWl5fj5MmTsmMMw/x94CVjhmH+kej1egwaNKhOOY1GIzqDDx8+REFBAaqrq9G+fXv88MMPf6kOwizhjz/+iK+//vov6ZLy9ttvi84gAERERICIkJSUJJOLiIjAjRs3UF1dLTv+wgsviM4gAPj4+OC1117DN998g5qaGhAR0tPT8eqrr4KIkJ+fL36io6NRXFysuDYDBw5kZ5Bh/sawQ8gwzD8SLy+vei9brl27Fm3btoXBYICrqyvc3Nywa9cuFBcX/+V6vPnmm2jVqlW9Ygnri4+Pj+y7k5MTAKBZs2aK4w8fPlS0w8/PT6HT398fpaWluHPnDu7cuYOioiKsWLECbm5uso/gZOfl5cl+36JFi7/cLoZhnh68ZMwwzD+S+s5WbdiwAYmJiejZsyfGjRsHd3d3aDQazJo1C1euXPnL9RBmCRMTE7Ft2zazMpaWkmtqaqDRaMzqtFSWOf6oI/rw4UMAtTu6Bw4caFambdu2su88O8gwf2/YIWQYpkGzefNm+Pr6YsuWLTLH7OOPP35kZSQkJGD69On45JNP0KNHD8V5Z2dnFBUVKY5fv34dvr6+j6weApcuXVIcu3jxIoxGI9zc3AAADg4OqKmpQVRU1CMvn2GY/z14yZhhmAaNMKsmnUU7duwYjh49+kjLmDRpErKzs7F9+3bF+ZYtWyIrKwuVlZXisZ07d+LGjRuPrA5Sjh49KosBvHHjBrZt24Zu3bpBo9FAo9Ggd+/eSE9Px5kzZxS/v3PnzmOpF8MwTw+eIWQYpkETFxeHLVu2oFevXujevTuuXbuGZcuWITAwEPfv339k5bz55puYNm0asrOzFefeffddbN68GTExMejXrx+uXLmCDRs2oGXLlo+sfClBQUGIjo6WpZ0BgE8++USUmT17Nr777jtERERg8ODBCAwMREFBAX744Qfs27cPBQUFj6VuDMM8HXiGkGGYBk1iYiJmzpyJH3/8EaNGjcI333yDDRs2oH379o+0HBsbG0yaNMnsuejoaMyfPx8XL17E6NGjcfToUezcuRPe3t6PtA4CL730EhYsWID169dj8uTJcHFxwZ49e2RxgR4eHjh+/DgGDRqELVu2YMSIEVi4cCEKCgrw6aefPpZ6MQzz9FDRo9r2xjAMwzAMw/wt4RlChmEYhmGYBg47hAzDMAzDMA0cdggZhmEYhmEaOOwQMgzDMAzDNHDYIWQYhmEYhmngsEPIMAzDMAzTwGGHkGEYhmEYpoHDDiHDMAzDMEwDhx1ChmEYhmGYBg47hAzDMAzDMA0cdggZhmEYhmEaOOwQMgzDMAzDNHDYIWQYhmEYhmngsEPIMAzDMAzTwPl/ExnDZ7lagvUAAAAASUVORK5CYII=",
- "text/plain": [
- ""
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "import matplotlib.pyplot as plt\n",
- "fig, ax = plt.subplots(figsize=(6,4), dpi=120)\n",
- "\n",
- "ax.plot(df.y1, ls='None', marker='o', mfc='None', mec='k', label='Observed')\n",
- "\n",
- "best_to_trial = np.minimum.accumulate(df.y1.values)\n",
- "ax.plot(best_to_trial, color='#0033FF', lw=2, label='Best to Trial')\n",
- "\n",
- "plt.xticks(range(len(df)))\n",
- "plt.xlabel('Trial Number')\n",
- "plt.ylabel('y1 value (Lower is Better)')\n",
- "plt.title('Advanced Optimization, Ax')\n",
- "plt.legend()\n",
- "plt.show()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "metadata": {},
- "outputs": [
- {
- "name": "stderr",
- "output_type": "stream",
- "text": [
- "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:36: AxParameterWarning:\n",
- "\n",
- "`is_ordered` is not specified for `ChoiceParameter` \"c1\". Defaulting to `True` since there are exactly two choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
- "\n",
- "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:36: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c1\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:37: AxParameterWarning:\n",
- "\n",
- "`is_ordered` is not specified for `ChoiceParameter` \"c2\". Defaulting to `True` since there are exactly two choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
- "\n",
- "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:37: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c2\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:38: AxParameterWarning:\n",
- "\n",
- "`is_ordered` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` since the parameter is a string with more than 2 choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
- "\n",
- "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:38: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"c3\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:39: AxParameterWarning:\n",
- "\n",
- "`is_ordered` is not specified for `ChoiceParameter` \"Task\". Defaulting to `True` since there are exactly two choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
- "\n",
- "C:\\Users\\MF\\AppData\\Local\\Temp\\ipykernel_22304\\2118524986.py:39: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"Task\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[WARNING 09-08 22:00:07] ax.service.ax_client: Random seed set to 42. Note that this setting only affects the Sobol quasi-random generator and BoTorch-powered Bayesian optimization models. For the latter models, setting random seed to the same number for two optimizations will make the generated trials similar, but not exactly the same, and over time the trials will diverge more.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x1. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x2. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x3. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x4. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x5. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x6. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x7. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x8. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x9. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x10. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x11. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x12. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x13. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x14. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x15. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x16. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x17. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x18. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x19. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.FLOAT for parameter x20. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Inferred value type of ParameterType.STRING for parameter Task. If that is not the expected value type, you can explicitly specify 'value_type' ('int', 'float', 'bool' or 'str') in parameter dict.\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`is_ordered` is not specified for `ChoiceParameter` \"Task\". Defaulting to `True` since there are exactly two choices.. To override this behavior (or avoid this warning), specify `is_ordered` during `ChoiceParameter` construction. Note that choice parameters with exactly 2 choices are always considered ordered and that the user-supplied `is_ordered` has no effect in this particular case.\n",
- "\n",
- "c:\\Users\\MF\\anaconda3\\envs\\BayBE\\lib\\site-packages\\ax\\service\\utils\\instantiation.py:244: AxParameterWarning:\n",
- "\n",
- "`sort_values` is not specified for `ChoiceParameter` \"Task\". Defaulting to `False` for parameters of `ParameterType` STRING. To override this behavior (or avoid this warning), specify `sort_values` during `ChoiceParameter` construction.\n",
- "\n",
- "[INFO 09-08 22:00:07] ax.service.utils.instantiation: Created search space: SearchSpace(parameters=[RangeParameter(name='x1', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x2', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x3', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x4', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x5', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x6', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x7', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x8', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x9', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x10', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x11', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x12', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x13', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x14', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x15', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x16', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x17', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x18', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x19', parameter_type=FLOAT, range=[0.0, 1.0]), RangeParameter(name='x20', parameter_type=FLOAT, range=[0.0, 1.0]), ChoiceParameter(name='Task', parameter_type=STRING, values=['y1', 'y2'], is_ordered=True, is_task=True, sort_values=False, target_value='y2')], parameter_constraints=[OrderConstraint(x19 <= x20), ParameterConstraint(1.0*x15 + 1.0*x6 <= 1.0)]).\n"
- ]
- }
- ],
- "source": [
- "import numpy as np\n",
- "from ax.core.observation import ObservationFeatures\n",
- "from ax.modelbridge.generation_strategy import GenerationStep, GenerationStrategy\n",
- "from ax.modelbridge.registry import Models\n",
- "from ax.modelbridge.transforms.task_encode import TaskEncode\n",
- "from ax.modelbridge.transforms.unit_x import UnitX\n",
- "from ax.service.ax_client import AxClient, ObjectiveProperties\n",
- "\n",
- "from ax import SearchSpace, ParameterType, RangeParameter, ChoiceParameter\n",
- "from ax.modelbridge.transforms.unit_x import UnitX\n",
- "from ax.modelbridge.transforms.task_encode import TaskEncode\n",
- "\n",
- "# Define the search space\n",
- "search_space = SearchSpace(\n",
- " parameters=[\n",
- " RangeParameter(name=\"x1\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x2\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x3\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x4\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x5\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x6\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x7\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x8\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x9\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x10\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x11\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x12\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x13\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x14\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x15\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x16\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x17\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x18\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x19\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " RangeParameter(name=\"x20\", parameter_type=ParameterType.FLOAT, lower=0.0, upper=1.0),\n",
- " ChoiceParameter(name=\"c1\", parameter_type=ParameterType.STRING, values=[\"c1_0\", \"c1_1\"]),\n",
- " ChoiceParameter(name=\"c2\", parameter_type=ParameterType.STRING, values=[\"c2_0\", \"c2_1\"]),\n",
- " ChoiceParameter(name=\"c3\", parameter_type=ParameterType.STRING, values=[\"c3_0\", \"c3_1\", \"c3_2\"]),\n",
- " ChoiceParameter(\n",
- " name=\"Task\", \n",
- " parameter_type=ParameterType.STRING, \n",
- " values=[\"y1\", \"y2\"], \n",
- " is_task=True, \n",
- " target_value=\"y2\" # Specify the target value\n",
- " ),\n",
- " ]\n",
- ")\n",
- "\n",
- "# Create the transforms\n",
- "transforms = [TaskEncode, UnitX]\n",
- "\n",
- "# Generation strategy with the transforms\n",
- "gs = GenerationStrategy(\n",
- " name=\"MultiTaskOp\", \n",
- " steps=[\n",
- " GenerationStep(\n",
- " model=Models.SOBOL, \n",
- " num_trials=5,\n",
- " model_kwargs={\"deduplicate\": True, \"transforms\": transforms},\n",
- " ),\n",
- " GenerationStep(\n",
- " model=Models.BOTORCH_MODULAR,\n",
- " num_trials=-1, \n",
- " model_kwargs={\"transforms\": transforms},\n",
- " ),\n",
- " ],\n",
- ")\n",
- "\n",
- "# Create the Ax client with the generation strategy\n",
- "ax_client = AxClient(generation_strategy=gs, random_seed=42, verbose_logging=False)\n",
- "\n",
- "# Create the experiment\n",
- "ax_client.create_experiment(\n",
- " name=\"MultiTaskOp\", \n",
- " parameters=[\n",
- " {\"name\": \"x1\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x2\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x3\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x4\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x5\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x6\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x7\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x8\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x9\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x10\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x11\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x12\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x13\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x14\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x15\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x16\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x17\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x18\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x19\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " {\"name\": \"x20\", \"type\": \"range\", \"bounds\": [0.0, 1.0]},\n",
- " # Add all other parameters similarly...\n",
- " {\"name\": \"Task\", \"type\": \"choice\", \"values\": [\"y1\", \"y2\"], \"is_task\": True, \"target_value\": \"y2\"},\n",
- " ],\n",
- " parameter_constraints=[\n",
- " \"x19 <= x20\",\n",
- " \"x6 + x15 <= 1.0\",\n",
- " ],\n",
- " objectives={\n",
- " \"Objective\": ObjectiveProperties(minimize=False),\n",
- " },\n",
- ")\n",
- " "
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": []
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "BayBE",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 3
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython3",
- "version": "3.10.14"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}