Upgrade to python 3.11 and TensorFlow 2.15.X (#1170)

* Updating to py 3.11 and tf 2.15 / 2.13
* Fix python version 3.11 in CI
* Removed deprecated padding in ui and used modern form of package versioning in setup.
* Fix telemetry test after paho upgrade

.github/workflows/python-package-conda.yml

@@ -18,10 +18,10 @@ jobs:
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
-      - name: Create python 3.9 conda env
+      - name: Create python 3.11 conda env
         uses: conda-incubator/setup-miniconda@v3
         with:
-          python-version: 3.9
+          python-version: 3.11
           mamba-version: "*"
           activate-environment: donkey
           auto-activate-base: false

donkeycar/__init__.py

@@ -3,7 +3,7 @@
 from pyfiglet import Figlet
 import logging
 
-__version__ = '5.1.dev0'
+__version__ = '5.1.dev1'
 
 logging.basicConfig(level=os.environ.get('LOGLEVEL', 'INFO').upper())
 
@@ -13,8 +13,8 @@
 print(f.renderText('Donkey Car'))
 print(f'using donkey v{__version__} ...')
 
-if sys.version_info.major < 3 or sys.version_info.minor < 8:
-    msg = f'Donkey Requires Python 3.8 or greater. You are using {sys.version}'
+if sys.version_info.major < 3 or sys.version_info.minor < 11:
+    msg = f'Donkey Requires Python 3.11 or greater. You are using {sys.version}'
     raise ValueError(msg)
 
 # The default recursion limits in CPython are too small.

donkeycar/management/ui.kv

@@ -104,7 +104,7 @@
         valign: 'middle'
         font_size: 14 if platform == 'linux' else 28
         size_hint_x: 0.8
-        padding_x: 10
+        padding: 10, 0
         canvas.before:
             Color:
                 rgba: 0.14, 0.15, 0.22, 1

donkeycar/parts/pytorch/torch_train.py

@@ -46,8 +46,8 @@ def train(cfg, tub_paths, model_output_path, model_type, checkpoint_path=None):
 
     if cfg.PRINT_MODEL_SUMMARY:
         summarize(model)
-    trainer = pl.Trainer(gpus=gpus, logger=logger, max_epochs=cfg.MAX_EPOCHS,
-                         default_root_dir=output_dir)
+    trainer = pl.Trainer(accelerator='cpu', logger=logger,
+                         max_epochs=cfg.MAX_EPOCHS, default_root_dir=output_dir)
 
     data_module = TorchTubDataModule(cfg, tub_paths)
     trainer.fit(model, data_module)

donkeycar/parts/telemetry.py

@@ -14,6 +14,7 @@
 import numpy as np
 from logging import StreamHandler
 from paho.mqtt.client import Client as MQTTClient
+from paho.mqtt.enums import CallbackAPIVersion
 
 logger = logging.getLogger()
 
@@ -40,7 +41,7 @@ def __init__(self, cfg):
         self._mqtt_broker = os.environ.get('DONKEY_MQTT_BROKER', cfg.TELEMETRY_MQTT_BROKER_HOST)  # 'iot.eclipse.org'
         self._topic = cfg.TELEMETRY_MQTT_TOPIC_TEMPLATE % self._donkey_name
         self._use_json_format = cfg.TELEMETRY_MQTT_JSON_ENABLE
-        self._mqtt_client = MQTTClient()
+        self._mqtt_client = MQTTClient(callback_api_version=CallbackAPIVersion.VERSION2)
         self._mqtt_client.connect(self._mqtt_broker, cfg.TELEMETRY_MQTT_BROKER_PORT)
         self._mqtt_client.loop_start()
         self._on = True

donkeycar/tests/test_telemetry.py

@@ -3,9 +3,10 @@
 import time
 from unittest import mock
 from paho.mqtt.client import Client
+from paho.mqtt.enums import CallbackAPIVersion
+
 import donkeycar.templates.cfg_complete as cfg
 from donkeycar.parts.telemetry import MqttTelemetry
-import pytest
 from random import randint
 
 
@@ -16,11 +17,8 @@ def test_mqtt_telemetry():
     cfg.TELEMETRY_MQTT_JSON_ENABLE = True
 
     # Create receiver
-    sub = Client(clean_session=True)
-
-    # def on_message(client, userdata, message):
-    #     data = message.payload
-    #     print(message)
+    sub = Client(callback_api_version=CallbackAPIVersion.VERSION2,
+                 clean_session=True)
 
     on_message_mock = mock.Mock()
     sub.on_message = on_message_mock

donkeycar/tests/test_torch.py

@@ -109,7 +109,7 @@ def test_training_pipeline(config: Config, model_type: str, car_dir: str) \
         gpus = 0
 
     # Overfit the data
-    trainer = pl.Trainer(gpus=gpus, overfit_batches=2, max_epochs=30)
+    trainer = pl.Trainer(accelerator='cpu', overfit_batches=2, max_epochs=30)
     trainer.fit(model, data_module)
     final_loss = model.loss_history[-1]
     assert final_loss < 0.35, \

setup.cfg

@@ -17,14 +17,13 @@ classifiers =
     # Indicate who your project is intended for
     Intended Audience :: Developers
     Topic :: Scientific/Engineering :: Artificial Intelligence
-    Programming Language :: Python :: 3.8
-    Programming Language :: Python :: 3.9
+    Programming Language :: Python :: 3.11
 
 [options]
 packages = find_namespace:
 zip_safe = True
 include_package_data = True
-python_requires = >=3.8,<4
+python_requires = >=3.11.0,<3.12
 install_requires =
     numpy
     pillow
@@ -35,7 +34,6 @@ install_requires =
     paho-mqtt
     simple_pid
     progress
-    typing_extensions
     pyfiglet
     psutil
     pynmea2
@@ -51,32 +49,32 @@ pi =
     adafruit-circuitpython-ssd1306
     adafruit-circuitpython-rplidar
     RPi.GPIO
-    tensorflow-aarch64==2.9.3
+    tensorflow-aarch64==2.15.*
     opencv-contrib-python
 
 nano =
     Adafruit_PCA9685
     adafruit-circuitpython-ssd1306
     adafruit-circuitpython-rplidar
     Jetson.GPIO
-    numpy==1.23
-    matplotlib==3.7
-    kivy==2.1
+    numpy==1.23.*
+    matplotlib==3.7.*
+    kivy
     plotly
-    pandas==2.0
+    pandas==2.0.*
 
 pc =
-    tensorflow==2.9
+    tensorflow==2.15.*
     matplotlib
-    kivy==2.1
+    kivy
     pandas
     plotly
     albumentations
 
 macos =
-    tensorflow-macos==2.9
+    tensorflow-macos==2.15.*
     matplotlib
-    kivy==2.1
+    kivy
     pandas
     plotly
     albumentations
@@ -88,8 +86,9 @@ dev =
     mypy
 
 torch =
-    pytorch
-    torchvision==0.12
+    torch
+    pytorch-lightning
+    torchvision
     torchaudio
     fastai