From 5409c32466cfac7e82769d2bf4f587dcd3fbb5e9 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Tue, 18 Jul 2023 15:36:56 +0200
Subject: [PATCH 01/76] Used proper torchmetric parameter order and replaced
 own PSNR implementation with torchmetric PSNR

- I replaced the self-implemented PSNR computation with the one provided by torchmetric.
- The ordering of torchmetric function call arguments is actually predictions ("preds") and then target ("target"), not the other way around.
---
 GANDLF/metrics/synthesis.py | 17 +++++++----------
 1 file changed, 7 insertions(+), 10 deletions(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 3321b121a..258a63c42 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -8,6 +8,7 @@
     MeanSquaredError,
     MeanSquaredLogError,
     MeanAbsoluteError,
+    PeakSignalNoiseRatio,
 )
 from GANDLF.utils import get_image_from_tensor
 
@@ -25,7 +26,7 @@ def structural_similarity_index(target, prediction, mask=None) -> torch.Tensor:
         torch.Tensor: The structural similarity index.
     """
     ssim = StructuralSimilarityIndexMeasure(return_full_image=True)
-    _, ssim_idx_full_image = ssim(target, prediction)
+    _, ssim_idx_full_image = ssim(preds=prediction, target=target)
     mask = torch.ones_like(ssim_idx_full_image) if mask is None else mask
     try:
         ssim_idx = ssim_idx_full_image[mask]
@@ -45,7 +46,7 @@ def mean_squared_error(target, prediction) -> torch.Tensor:
         prediction (torch.Tensor): The prediction tensor.
     """
     mse = MeanSquaredError()
-    return mse(target, prediction)
+    return mse(preds=prediction, target=target)
 
 
 def peak_signal_noise_ratio(target, prediction) -> torch.Tensor:
@@ -56,12 +57,8 @@ def peak_signal_noise_ratio(target, prediction) -> torch.Tensor:
         target (torch.Tensor): The target tensor.
         prediction (torch.Tensor): The prediction tensor.
     """
-    mse = mean_squared_error(target, prediction)
-    return (
-        10.0
-        * torch.log10((torch.max(target) - torch.min(target)) ** 2)
-        / (mse + sys.float_info.epsilon)
-    )
+    psnr = PeakSignalNoiseRatio()
+    return psnr(preds=prediction, target=target)
 
 
 def mean_squared_log_error(target, prediction) -> torch.Tensor:
@@ -73,7 +70,7 @@ def mean_squared_log_error(target, prediction) -> torch.Tensor:
         prediction (torch.Tensor): The prediction tensor.
     """
     mle = MeanSquaredLogError()
-    return mle(target, prediction)
+    return mle(preds=prediction, target=target)
 
 
 def mean_absolute_error(target, prediction) -> torch.Tensor:
@@ -85,7 +82,7 @@ def mean_absolute_error(target, prediction) -> torch.Tensor:
         prediction (torch.Tensor): The prediction tensor.
     """
     mae = MeanAbsoluteError()
-    return mae(target, prediction)
+    return mae(preds=prediction, target=target)
 
 
 def _get_ncc_image(target, prediction) -> sitk.Image:

From 00ea9c5368bed035fc53709758d620b80bee91ba Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Fri, 21 Jul 2023 20:43:05 +0200
Subject: [PATCH 02/76] Added peak_signal_noise_ratio_eps as dicussed

peak_signal_noise_ratio_eps with the initial PSNR implementation (using range and epsilon)
---
 GANDLF/metrics/synthesis.py | 18 ++++++++++++++++++
 1 file changed, 18 insertions(+)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 258a63c42..3ded3867a 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -61,6 +61,24 @@ def peak_signal_noise_ratio(target, prediction) -> torch.Tensor:
     return psnr(preds=prediction, target=target)
 
 
+def peak_signal_noise_ratio_eps(target, prediction) -> torch.Tensor:
+    """
+    Computes the peak signal to noise ratio between the target and prediction. Uses a small epsilon in the denominator
+    of the fraction to avoid infinity as output. Also, operates on the data range instead of the maximum. This version
+    of PSNR is potentially more robust than the original formular.
+    
+    Args:
+        target (torch.Tensor): The target tensor.
+        prediction (torch.Tensor): The prediction tensor.
+    """
+    mse = mean_squared_error(target, prediction)
+    return (
+        10.0
+        * torch.log10((torch.max(target) - torch.min(target)) ** 2)
+        / (mse + sys.float_info.epsilon)
+    )
+
+
 def mean_squared_log_error(target, prediction) -> torch.Tensor:
     """
     Computes the mean squared log error between the target and prediction.

From 960e47a316c623120c0168a93aeb8849d384f46f Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Fri, 21 Jul 2023 20:47:08 +0200
Subject: [PATCH 03/76] Added peak_signal_noise_ratio_eps call for synthesis
 case.

Additionally to the vanilla PSNR, also the PSNR based on value range and with epsilon in the denominator is now added to the overall_stats_dict as "psnr_range_eps"
---
 GANDLF/cli/generate_metrics.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index cf64f991f..56a3ff633 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -14,6 +14,7 @@
     structural_similarity_index,
     mean_squared_error,
     peak_signal_noise_ratio,
+    peak_signal_noise_ratio_eps,
     mean_squared_log_error,
     mean_absolute_error,
     ncc_mean,
@@ -258,10 +259,13 @@ def __fix_2d_tensor(input_tensor):
                 gt_image_infill, output_infill
             ).item()
 
-            # PSNR - similar to pytorch PeakSignalNoiseRatio until 4 digits after decimal point
             overall_stats_dict[current_subject_id]["psnr"] = peak_signal_noise_ratio(
                 gt_image_infill, output_infill
             ).item()
+            
+            overall_stats_dict[current_subject_id]["psnr_range_eps"] = peak_signal_noise_ratio_eps(
+                gt_image_infill, output_infill
+            ).item()
 
     pprint(overall_stats_dict)
     if outputfile is not None:

From e3e36d75d66353476e8ee692486532cf288a55a2 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Fri, 21 Jul 2023 20:52:04 +0200
Subject: [PATCH 04/76] Added peak_signal_noise_ratio_eps also the the metrics
 init file

---
 GANDLF/metrics/__init__.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/GANDLF/metrics/__init__.py b/GANDLF/metrics/__init__.py
index b8de47cf1..55feddd80 100644
--- a/GANDLF/metrics/__init__.py
+++ b/GANDLF/metrics/__init__.py
@@ -31,6 +31,7 @@
     structural_similarity_index,
     mean_squared_error,
     peak_signal_noise_ratio,
+    peak_signal_noise_ratio_eps,
     mean_squared_log_error,
     mean_absolute_error,
     ncc_mean,

From 0e2d72e97c75e8e3b51a352914ca0d0ba317a748 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Fri, 21 Jul 2023 21:39:33 +0200
Subject: [PATCH 05/76] Removed Trailing whitespace (I think)

---
 GANDLF/cli/generate_metrics.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index 56a3ff633..ff9d2b069 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -262,7 +262,7 @@ def __fix_2d_tensor(input_tensor):
             overall_stats_dict[current_subject_id]["psnr"] = peak_signal_noise_ratio(
                 gt_image_infill, output_infill
             ).item()
-            
+
             overall_stats_dict[current_subject_id]["psnr_range_eps"] = peak_signal_noise_ratio_eps(
                 gt_image_infill, output_infill
             ).item()

From 9c9d9e63a4556422d5374aacb23318ed324d2d3a Mon Sep 17 00:00:00 2001
From: Geeks-sid <sid.cre8er@gmail.com>
Date: Fri, 28 Jul 2023 12:17:34 -0400
Subject: [PATCH 06/76] upgrade openvino version

---
 .devcontainer/onCreateCommand.sh  |  2 +-
 .github/workflows/python-test.yml |  2 +-
 Dockerfile-CPU                    |  2 +-
 Dockerfile-CUDA11.6               |  2 +-
 Dockerfile-ROCm                   |  2 +-
 GANDLF/utils/modelio.py           | 78 ++++++++++++++-----------------
 docs/setup.md                     |  2 +-
 7 files changed, 42 insertions(+), 48 deletions(-)

diff --git a/.devcontainer/onCreateCommand.sh b/.devcontainer/onCreateCommand.sh
index c4bf0ea5c..bd69500a8 100755
--- a/.devcontainer/onCreateCommand.sh
+++ b/.devcontainer/onCreateCommand.sh
@@ -2,7 +2,7 @@
 
 pip install --upgrade pip
 pip install wheel
-pip install openvino-dev==2022.1.0 # [OPTIONAL] to generate optimized models for inference
+pip install openvino-dev==2023.0.1 # [OPTIONAL] to generate optimized models for inference
 pip install mlcube_docker          # [OPTIONAL] to deploy GaNDLF models as MLCube-compliant Docker containers
 pip install medmnist==2.1.0
 pip install torch==1.13.1+cpu torchvision==0.14.1+cpu torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cpu
diff --git a/.github/workflows/python-test.yml b/.github/workflows/python-test.yml
index 592c8e342..5364dc8df 100644
--- a/.github/workflows/python-test.yml
+++ b/.github/workflows/python-test.yml
@@ -72,7 +72,7 @@ jobs:
         sudo apt-get install libvips libvips-tools -y
         python -m pip install --upgrade pip
         python -m pip install wheel
-        python -m pip install openvino-dev==2022.1.0 mlcube_docker
+        python -m pip install openvino-dev==2023.0.1 mlcube_docker
         pip install torch==1.13.1+cpu torchvision==0.14.1+cpu torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cpu
         pip install -e .
     - name: Run generic unit tests
diff --git a/Dockerfile-CPU b/Dockerfile-CPU
index 127ffda89..0b5221fa7 100644
--- a/Dockerfile-CPU
+++ b/Dockerfile-CPU
@@ -8,7 +8,7 @@ RUN apt-get update && apt-get install -y python3.8 python3-pip libjpeg8-dev zlib
 RUN python3.8 -m pip install --upgrade pip
 # EXPLICITLY install cpu versions of torch/torchvision (not all versions have +cpu modes on PyPI...)
 RUN python3.8 -m pip install torch==1.13.1+cpu torchvision==0.14.1+cpu torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cpu
-RUN python3.8 -m pip install openvino-dev==2022.1.0 opencv-python-headless mlcube_docker
+RUN python3.8 -m pip install openvino-dev==2023.0.1 opencv-python-headless mlcube_docker
 
 # Do some dependency installation separately here to make layer caching more efficient
 COPY ./setup.py ./setup.py
diff --git a/Dockerfile-CUDA11.6 b/Dockerfile-CUDA11.6
index 05409bb47..0b8ed9c42 100644
--- a/Dockerfile-CUDA11.6
+++ b/Dockerfile-CUDA11.6
@@ -10,7 +10,7 @@ LABEL version=1.0
 RUN apt-get update && apt-get install -y python3.8 python3-pip libjpeg8-dev zlib1g-dev python3-dev libpython3.8-dev libffi-dev libgl1
 RUN python3.8 -m pip install --upgrade pip
 RUN python3.8 -m pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116
-RUN python3.8 -m pip install openvino-dev==2022.1.0 opencv-python-headless mlcube_docker
+RUN python3.8 -m pip install openvino-dev==2023.0.1 opencv-python-headless mlcube_docker
 
 # Do some dependency installation separately here to make layer caching more efficient
 COPY ./setup.py ./setup.py
diff --git a/Dockerfile-ROCm b/Dockerfile-ROCm
index 9cf8053fc..62e34cb81 100644
--- a/Dockerfile-ROCm
+++ b/Dockerfile-ROCm
@@ -8,7 +8,7 @@ LABEL version=1.0
 # The base image contains ROCm, python 3.8 and pytorch already, no need to install those
 RUN python3 -m pip install --upgrade pip
 RUN python3.8 -m pip install torch==1.13.1+rocm5.2 torchvision==0.14.1+rocm5.2 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/rocm5.2
-RUN python3 -m pip install --upgrade pip && python3 -m pip install openvino-dev==2022.1.0 opencv-python-headless mlcube_docker
+RUN python3 -m pip install --upgrade pip && python3 -m pip install openvino-dev==2023.0.1 opencv-python-headless mlcube_docker
 RUN apt-get update && apt-get install -y libgl1
 
 # Do some dependency installation separately here to make layer caching more efficient
diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index fa1004852..8143b4f5b 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -26,40 +26,48 @@
 initial_model_path_end = "_initial.pth.tar"
 
 
+import os
+import torch
+import subprocess
+
+
 def optimize_and_save_model(model, params, path, onnx_export=True):
     """
     Perform post-training optimization and save it to a file.
 
     Args:
-        model (torch model): Trained torch model.
+        model (torch.nn.Module): Trained torch model.
         params (dict): The parameter dictionary.
         path (str): The path to save the model dictionary to.
         onnx_export (bool): Whether to export to ONNX and OpenVINO.
     """
+    # Check if ONNX export is enabled in the parameter dictionary
     onnx_export = params["model"].get("onnx_export", onnx_export)
-    # check for incompatible topologies and disable onnx export
-    # customized imagenet_vgg no longer supported for onnx export: https://github.com/pytorch/pytorch/issues/42653
+
+    # Check for incompatible topologies and disable ONNX export
+    # Customized imagenet_vgg no longer supported for ONNX export
     if onnx_export:
-        if (params["model"]["architecture"] in ["sdnet", "brain_age"]) or (
-            "imagenet_vgg" in params["model"]["architecture"]
-        ):
+        architecture = params["model"]["architecture"]
+        if architecture in ["sdnet", "brain_age"] or "imagenet_vgg" in architecture:
             onnx_export = False
 
-    if not (onnx_export):
+    if not onnx_export:
+        # Print a warning if ONNX export is disabled and not already warned
         if "onnx_print" not in params:
             print("WARNING: Current model is not supported by ONNX/OpenVINO!")
             params["onnx_print"] = True
         return
     else:
         try:
-            print("Optimizing best model.")
+            print("Optimizing the best model.")
             num_channel = params["model"]["num_channels"]
             model_dimension = params["model"]["dimension"]
             ov_output_data_type = params["model"].get("data_type", "FP32")
             input_shape = params["patch_size"]
             onnx_path = path
-            if not (onnx_path.endswith(".onnx")):
+            if not onnx_path.endswith(".onnx"):
                 onnx_path = onnx_path.replace("pth.tar", "onnx")
+
             if model_dimension == 2:
                 dummy_input = torch.randn(
                     (1, num_channel, input_shape[0], input_shape[1])
@@ -69,6 +77,7 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
                     (1, num_channel, input_shape[0], input_shape[1], input_shape[2])
                 )
 
+            # Export the model to ONNX format
             with torch.no_grad():
                 torch.onnx.export(
                     model.to("cpu"),
@@ -86,52 +95,37 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
             print("WARNING: Cannot export to ONNX model.")
             return
 
-        # https://github.com/mlcommons/GaNDLF/issues/605
+        # Check if OpenVINO is present and try to convert the ONNX model
         openvino_present = False
         try:
-            import openvino
+            import openvino as ov
+            from openvino.tools.mo import convert_model
 
             openvino_present = True
         except ImportError:
             print("WARNING: OpenVINO is not present.")
 
         if openvino_present:
+            xml_path = onnx_path.replace("onnx", "xml")
+            bin_path = onnx_path.replace("onnx", "bin")
             try:
                 if model_dimension == 2:
-                    subprocess.call(
-                        [
-                            "mo",
-                            "--input_model",
-                            "{0}".format(onnx_path),
-                            "--input_shape",
-                            "[1,{0},{1},{2}]".format(
-                                num_channel, input_shape[0], input_shape[1]
-                            ),
-                            "--data_type",
-                            "{0}".format(ov_output_data_type),
-                            "--output_dir",
-                            "{0}".format(ov_output_dir),
-                        ],
+                    ov_model = convert_model(
+                        onnx_path,
+                        input_shape=(1, num_channel, input_shape[0], input_shape[1]),
                     )
                 else:
-                    subprocess.call(
-                        [
-                            "mo",
-                            "--input_model",
-                            "{0}".format(onnx_path),
-                            "--input_shape",
-                            "[1,{0},{1},{2},{3}]".format(
-                                num_channel,
-                                input_shape[0],
-                                input_shape[1],
-                                input_shape[2],
-                            ),
-                            "--data_type",
-                            "{0}".format(ov_output_data_type),
-                            "--output_dir",
-                            "{0}".format(ov_output_dir),
-                        ],
+                    ov_model = convert_model(
+                        onnx_path,
+                        input_shape=(
+                            1,
+                            num_channel,
+                            input_shape[0],
+                            input_shape[1],
+                            input_shape[2],
+                        ),
                     )
+                ov.runtime.serialize(ov_model, xml_path=xml_path, bin_path=bin_path)
             except subprocess.CalledProcessError:
                 print("WARNING: OpenVINO Model Optimizer IR conversion failed.")
 
diff --git a/docs/setup.md b/docs/setup.md
index b3b9eed36..ed15f014d 100644
--- a/docs/setup.md
+++ b/docs/setup.md
@@ -42,7 +42,7 @@ GaNDLF's primary computational foundation is built on PyTorch, and as such it su
 The following dependencies are optional, and are needed for specific features of GaNDLF.
 
 ```bash
-(venv_gandlf) $> pip install openvino-dev==2022.1.0 # [OPTIONAL] to generate post-training optimized models for inference
+(venv_gandlf) $> pip install openvino-dev==2023.0.1 # [OPTIONAL] to generate post-training optimized models for inference
 (venv_gandlf) $> pip install mlcube_docker # [OPTIONAL] to deploy GaNDLF models as MLCube-compliant Docker containers
 ```
 

From 183697215225e62d4ead0cc6ab073aa280023e1d Mon Sep 17 00:00:00 2001
From: Geeks-sid <sid.cre8er@gmail.com>
Date: Fri, 28 Jul 2023 12:19:29 -0400
Subject: [PATCH 07/76] udpate to base function

---
 .../cli/post_training_model_optimization.py   | 32 +++++++++----------
 1 file changed, 16 insertions(+), 16 deletions(-)

diff --git a/GANDLF/cli/post_training_model_optimization.py b/GANDLF/cli/post_training_model_optimization.py
index 65a3147b2..a5be38b73 100644
--- a/GANDLF/cli/post_training_model_optimization.py
+++ b/GANDLF/cli/post_training_model_optimization.py
@@ -4,7 +4,7 @@
 from GANDLF.utils import version_check, load_model, optimize_and_save_model
 
 
-def post_training_model_optimization(model_path, config_path):
+def post_training_model_optimization(model_path: str, config_path: str) -> bool:
     """
     CLI function to optimize a model for deployment.
 
@@ -15,29 +15,29 @@ def post_training_model_optimization(model_path, config_path):
     Returns:
         bool: True if successful, False otherwise.
     """
-
+    # Load the model and its parameters from the given paths
     main_dict = load_model(model_path, "cpu")
     parameters = main_dict.get("parameters", None)
-    parameters = (
-        parseConfig(config_path, version_check_flag=False)
-        if parameters is None
-        else parameters
-    )
-    (
-        model,
-        _,
-        _,
-        _,
-        _,
-        parameters,
-    ) = create_pytorch_objects(parameters, device="cpu")
+
+    # If parameters are not available in the model file, parse them from the config file
+    if parameters is None:
+        parameters = parseConfig(config_path, version_check_flag=False)
+
+    # Create PyTorch objects and set onnx_export to True for optimization
+    model, _, _, _, _, parameters = create_pytorch_objects(parameters, device="cpu")
     parameters["model"]["onnx_export"] = True
 
+    # Perform version check and load the model's state dictionary
     version_check(parameters["version"], version_to_check=main_dict["version"])
     model.load_state_dict(main_dict["model_state_dict"])
+
+    # Optimize the model and save it to an ONNX file
     optimize_and_save_model(model, parameters, model_path, onnx_export=True)
+
+    # Check if the optimized model file exists
     optimized_model_path = model_path.replace("pth.tar", "onnx")
     if not os.path.exists(optimized_model_path):
-        print("Error while optimizing model.")
+        print("Error while optimizing the model.")
         return False
+
     return True

From f5d2488b96ff57e230b562a79b95168fbb09836e Mon Sep 17 00:00:00 2001
From: Geeks-sid <sid.cre8er@gmail.com>
Date: Fri, 28 Jul 2023 12:22:08 -0400
Subject: [PATCH 08/76] update to modelio

---
 GANDLF/utils/modelio.py | 24 ++++++++++++++++++------
 1 file changed, 18 insertions(+), 6 deletions(-)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index 8143b4f5b..4512f4cfc 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -3,6 +3,7 @@
 
 from .generic import get_unique_timestamp
 from ..version import __version__
+from typing import Dict, Any
 
 # these are the base keys for the model dictionary to save
 model_dict_full = {
@@ -130,13 +131,19 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
                 print("WARNING: OpenVINO Model Optimizer IR conversion failed.")
 
 
-def save_model(model_dict, model, params, path, onnx_export=True):
+def save_model(
+    model_dict: Dict[str, Any],
+    model: torch.nn.Module,
+    params: Dict[str, Any],
+    path: str,
+    onnx_export: bool = True,
+):
     """
     Save the model dictionary to a file.
 
     Args:
         model_dict (dict): Model dictionary to save.
-        model (torch model): Trained torch model.
+        model (torch.nn.Module): Trained torch model.
         params (dict): The parameter dictionary.
         path (str): The path to save the model dictionary to.
         onnx_export (bool): Whether to export to ONNX and OpenVINO.
@@ -147,6 +154,7 @@ def save_model(model_dict, model, params, path, onnx_export=True):
     ).hexdigest()
     model_dict["version"] = __version__
     model_dict["parameters"] = params
+
     try:
         model_dict["git_hash"] = (
             subprocess.check_output(["git", "rev-parse", "HEAD"])
@@ -155,20 +163,23 @@ def save_model(model_dict, model, params, path, onnx_export=True):
         )
     except subprocess.CalledProcessError:
         model_dict["git_hash"] = None
+
     torch.save(model_dict, path)
 
     # post-training optimization
     optimize_and_save_model(model, params, path, onnx_export=onnx_export)
 
 
-def load_model(path, device, full_sanity_check=True):
+def load_model(
+    path: str, device: torch.device, full_sanity_check: bool = True
+) -> Dict[str, Any]:
     """
     Load a model dictionary from a file.
 
     Args:
         path (str): The path to save the model dictionary to.
         device (torch.device): The device to run the model on.
-        full_sanity_check (bool): Whether to run full sanity checking on model.
+        full_sanity_check (bool): Whether to run full sanity checking on the model.
 
     Returns:
         dict: Model dictionary containing model parameters and metadata.
@@ -187,8 +198,9 @@ def load_model(path, device, full_sanity_check=True):
             )
 
     # check if required keys are absent, and if so raise an error
+    model_dict_required = {"version", "parameters", "timestamp", "timestamp_hash"}
     incomplete_required_keys = [
-        key for key in model_dict_required.keys() if key not in model_dict.keys()
+        key for key in model_dict_required if key not in model_dict.keys()
     ]
     if len(incomplete_required_keys) > 0:
         raise KeyError(
@@ -199,7 +211,7 @@ def load_model(path, device, full_sanity_check=True):
     return model_dict
 
 
-def load_ov_model(path, device="CPU"):
+def load_ov_model(path: str, device: str = "CPU"):
     """
     Load an OpenVINO IR model from an .xml file.
 

From 130c99d68658cd4955e40ead966ba3dcc7f9d86d Mon Sep 17 00:00:00 2001
From: Geeks-sid <sid.cre8er@gmail.com>
Date: Fri, 28 Jul 2023 12:39:37 -0400
Subject: [PATCH 09/76] removed hardcoded required keys

---
 GANDLF/utils/modelio.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index 4512f4cfc..1111255a2 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -198,9 +198,8 @@ def load_model(
             )
 
     # check if required keys are absent, and if so raise an error
-    model_dict_required = {"version", "parameters", "timestamp", "timestamp_hash"}
     incomplete_required_keys = [
-        key for key in model_dict_required if key not in model_dict.keys()
+        key for key in model_dict_required.keys() if key not in model_dict.keys()
     ]
     if len(incomplete_required_keys) > 0:
         raise KeyError(

From d98472ca4d90ea7e4f491895218a875acb754943 Mon Sep 17 00:00:00 2001
From: Geeks-sid <sid.cre8er@gmail.com>
Date: Fri, 28 Jul 2023 12:48:30 -0400
Subject: [PATCH 10/76] updated imports

---
 GANDLF/utils/modelio.py | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index 1111255a2..0deead23f 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -1,9 +1,12 @@
-import os, hashlib, pkg_resources, subprocess
+import hashlib
+import os
+import subprocess
+from typing import Any, Dict
+
 import torch
 
-from .generic import get_unique_timestamp
 from ..version import __version__
-from typing import Dict, Any
+from .generic import get_unique_timestamp
 
 # these are the base keys for the model dictionary to save
 model_dict_full = {
@@ -27,11 +30,6 @@
 initial_model_path_end = "_initial.pth.tar"
 
 
-import os
-import torch
-import subprocess
-
-
 def optimize_and_save_model(model, params, path, onnx_export=True):
     """
     Perform post-training optimization and save it to a file.

From 0452c2679a5387678e010b34400cfd8f0047fe99 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Fri, 28 Jul 2023 19:17:03 -0400
Subject: [PATCH 11/76] updated default weight decay

---
 GANDLF/optimizers/wrap_torch.py | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/GANDLF/optimizers/wrap_torch.py b/GANDLF/optimizers/wrap_torch.py
index fe91be096..9a0455ec5 100644
--- a/GANDLF/optimizers/wrap_torch.py
+++ b/GANDLF/optimizers/wrap_torch.py
@@ -28,10 +28,10 @@ def sgd(parameters):
     optimizer = SGD(
         parameters["model_parameters"],
         lr=parameters.get("learning_rate"),
-        momentum=parameters["optimizer"].get("momentum", 0.9),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        momentum=parameters["optimizer"].get("momentum", 0.99),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
         dampening=parameters["optimizer"].get("dampening", 0),
-        nesterov=parameters["optimizer"].get("Nesterov", False),
+        nesterov=parameters["optimizer"].get("nesterov", True),
     )
 
     return optimizer
@@ -55,7 +55,7 @@ def asgd(parameters):
         alpha=parameters["optimizer"].get("alpha", 0.75),
         t0=parameters["optimizer"].get("t0", 1e6),
         lambd=parameters["optimizer"].get("lambd", 1e-4),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
     )
 
 
@@ -177,7 +177,7 @@ def adadelta(parameters):
         lr=parameters.get("learning_rate"),
         rho=parameters["optimizer"].get("rho", 0.9),
         eps=parameters["optimizer"].get("eps", 1e-6),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
     )
 
 
@@ -199,7 +199,7 @@ def adagrad(parameters):
         lr=parameters.get("learning_rate"),
         lr_decay=parameters["optimizer"].get("lr_decay", 0),
         eps=parameters["optimizer"].get("eps", 1e-6),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
     )
 
 
@@ -222,7 +222,7 @@ def rmsprop(parameters):
         eps=parameters["optimizer"].get("eps", 1e-8),
         centered=parameters["optimizer"].get("centered", False),
         momentum=parameters["optimizer"].get("momentum", 0),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
     )
 
 
@@ -242,6 +242,6 @@ def radam(parameters):
         lr=parameters.get("learning_rate"),
         betas=parameters["optimizer"].get("betas", (0.9, 0.999)),
         eps=parameters["optimizer"].get("eps", 1e-8),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
         foreach=parameters["optimizer"].get("foreach", None),
     )

From 08aac5fe0518bbc2d84bb0aab1c89d3f68b1eaea Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 10:21:10 +0200
Subject: [PATCH 12/76] Added epsilon and data_range as parameters to PSNR

---
 GANDLF/metrics/synthesis.py | 41 +++++++++++++++++--------------------
 1 file changed, 19 insertions(+), 22 deletions(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 3ded3867a..af5eef9f5 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -49,34 +49,31 @@ def mean_squared_error(target, prediction) -> torch.Tensor:
     return mse(preds=prediction, target=target)
 
 
-def peak_signal_noise_ratio(target, prediction) -> torch.Tensor:
+def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -> torch.Tensor:
     """
     Computes the peak signal to noise ratio between the target and prediction.
 
     Args:
         target (torch.Tensor): The target tensor.
         prediction (torch.Tensor): The prediction tensor.
-    """
-    psnr = PeakSignalNoiseRatio()
-    return psnr(preds=prediction, target=target)
-
-
-def peak_signal_noise_ratio_eps(target, prediction) -> torch.Tensor:
-    """
-    Computes the peak signal to noise ratio between the target and prediction. Uses a small epsilon in the denominator
-    of the fraction to avoid infinity as output. Also, operates on the data range instead of the maximum. This version
-    of PSNR is potentially more robust than the original formular.
-    
-    Args:
-        target (torch.Tensor): The target tensor.
-        prediction (torch.Tensor): The prediction tensor.
-    """
-    mse = mean_squared_error(target, prediction)
-    return (
-        10.0
-        * torch.log10((torch.max(target) - torch.min(target)) ** 2)
-        / (mse + sys.float_info.epsilon)
-    )
+        data_range (float, optional): If not None, this data range is used as enumerator instead of computing it from the given data. Defaults to None.
+        epsilon (float, optional): If not None, this epsilon is added to the denominator of the fraction to avoid infinity as output. Defaults to None.
+    """
+
+    if epsilon == None:
+        psnr = PeakSignalNoiseRatio(data_range=data_range)
+        return psnr(preds=prediction, target=target)
+    else: #reimplement torchmetrics RSNR but with epsilon
+        mse = mean_squared_error(target, prediction)
+        if data_range == None: #compute data_range like torchmetrics if not given
+            min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line
+            max_v = torch.max(target)
+            data_range = max_v - min_v
+        return (
+            10.0
+            * torch.log10(data_range) ** 2)
+            / (mse + epsilon)
+        )
 
 
 def mean_squared_log_error(target, prediction) -> torch.Tensor:

From 3ffbaa791320bd601a4ef3c308561e685e4d27ca Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 10:21:58 +0200
Subject: [PATCH 13/76] Unified PSNR versions

---
 GANDLF/metrics/__init__.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/GANDLF/metrics/__init__.py b/GANDLF/metrics/__init__.py
index 55feddd80..b8de47cf1 100644
--- a/GANDLF/metrics/__init__.py
+++ b/GANDLF/metrics/__init__.py
@@ -31,7 +31,6 @@
     structural_similarity_index,
     mean_squared_error,
     peak_signal_noise_ratio,
-    peak_signal_noise_ratio_eps,
     mean_squared_log_error,
     mean_absolute_error,
     ncc_mean,

From af8c12dcb3327e8a1995d19ba0ba3b28a89d116a Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 10:23:44 +0200
Subject: [PATCH 14/76] Update generate_metrics.py for usage of the unified
 PSNR signature

---
 GANDLF/cli/generate_metrics.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index ff9d2b069..75800ccea 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -14,7 +14,6 @@
     structural_similarity_index,
     mean_squared_error,
     peak_signal_noise_ratio,
-    peak_signal_noise_ratio_eps,
     mean_squared_log_error,
     mean_absolute_error,
     ncc_mean,
@@ -263,8 +262,8 @@ def __fix_2d_tensor(input_tensor):
                 gt_image_infill, output_infill
             ).item()
 
-            overall_stats_dict[current_subject_id]["psnr_range_eps"] = peak_signal_noise_ratio_eps(
-                gt_image_infill, output_infill
+            overall_stats_dict[current_subject_id]["psnr_eps"] = peak_signal_noise_ratio(
+                gt_image_infill, output_infill, epsilon=sys.float_info.epsilon
             ).item()
 
     pprint(overall_stats_dict)

From b42ca4e6b801eb1f4d379c741db49cdb30395b97 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 10:40:55 +0200
Subject: [PATCH 15/76] Fixed IndentationError?

---
 GANDLF/metrics/synthesis.py | 6 +-----
 1 file changed, 1 insertion(+), 5 deletions(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index af5eef9f5..6db0c74e4 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -69,11 +69,7 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line
             max_v = torch.max(target)
             data_range = max_v - min_v
-        return (
-            10.0
-            * torch.log10(data_range) ** 2)
-            / (mse + epsilon)
-        )
+        return 10.0 * ( torch.log10(data_range) ** 2) / (mse + epsilon) )
 
 
 def mean_squared_log_error(target, prediction) -> torch.Tensor:

From fdea5185761578c0b162db77340c9e9484af0a67 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 10:56:43 +0200
Subject: [PATCH 16/76] Fixed: unmatched ")"

---
 GANDLF/metrics/synthesis.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 6db0c74e4..017a6cc27 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -69,7 +69,7 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line
             max_v = torch.max(target)
             data_range = max_v - min_v
-        return 10.0 * ( torch.log10(data_range) ** 2) / (mse + epsilon) )
+        return 10.0 * (( torch.log10(data_range) ** 2) / (mse + epsilon) )
 
 
 def mean_squared_log_error(target, prediction) -> torch.Tensor:

From d2bf1274ca56ce3795fdc18e1b590642cf225609 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 11:58:26 +0200
Subject: [PATCH 17/76] Removed unused sys package

---
 GANDLF/metrics/synthesis.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 017a6cc27..12550b0a6 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -1,4 +1,3 @@
-import sys
 import SimpleITK as sitk
 import PIL.Image
 import numpy as np

From acef5d8dd3504fd27fe69c82a3b0ea722c045903 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 11:58:50 +0200
Subject: [PATCH 18/76] Added required sys package

---
 GANDLF/cli/generate_metrics.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index 75800ccea..7a0e2c5ca 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -1,3 +1,4 @@
+import sys
 import yaml
 from pprint import pprint
 import pandas as pd

From 941c85bdc0cef7866984771e62e3ee8be261f255 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 13:14:24 +0200
Subject: [PATCH 19/76] Introduced percentile normalization for synthesis
 challenge metrics

---
 GANDLF/cli/generate_metrics.py | 33 ++++++++++++++++++++++++++++++---
 1 file changed, 30 insertions(+), 3 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index cf64f991f..058eb83c3 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -193,6 +193,32 @@ def __fix_2d_tensor(input_tensor):
             else:
                 return input_tensor
 
+        def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5, strictlyPositive=True):
+            """Normalizes a tensor based on percentiles. Clips values below and above the percentile.
+            Percentiles for normalization can come from another tensor.
+        
+            Args:
+                input_tensor (torch.Tensor): Tensor to be normalized based on the data from the reference_tensor.
+                    If reference_tensor is None, the percentiles from this tensor will be used.
+                reference_tensor (torch.Tensor, optional): The tensor used for obtaining the percentiles.
+                p_min (float, optional): Lower end percentile. Defaults to 0.5.
+                p_max (float, optional): Upper end percentile. Defaults to 99.5.
+                strictlyPositive (bool, optional): Ensures that really all values are above 0 before normalization. Defaults to True.
+        
+            Returns:
+                torch.Tensor: The input_tensor normalized based on the percentiles of the reference tensor.
+            """
+            if(reference_tensor == None):
+                reference_tensor = input_tensor
+            v_min, v_max = np.percentile(reference_tensor, [p_min,p_max]) #get p_min percentile and p_max percentile
+        
+            if( v_min < 0 and strictlyPositive): #set lower bound to be 0 if it would be below
+                v_min = 0
+            output_tensor = np.clip(input_tensor,v_min,v_max) #clip values to percentiles from reference_tensor
+            output_tensor = (output_tensor - v_min)/(v_max-v_min) #normalizes values to [0;1]
+        
+            return output_tensor
+
         for _, row in tqdm(input_df.iterrows(), total=input_df.shape[0]):
             current_subject_id = row[headers["subjectid"]]
             overall_stats_dict[current_subject_id] = {}
@@ -219,9 +245,9 @@ def __fix_2d_tensor(input_tensor):
             # Normalize to [0;1] based on GT (otherwise MSE will depend on the image intensity range)
             normalize = parameters.get("normalize", True)
             if normalize:
-                v_max = gt_image_infill.max()
-                output_infill /= v_max
-                gt_image_infill /= v_max
+                reference_tensor = gt_image * ~mask #use all the tissue that is not masked for normalization
+                gt_image_infill = __percentile_clip(gt_image_infill, reference_tensor=reference_tensor, p_min=0.5, p_max=99.5, strictlyPositive=True)
+                prediction_infill = __percentile_clip(prediction_infill, reference_tensor=reference_tensor, p_min=0.5, p_max=99.5, strictlyPositive=True)
 
             overall_stats_dict[current_subject_id][
                 "ssim"
@@ -258,6 +284,7 @@ def __fix_2d_tensor(input_tensor):
                 gt_image_infill, output_infill
             ).item()
 
+            #TODO: use data_range=1.0 as parameter for PSNR when the Pull request is accepted that introduces the data_range parameter!
             # PSNR - similar to pytorch PeakSignalNoiseRatio until 4 digits after decimal point
             overall_stats_dict[current_subject_id]["psnr"] = peak_signal_noise_ratio(
                 gt_image_infill, output_infill

From 6d1b3fbf290b3b81cdd9e16c1e5f28c51f3e7519 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Sat, 29 Jul 2023 13:27:59 +0200
Subject: [PATCH 20/76] Adapted different naming, removed tailing whitespaces

---
 GANDLF/cli/generate_metrics.py | 11 +++++------
 1 file changed, 5 insertions(+), 6 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index 058eb83c3..f4f970319 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -196,7 +196,7 @@ def __fix_2d_tensor(input_tensor):
         def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5, strictlyPositive=True):
             """Normalizes a tensor based on percentiles. Clips values below and above the percentile.
             Percentiles for normalization can come from another tensor.
-        
+
             Args:
                 input_tensor (torch.Tensor): Tensor to be normalized based on the data from the reference_tensor.
                     If reference_tensor is None, the percentiles from this tensor will be used.
@@ -204,19 +204,18 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
                 p_min (float, optional): Lower end percentile. Defaults to 0.5.
                 p_max (float, optional): Upper end percentile. Defaults to 99.5.
                 strictlyPositive (bool, optional): Ensures that really all values are above 0 before normalization. Defaults to True.
-        
+
             Returns:
                 torch.Tensor: The input_tensor normalized based on the percentiles of the reference tensor.
             """
             if(reference_tensor == None):
                 reference_tensor = input_tensor
             v_min, v_max = np.percentile(reference_tensor, [p_min,p_max]) #get p_min percentile and p_max percentile
-        
+
             if( v_min < 0 and strictlyPositive): #set lower bound to be 0 if it would be below
                 v_min = 0
             output_tensor = np.clip(input_tensor,v_min,v_max) #clip values to percentiles from reference_tensor
             output_tensor = (output_tensor - v_min)/(v_max-v_min) #normalizes values to [0;1]
-        
             return output_tensor
 
         for _, row in tqdm(input_df.iterrows(), total=input_df.shape[0]):
@@ -245,9 +244,9 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
             # Normalize to [0;1] based on GT (otherwise MSE will depend on the image intensity range)
             normalize = parameters.get("normalize", True)
             if normalize:
-                reference_tensor = gt_image * ~mask #use all the tissue that is not masked for normalization
+                reference_tensor = target_image * ~mask #use all the tissue that is not masked for normalization
                 gt_image_infill = __percentile_clip(gt_image_infill, reference_tensor=reference_tensor, p_min=0.5, p_max=99.5, strictlyPositive=True)
-                prediction_infill = __percentile_clip(prediction_infill, reference_tensor=reference_tensor, p_min=0.5, p_max=99.5, strictlyPositive=True)
+                output_infill = __percentile_clip(output_infill, reference_tensor=reference_tensor, p_min=0.5, p_max=99.5, strictlyPositive=True)
 
             overall_stats_dict[current_subject_id][
                 "ssim"

From ee6079c74e8387c0602795ed5f588a63061088e3 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
Date: Sun, 30 Jul 2023 09:21:47 -0400
Subject: [PATCH 21/76] reverted to in-line if for coverage

---
 GANDLF/cli/post_training_model_optimization.py | 7 +++++--
 1 file changed, 5 insertions(+), 2 deletions(-)

diff --git a/GANDLF/cli/post_training_model_optimization.py b/GANDLF/cli/post_training_model_optimization.py
index a5be38b73..46a5ea6ff 100644
--- a/GANDLF/cli/post_training_model_optimization.py
+++ b/GANDLF/cli/post_training_model_optimization.py
@@ -20,8 +20,11 @@ def post_training_model_optimization(model_path: str, config_path: str) -> bool:
     parameters = main_dict.get("parameters", None)
 
     # If parameters are not available in the model file, parse them from the config file
-    if parameters is None:
-        parameters = parseConfig(config_path, version_check_flag=False)
+    parameters = (
+        parseConfig(config_path, version_check_flag=False)
+        if parameters is None
+        else parameters
+    )
 
     # Create PyTorch objects and set onnx_export to True for optimization
     model, _, _, _, _, parameters = create_pytorch_objects(parameters, device="cpu")

From 9472f068dead62e7308ef985a915e415c82dddd7 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Mon, 31 Jul 2023 17:06:16 +0200
Subject: [PATCH 22/76] Different description (comment) for non-torchmetrics
 PSNR

Co-authored-by: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
---
 GANDLF/metrics/synthesis.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 12550b0a6..4d70e284b 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -62,7 +62,8 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
     if epsilon == None:
         psnr = PeakSignalNoiseRatio(data_range=data_range)
         return psnr(preds=prediction, target=target)
-    else: #reimplement torchmetrics RSNR but with epsilon
+    else:
+        # implementation of PSNR that does not give `inf`/`nan` when `mse==0`
         mse = mean_squared_error(target, prediction)
         if data_range == None: #compute data_range like torchmetrics if not given
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line

From 5be2fcaebbe37febbf55b750efb4f5a928f8cd37 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Mon, 31 Jul 2023 17:09:31 +0200
Subject: [PATCH 23/76] Fixed wrong parenthesis in PSR definition

Co-authored-by: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
---
 GANDLF/metrics/synthesis.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 4d70e284b..a10ba7d96 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -69,7 +69,7 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line
             max_v = torch.max(target)
             data_range = max_v - min_v
-        return 10.0 * (( torch.log10(data_range) ** 2) / (mse + epsilon) )
+        return 10.0 * torch.log10((data_range ** 2) / (mse + epsilon))
 
 
 def mean_squared_log_error(target, prediction) -> torch.Tensor:

From 70f8ff5a9bb18f4a91c3bdadeaa3eb1bd2db97bf Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Mon, 31 Jul 2023 17:30:35 +0200
Subject: [PATCH 24/76] Trying different quotation marks

I don't know why changing this comment broke the testing pipeline. Maybe it was not the comment. I changed the quotation marks hoping that would help (probably does not though...)
---
 GANDLF/metrics/synthesis.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index a10ba7d96..de04700eb 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -63,7 +63,7 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
         psnr = PeakSignalNoiseRatio(data_range=data_range)
         return psnr(preds=prediction, target=target)
     else:
-        # implementation of PSNR that does not give `inf`/`nan` when `mse==0`
+        # implementation of PSNR that does not give 'inf'/'nan' when 'mse==0'
         mse = mean_squared_error(target, prediction)
         if data_range == None: #compute data_range like torchmetrics if not given
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line

From dfa16657ab95c10b15c590198f52ba733bf41793 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Tue, 1 Aug 2023 20:51:11 +0200
Subject: [PATCH 25/76] Tried removing comment

---
 GANDLF/metrics/synthesis.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index de04700eb..21ce07c7f 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -63,7 +63,6 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
         psnr = PeakSignalNoiseRatio(data_range=data_range)
         return psnr(preds=prediction, target=target)
     else:
-        # implementation of PSNR that does not give 'inf'/'nan' when 'mse==0'
         mse = mean_squared_error(target, prediction)
         if data_range == None: #compute data_range like torchmetrics if not given
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line

From 621b8891955b1be767df2b00fd3ca64b31ea7ae2 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
Date: Tue, 1 Aug 2023 15:04:55 -0400
Subject: [PATCH 26/76] added a version check

---
 GANDLF/utils/modelio.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index 0deead23f..40b785be9 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -99,8 +99,10 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
         try:
             import openvino as ov
             from openvino.tools.mo import convert_model
-
-            openvino_present = True
+            from openvino.runtime import get_version
+            openvino_present = False
+            if "2023" in get_version():
+                openvino_present = True
         except ImportError:
             print("WARNING: OpenVINO is not present.")
 

From 5f584af9197ae77dccdedd770e114fedcdef11f5 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Tue, 1 Aug 2023 21:08:50 +0200
Subject: [PATCH 27/76] Trying to revert parenthesis fix

Now the code should be in the state when it last worked
---
 GANDLF/metrics/synthesis.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 21ce07c7f..1e22fe21e 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -68,7 +68,8 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line
             max_v = torch.max(target)
             data_range = max_v - min_v
-        return 10.0 * torch.log10((data_range ** 2) / (mse + epsilon))
+        return 10.0 * (( torch.log10(data_range) ** 2) / (mse + epsilon) )
+        #return 10.0 * torch.log10((data_range ** 2) / (mse + epsilon))
 
 
 def mean_squared_log_error(target, prediction) -> torch.Tensor:

From d8b1f8d33c6be488d3a70eea1fe572d04dace53a Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Tue, 1 Aug 2023 21:16:33 +0200
Subject: [PATCH 28/76] Returned to current state of code

I do not know why the pipeline fails To me it seems unrelated to the changes that were made since the last successful run.
---
 GANDLF/metrics/synthesis.py | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 1e22fe21e..fd3590a58 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -62,14 +62,13 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
     if epsilon == None:
         psnr = PeakSignalNoiseRatio(data_range=data_range)
         return psnr(preds=prediction, target=target)
-    else:
+    else: # implementation of PSNR that does not give 'inf'/'nan' when 'mse==0'
         mse = mean_squared_error(target, prediction)
         if data_range == None: #compute data_range like torchmetrics if not given
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line
             max_v = torch.max(target)
             data_range = max_v - min_v
-        return 10.0 * (( torch.log10(data_range) ** 2) / (mse + epsilon) )
-        #return 10.0 * torch.log10((data_range ** 2) / (mse + epsilon))
+        return 10.0 * torch.log10((data_range ** 2) / (mse + epsilon))
 
 
 def mean_squared_log_error(target, prediction) -> torch.Tensor:

From 67b9d720b466b84b192e566035f2a721f2f6a9d6 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Tue, 1 Aug 2023 21:32:44 +0200
Subject: [PATCH 29/76] Sarthaks suggestion for code coverage

Co-authored-by: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
---
 GANDLF/cli/generate_metrics.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index f4f970319..162ab1f1b 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -208,8 +208,7 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
             Returns:
                 torch.Tensor: The input_tensor normalized based on the percentiles of the reference tensor.
             """
-            if(reference_tensor == None):
-                reference_tensor = input_tensor
+            reference_tensor = input_tensor if reference_tensor is None else reference_tensor
             v_min, v_max = np.percentile(reference_tensor, [p_min,p_max]) #get p_min percentile and p_max percentile
 
             if( v_min < 0 and strictlyPositive): #set lower bound to be 0 if it would be below

From e9a91b1bf99752667ce81a1a40d1eccd327768cd Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Tue, 1 Aug 2023 21:33:49 +0200
Subject: [PATCH 30/76] Sarthaks suggestion to increase code coverage Nr. 2

Co-authored-by: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
---
 GANDLF/cli/generate_metrics.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index 162ab1f1b..f0bc15590 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -211,8 +211,8 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
             reference_tensor = input_tensor if reference_tensor is None else reference_tensor
             v_min, v_max = np.percentile(reference_tensor, [p_min,p_max]) #get p_min percentile and p_max percentile
 
-            if( v_min < 0 and strictlyPositive): #set lower bound to be 0 if it would be below
-                v_min = 0
+            # set lower bound to be 0 if strictlyPositive is enabled
+            v_min = max(v_min, 0.0) if strictlyPositive else v_min
             output_tensor = np.clip(input_tensor,v_min,v_max) #clip values to percentiles from reference_tensor
             output_tensor = (output_tensor - v_min)/(v_max-v_min) #normalizes values to [0;1]
             return output_tensor

From 0cac8276f5fb3a77e758be02dcfd0b3734f333c9 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
Date: Tue, 1 Aug 2023 16:56:27 -0400
Subject: [PATCH 31/76] better check + comment

---
 GANDLF/utils/modelio.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index 40b785be9..af4f77d84 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -101,7 +101,8 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
             from openvino.tools.mo import convert_model
             from openvino.runtime import get_version
             openvino_present = False
-            if "2023" in get_version():
+            # check for the correct openvino version to prevent inadvertent api breaks
+            if "2023.0.1" in get_version():
                 openvino_present = True
         except ImportError:
             print("WARNING: OpenVINO is not present.")

From 813e8979f31a48c98e848b721bde064f2889d818 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Tue, 1 Aug 2023 17:05:43 -0400
Subject: [PATCH 32/76] checking a fix for openfl-CI

---
 .github/workflows/openfl-test.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/openfl-test.yml b/.github/workflows/openfl-test.yml
index 43883cff0..f65ecd929 100644
--- a/.github/workflows/openfl-test.yml
+++ b/.github/workflows/openfl-test.yml
@@ -90,6 +90,7 @@ jobs:
         cd openfl
         git fetch --tags
         git checkout $(git describe --tags --abbrev=0)
+        pip install tensorboardX<=2.6.1 # https://github.com/lanpa/tensorboardX/issues/716
         pip install -e .
         cd ..
         echo "Copying files to appropriate directories"

From 3f300c8a0c886d718a8e5594df0dc50842adcd26 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Tue, 1 Aug 2023 17:22:35 -0400
Subject: [PATCH 33/76] updated syntax

---
 .github/workflows/openfl-test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/openfl-test.yml b/.github/workflows/openfl-test.yml
index f65ecd929..c512768aa 100644
--- a/.github/workflows/openfl-test.yml
+++ b/.github/workflows/openfl-test.yml
@@ -90,7 +90,7 @@ jobs:
         cd openfl
         git fetch --tags
         git checkout $(git describe --tags --abbrev=0)
-        pip install tensorboardX<=2.6.1 # https://github.com/lanpa/tensorboardX/issues/716
+        pip install "tensorboardX!=2.6.2" # https://github.com/lanpa/tensorboardX/issues/716
         pip install -e .
         cd ..
         echo "Copying files to appropriate directories"

From f714ef0bd69af15d6ab766d62e714805292b1424 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Tue, 1 Aug 2023 19:41:13 -0400
Subject: [PATCH 34/76] trying sed to replace protobuf version requirement

---
 .github/workflows/openfl-test.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/openfl-test.yml b/.github/workflows/openfl-test.yml
index c512768aa..c33f10c79 100644
--- a/.github/workflows/openfl-test.yml
+++ b/.github/workflows/openfl-test.yml
@@ -90,7 +90,8 @@ jobs:
         cd openfl
         git fetch --tags
         git checkout $(git describe --tags --abbrev=0)
-        pip install "tensorboardX!=2.6.2" # https://github.com/lanpa/tensorboardX/issues/716
+        # pip install "tensorboardX!=2.6.2" # https://github.com/lanpa/tensorboardX/issues/716
+        sed -i -e 's/protobuf==3.19.6/protobuf/g' setup.py ## this should NOT be there
         pip install -e .
         cd ..
         echo "Copying files to appropriate directories"

From da780850a34b8be9ad1d325625920ebfbd0628c6 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
Date: Wed, 2 Aug 2023 08:40:03 -0400
Subject: [PATCH 35/76] removed unwanted variable

---
 GANDLF/utils/modelio.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index af4f77d84..a01857dc6 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -61,7 +61,6 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
             print("Optimizing the best model.")
             num_channel = params["model"]["num_channels"]
             model_dimension = params["model"]["dimension"]
-            ov_output_data_type = params["model"].get("data_type", "FP32")
             input_shape = params["patch_size"]
             onnx_path = path
             if not onnx_path.endswith(".onnx"):

From 285aefd5868002cdceb4e669eb8e7e54e1fe367e Mon Sep 17 00:00:00 2001
From: Siddhesh Thakur <sid.cre8er@gmail.com>
Date: Wed, 2 Aug 2023 09:40:12 -0400
Subject: [PATCH 36/76] Update GANDLF/utils/modelio.py

Co-authored-by: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
---
 GANDLF/utils/modelio.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index a01857dc6..e49c59cee 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -127,8 +127,8 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
                         ),
                     )
                 ov.runtime.serialize(ov_model, xml_path=xml_path, bin_path=bin_path)
-            except subprocess.CalledProcessError:
-                print("WARNING: OpenVINO Model Optimizer IR conversion failed.")
+            except Exception as e:
+                print("WARNING: OpenVINO Model Optimizer IR conversion failed: " + e)
 
 
 def save_model(

From e6580768f848f2a7bdf36165ef9fe5356a999006 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Wed, 2 Aug 2023 16:02:55 +0200
Subject: [PATCH 37/76] Additional PSNR versions/columns for the normalized
 synthesis case

As we normalize the data to [0;1], we have top-down knowledge now about the data range. For this knowledge I added two cases/columns of PSNR evaluations.
---
 GANDLF/cli/generate_metrics.py | 17 ++++++++++++-----
 1 file changed, 12 insertions(+), 5 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index 9d3b2d8c0..4dc6eaa74 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -283,16 +283,23 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
                 gt_image_infill, output_infill
             ).item()
 
-            #TODO: use data_range=1.0 as parameter for PSNR when the Pull request is accepted that introduces the data_range parameter!
-            # PSNR - similar to pytorch PeakSignalNoiseRatio until 4 digits after decimal point
-            overall_stats_dict[current_subject_id]["psnr"] = peak_signal_noise_ratio(
-                gt_image_infill, output_infill
+            overall_stats_dict[current_subject_id]["psnr"] = peak_signal_noise_ratio( #torchmetrics PSNR using "max"
+                gt_image_infill, output_infill 
             ).item()
 
-            overall_stats_dict[current_subject_id]["psnr_eps"] = peak_signal_noise_ratio(
+            overall_stats_dict[current_subject_id]["psnr_eps"] = peak_signal_noise_ratio( #same as above but with epsilon for robustness
                 gt_image_infill, output_infill, epsilon=sys.float_info.epsilon
             ).item()
 
+            if normalize : #only use fix data range to [0;1] if the data was normalized before
+                overall_stats_dict[current_subject_id]["psnr_01"] = peak_signal_noise_ratio( #torchmetrics PSNR but with fixed data range of 0 to 1
+                    gt_image_infill, output_infill, data_range=1.0
+                ).item()
+    
+                overall_stats_dict[current_subject_id]["psnr_01_eps"] = peak_signal_noise_ratio( #same as above but with epsilon for robustness
+                    gt_image_infill, output_infill, epsilon=sys.float_info.epsilon
+                ).item()
+
     pprint(overall_stats_dict)
     if outputfile is not None:
         with open(outputfile, "w") as outfile:

From 31605a349d20a60e9cacaa8095c3cd9d76620429 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Wed, 2 Aug 2023 18:05:35 +0200
Subject: [PATCH 38/76] Comment formatting, running black

---
 GANDLF/cli/generate_metrics.py | 25 ++++++++++++++++++-------
 1 file changed, 18 insertions(+), 7 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index 4dc6eaa74..c43a1f10e 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -283,20 +283,31 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
                 gt_image_infill, output_infill
             ).item()
 
-            overall_stats_dict[current_subject_id]["psnr"] = peak_signal_noise_ratio( #torchmetrics PSNR using "max"
-                gt_image_infill, output_infill 
+                        # torchmetrics PSNR using "max"
+            overall_stats_dict[current_subject_id]["psnr"] = peak_signal_noise_ratio(
+                gt_image_infill, output_infill
             ).item()
 
-            overall_stats_dict[current_subject_id]["psnr_eps"] = peak_signal_noise_ratio( #same as above but with epsilon for robustness
+            # same as above but with epsilon for robustness
+            overall_stats_dict[current_subject_id][
+                "psnr_eps"
+            ] = peak_signal_noise_ratio(
                 gt_image_infill, output_infill, epsilon=sys.float_info.epsilon
             ).item()
 
-            if normalize : #only use fix data range to [0;1] if the data was normalized before
-                overall_stats_dict[current_subject_id]["psnr_01"] = peak_signal_noise_ratio( #torchmetrics PSNR but with fixed data range of 0 to 1
+            # only use fix data range to [0;1] if the data was normalized before
+            if normalize:
+                # torchmetrics PSNR but with fixed data range of 0 to 1
+                overall_stats_dict[current_subject_id][
+                    "psnr_01"
+                ] = peak_signal_noise_ratio(
                     gt_image_infill, output_infill, data_range=1.0
                 ).item()
-    
-                overall_stats_dict[current_subject_id]["psnr_01_eps"] = peak_signal_noise_ratio( #same as above but with epsilon for robustness
+
+                # same as above but with epsilon for robustness
+                overall_stats_dict[current_subject_id][
+                    "psnr_01_eps"
+                ] = peak_signal_noise_ratio(
                     gt_image_infill, output_infill, epsilon=sys.float_info.epsilon
                 ).item()
 

From b66a7c61de075198dba6b98d8d931f89f0ad06f8 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@pennmedicine.upenn.edu>
Date: Wed, 2 Aug 2023 12:40:49 -0400
Subject: [PATCH 39/76] removed spaces

---
 GANDLF/cli/generate_metrics.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index c43a1f10e..07423a3fc 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -283,7 +283,7 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
                 gt_image_infill, output_infill
             ).item()
 
-                        # torchmetrics PSNR using "max"
+            # torchmetrics PSNR using "max"
             overall_stats_dict[current_subject_id]["psnr"] = peak_signal_noise_ratio(
                 gt_image_infill, output_infill
             ).item()

From 855d297783bfa6ed51484e1fcacb29e7aa01fd77 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Wed, 2 Aug 2023 15:22:43 -0400
Subject: [PATCH 40/76] added print of weights

---
 GANDLF/compute/generic.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/GANDLF/compute/generic.py b/GANDLF/compute/generic.py
index 517db518f..d3674f42e 100644
--- a/GANDLF/compute/generic.py
+++ b/GANDLF/compute/generic.py
@@ -97,6 +97,9 @@ def create_pytorch_objects(parameters, train_csv=None, val_csv=None, device="cpu
             parameters["class_weights"],
         ) = get_class_imbalance_weights(parameters["training_data"], parameters)
 
+        print("Class weights  : ", parameters["class_weights"])
+        print("Penalty weights: ", parameters["weights"])
+
     else:
         scheduler = None
 

From 6d476a238e459410c9ce11f676410b617cef356a Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 12:53:08 -0400
Subject: [PATCH 41/76] added comments and expected data types

---
 GANDLF/losses/segmentation.py | 35 ++++++++++++++++++++++++++---------
 1 file changed, 26 insertions(+), 9 deletions(-)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index 5591e2c1e..399ddd710 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -3,13 +3,13 @@
 
 
 # Dice scores and dice losses
-def dice(predicted, target) -> torch.Tensor:
+def dice(predicted: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
     """
     This function computes a dice score between two tensors.
 
     Args:
-        predicted (_type_): Predicted value by the network.
-        target (_type_): Required target label to match the predicted with
+        predicted (torch.Tensor): Predicted value by the network.
+        target (torch.Tensor): Required target label to match the predicted with
 
     Returns:
         torch.Tensor: The computed dice score.
@@ -25,7 +25,14 @@ def dice(predicted, target) -> torch.Tensor:
     return dice_score
 
 
-def MCD(predicted, target, num_class, weights=None, ignore_class=None, loss_type=0):
+def MCD(
+    predicted: torch.Tensor,
+    target: torch.Tensor,
+    num_class: int,
+    weights: list = None,
+    ignore_class: int = None,
+    loss_type: int = 0,
+) -> torch.Tensor:
     """
     This function computes the mean class dice score between two tensors
 
@@ -66,7 +73,9 @@ def MCD(predicted, target, num_class, weights=None, ignore_class=None, loss_type
     return acc_dice
 
 
-def MCD_loss(predicted, target, params):
+def MCD_loss(
+    predicted: torch.Tensor, target: torch.Tensor, params: dict
+) -> torch.Tensor:
     """
     These weights should be the penalty weights, not dice weights
     """
@@ -80,7 +89,9 @@ def MCD_loss(predicted, target, params):
     )
 
 
-def MCD_log_loss(predicted, target, params):
+def MCD_log_loss(
+    predicted: torch.Tensor, target: torch.Tensor, params: dict
+) -> torch.Tensor:
     """
     These weights should be the penalty weights, not dice weights
     """
@@ -94,7 +105,9 @@ def MCD_log_loss(predicted, target, params):
     )
 
 
-def tversky_loss(predicted, target, alpha=0.5, beta=0.5):
+def tversky_loss(
+    predicted: torch.Tensor, target: torch.Tensor, alpha: float = 0.5, beta: float = 0.5
+) -> torch.Tensor:
     """
     This function calculates the Tversky loss between two tensors.
 
@@ -127,7 +140,9 @@ def tversky_loss(predicted, target, alpha=0.5, beta=0.5):
     return loss
 
 
-def MCT_loss(predicted, target, params=None):
+def MCT_loss(
+    predicted: torch.Tensor, target: torch.Tensor, params: dict = None
+) -> torch.Tensor:
     """
     This function calculates the Multi-Class Tversky loss between two tensors.
 
@@ -171,7 +186,9 @@ def KullbackLeiblerDivergence(mu, logvar, params=None):
     return loss.mean()
 
 
-def FocalLoss(predicted, target, params=None):
+def FocalLoss(
+    predicted: torch.Tensor, target: torch.Tensor, params: dict = None
+) -> torch.Tensor:
     """
     This function calculates the Focal loss between two tensors.
 

From 44ac9a9005899c1d8c868cd6fcab61f5a69a75ef Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 12:55:41 -0400
Subject: [PATCH 42/76] added mcc function

---
 GANDLF/losses/segmentation.py | 31 +++++++++++++++++++++++++++++++
 1 file changed, 31 insertions(+)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index 399ddd710..9aa9e5b3c 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -25,6 +25,37 @@ def dice(predicted: torch.Tensor, target: torch.Tensor) -> torch.Tensor:
     return dice_score
 
 
+def mcc(predictions: torch.Tensor, targets: torch.Tensor) -> torch.Tensor:
+    """
+    This function computes the Matthews Correlation Coefficient (MCC) between two tensors. Adapted from https://github.com/kakumarabhishek/MCC-Loss/blob/main/loss.py.
+
+    Args:
+        predictions (torch.Tensor): The predicted value by the network.
+        targets (torch.Tensor): Required target label to match the predicted with
+
+    Returns:
+        torch.Tensor: The computed MCC score.
+    """
+    tp = torch.sum(torch.mul(predictions, targets))
+    tn = torch.sum(torch.mul((1 - predictions), (1 - targets)))
+    fp = torch.sum(torch.mul(predictions, (1 - targets)))
+    fn = torch.sum(torch.mul((1 - predictions), targets))
+
+    numerator = torch.mul(tp, tn) - torch.mul(fp, fn)
+    # Adding epsilon to the denominator to avoid divide-by-zero errors.
+    denominator = (
+        torch.sqrt(
+            torch.add(tp, 1, fp)
+            * torch.add(tp, 1, fn)
+            * torch.add(tn, 1, fp)
+            * torch.add(tn, 1, fn)
+        )
+        + sys.float_info.epsilon
+    )
+
+    return torch.div(numerator.sum(), denominator.sum())
+
+
 def MCD(
     predicted: torch.Tensor,
     target: torch.Tensor,

From 7bca7d1a60dd7a4ec715aa196704e8df23f72285 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 12:56:26 -0400
Subject: [PATCH 43/76] using torch epsilon

---
 GANDLF/losses/segmentation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index 9aa9e5b3c..f6b42ead6 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -50,7 +50,7 @@ def mcc(predictions: torch.Tensor, targets: torch.Tensor) -> torch.Tensor:
             * torch.add(tn, 1, fp)
             * torch.add(tn, 1, fn)
         )
-        + sys.float_info.epsilon
+        + torch.finfo(torch.float32).eps
     )
 
     return torch.div(numerator.sum(), denominator.sum())

From cc67266363226ba1e5c812e8f96b3418249ac54b Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:01:33 -0400
Subject: [PATCH 44/76] added 2 types of mcc loss

---
 GANDLF/losses/segmentation.py | 83 ++++++++++++++++++++++++++++++++---
 1 file changed, 76 insertions(+), 7 deletions(-)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index f6b42ead6..bbef68cdd 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -56,10 +56,11 @@ def mcc(predictions: torch.Tensor, targets: torch.Tensor) -> torch.Tensor:
     return torch.div(numerator.sum(), denominator.sum())
 
 
-def MCD(
+def generic_loss_calculator(
     predicted: torch.Tensor,
     target: torch.Tensor,
     num_class: int,
+    loss_criteria: function,
     weights: list = None,
     ignore_class: int = None,
     loss_type: int = 0,
@@ -71,6 +72,7 @@ def MCD(
         predicted (torch.Tensor): Predicted generally by the network
         target (torch.Tensor): Required target label to match the predicted with
         num_class (int): Number of classes (including the background class)
+        loss_criteria (function): Loss function to use
         weights (list, optional): Dice weights for each class (excluding the background class), defaults to None
         ignore_class (int, optional): Class to ignore, defaults to None
         loss_type (int, optional): Type of loss to compute, defaults to 0
@@ -81,11 +83,10 @@ def MCD(
     Returns:
         torch.Tensor: Mean Class Dice score
     """
-
     acc_dice = 0
 
     for i in range(num_class):  # 0 is background
-        currentDice = dice(predicted[:, i, ...], target[:, i, ...])
+        currentDice = loss_criteria(predicted[:, i, ...], target[:, i, ...])
 
         if loss_type == 1:
             currentDice = 1 - currentDice  # subtract from 1 because this is a loss
@@ -108,12 +109,21 @@ def MCD_loss(
     predicted: torch.Tensor, target: torch.Tensor, params: dict
 ) -> torch.Tensor:
     """
-    These weights should be the penalty weights, not dice weights
+    This function computes the Dice loss between two tensors. These weights should be the penalty weights, not dice weights.
+
+    Args:
+        predicted (torch.Tensor): The predicted value by the network.
+        target (torch.Tensor): Required target label to match the predicted with
+        params (dict): Dictionary of parameters
+
+    Returns:
+        torch.Tensor: The computed MCC loss.
     """
-    return MCD(
+    return generic_loss_calculator(
         predicted,
         target,
         len(params["model"]["class_list"]),
+        dice,
         params["weights"],
         None,
         1,
@@ -124,12 +134,71 @@ def MCD_log_loss(
     predicted: torch.Tensor, target: torch.Tensor, params: dict
 ) -> torch.Tensor:
     """
-    These weights should be the penalty weights, not dice weights
+    This function computes the Dice loss between two tensors with log. These weights should be the penalty weights, not dice weights.
+
+    Args:
+        predicted (torch.Tensor): The predicted value by the network.
+        target (torch.Tensor): Required target label to match the predicted with
+        params (dict): Dictionary of parameters
+
+    Returns:
+        torch.Tensor: The computed MCC loss.
+    """
+    return generic_loss_calculator(
+        predicted,
+        target,
+        len(params["model"]["class_list"]),
+        dice,
+        params["weights"],
+        None,
+        2,
+    )
+
+
+def MCD_loss(
+    predicted: torch.Tensor, target: torch.Tensor, params: dict
+) -> torch.Tensor:
+    """
+    This function computes the Matthews Correlation Coefficient (MCC) loss between two tensors. These weights should be the penalty weights, not dice weights.
+
+    Args:
+        predicted (torch.Tensor): The predicted value by the network.
+        target (torch.Tensor): Required target label to match the predicted with
+        params (dict): Dictionary of parameters
+
+    Returns:
+        torch.Tensor: The computed MCC loss.
+    """
+    return generic_loss_calculator(
+        predicted,
+        target,
+        len(params["model"]["class_list"]),
+        mcc,
+        params["weights"],
+        None,
+        1,
+    )
+
+
+def MCC_log_loss(
+    predicted: torch.Tensor, target: torch.Tensor, params: dict
+) -> torch.Tensor:
+    """
+    This function computes the Matthews Correlation Coefficient (MCC) loss between two tensors with log. These weights should be the penalty weights, not dice weights.
+
+    Args:
+        predicted (torch.Tensor): The predicted value by the network.
+        target (torch.Tensor): Required target label to match the predicted with
+        params (dict): Dictionary of parameters
+
+    Returns:
+        torch.Tensor: The computed MCC loss.
     """
-    return MCD(
+    return generic_loss_calculator(
         predicted,
         target,
         len(params["model"]["class_list"]),
+        mcc,
         params["weights"],
         None,
         2,

From 2649ce1e854c181df2cf849e357bc58417402c53 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:02:45 -0400
Subject: [PATCH 45/76] updated global dict

---
 GANDLF/losses/__init__.py | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/GANDLF/losses/__init__.py b/GANDLF/losses/__init__.py
index 4e6d04a86..4779bb87c 100644
--- a/GANDLF/losses/__init__.py
+++ b/GANDLF/losses/__init__.py
@@ -7,6 +7,8 @@
     MCT_loss,
     KullbackLeiblerDivergence,
     FocalLoss,
+    MCC_loss,
+    MCC_log_loss,
 )
 from .regression import CE, CEL, MSE_loss, L1_loss
 from .hybrid import DCCE, DCCE_Logits, DC_Focal
@@ -17,7 +19,14 @@
     "dc": MCD_loss,
     "dice": MCD_loss,
     "dc_log": MCD_log_loss,
+    "dclog": MCD_log_loss,
     "dice_log": MCD_log_loss,
+    "dicelog": MCD_log_loss,
+    "mcc": MCC_loss,
+    "mcc_log": MCC_log_loss,
+    "mcclog": MCC_log_loss,
+    "mathews": MCC_loss,
+    "mathews_log": MCC_log_loss,
     "dcce": DCCE,
     "dcce_logits": DCCE_Logits,
     "ce": CE,

From 5d4eeb6fae8e4eeb109242e96af4c8b0f7ba464a Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:02:54 -0400
Subject: [PATCH 46/76] renamed

---
 GANDLF/losses/segmentation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index bbef68cdd..1992a2310 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -155,7 +155,7 @@ def MCD_log_loss(
     )
 
 
-def MCD_loss(
+def MCC_loss(
     predicted: torch.Tensor, target: torch.Tensor, params: dict
 ) -> torch.Tensor:
     """

From 79c0aba0f999e6a3dfc4346996b10da4d19afa8f Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:03:53 -0400
Subject: [PATCH 47/76] typo fix

---
 GANDLF/losses/segmentation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index 1992a2310..2b2a0238a 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -308,7 +308,7 @@ def FocalLoss(
 
     def _focal_loss(preds, target, gamma, size_average=True):
         """
-        Internal helper function to calcualte focal loss for a single class.
+        Internal helper function to calculate focal loss for a single class.
 
         Args:
             preds (torch.Tensor): predicted generally by the network

From 5efb2407954211c2c71f042327229f692066777d Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:09:19 -0400
Subject: [PATCH 48/76] updated variable names and comments

---
 GANDLF/losses/segmentation.py | 35 +++++++++++++++++++++--------------
 1 file changed, 21 insertions(+), 14 deletions(-)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index 2b2a0238a..25ddbfc60 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -75,7 +75,7 @@ def generic_loss_calculator(
         loss_criteria (function): Loss function to use
         weights (list, optional): Dice weights for each class (excluding the background class), defaults to None
         ignore_class (int, optional): Class to ignore, defaults to None
-        loss_type (int, optional): Type of loss to compute, defaults to 0
+        loss_type (int, optional): Type of loss to compute, defaults to 0. The options are:
             0: no loss, normal dice calculation
             1: dice loss, (1-dice)
             2: log dice, -log(dice)
@@ -83,26 +83,33 @@ def generic_loss_calculator(
     Returns:
         torch.Tensor: Mean Class Dice score
     """
-    acc_dice = 0
+    accumulated_loss = 0
+    # default to a ridiculous value so that it is ignored by default
+    ignore_class = -1e10 if ignore_class is None else ignore_class
 
-    for i in range(num_class):  # 0 is background
-        currentDice = loss_criteria(predicted[:, i, ...], target[:, i, ...])
+    for class_index in range(num_class):
+        if class_index != ignore_class:
+            current_loss = loss_criteria(
+                predicted[:, class_index, ...], target[:, class_index, ...]
+            )
 
-        if loss_type == 1:
-            currentDice = 1 - currentDice  # subtract from 1 because this is a loss
-        elif loss_type == 2:
-            # negative because we want positive losses
-            currentDice = -torch.log(currentDice + torch.finfo(torch.float32).eps)
+            if loss_type == 1:
+                # subtract from 1 because this is a loss
+                current_loss = 1 - current_loss
+            elif loss_type == 2:
+                # negative because we want positive losses, and add epsilon to avoid infinities
+                current_loss = -torch.log(current_loss + torch.finfo(torch.float32).eps)
 
-        if weights is not None:
-            currentDice = currentDice * weights[i]  # multiply by weight
+            # multiply by appropriate weight if provided
+            if weights is not None:
+                current_loss = current_loss * weights[class_index]
 
-        acc_dice += currentDice
+            accumulated_loss += current_loss
 
     if weights is None:
-        acc_dice /= num_class  # we should not be considering 0
+        accumulated_loss /= num_class
 
-    return acc_dice
+    return accumulated_loss
 
 
 def MCD_loss(

From c8bd0bd18255243bd5789fa3763f386249778e16 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:10:48 -0400
Subject: [PATCH 49/76] initialized a default loss

---
 GANDLF/losses/segmentation.py | 9 +++++----
 1 file changed, 5 insertions(+), 4 deletions(-)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index 25ddbfc60..36e9a3797 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -93,12 +93,13 @@ def generic_loss_calculator(
                 predicted[:, class_index, ...], target[:, class_index, ...]
             )
 
-            if loss_type == 1:
-                # subtract from 1 because this is a loss
-                current_loss = 1 - current_loss
-            elif loss_type == 2:
+            # subtract from 1 because this is supposed to be a loss
+            default_loss = 1 - current_loss
+            if loss_type == 2 or loss_type == "log":
                 # negative because we want positive losses, and add epsilon to avoid infinities
                 current_loss = -torch.log(current_loss + torch.finfo(torch.float32).eps)
+            else:
+                current_loss = default_loss
 
             # multiply by appropriate weight if provided
             if weights is not None:

From 99d5c7ffdd38c686e8f5af90b6c9f8752b890f45 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:17:55 -0400
Subject: [PATCH 50/76] black .

---
 GANDLF/utils/modelio.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index e49c59cee..60a873006 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -99,6 +99,7 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
             import openvino as ov
             from openvino.tools.mo import convert_model
             from openvino.runtime import get_version
+
             openvino_present = False
             # check for the correct openvino version to prevent inadvertent api breaks
             if "2023.0.1" in get_version():

From 1513cca7213ac1799b71dd0c424c59d2529319b1 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:18:07 -0400
Subject: [PATCH 51/76] this is causing problems

---
 GANDLF/losses/segmentation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/losses/segmentation.py b/GANDLF/losses/segmentation.py
index 36e9a3797..6b4369df6 100644
--- a/GANDLF/losses/segmentation.py
+++ b/GANDLF/losses/segmentation.py
@@ -60,7 +60,7 @@ def generic_loss_calculator(
     predicted: torch.Tensor,
     target: torch.Tensor,
     num_class: int,
-    loss_criteria: function,
+    loss_criteria,
     weights: list = None,
     ignore_class: int = None,
     loss_type: int = 0,

From 113f8a3cdeaaae6db8d494fdc1a9c754d9b9d185 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:18:22 -0400
Subject: [PATCH 52/76] added new losses to test

---
 testing/test_full.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/testing/test_full.py b/testing/test_full.py
index 73ad8af65..28e2f00df 100644
--- a/testing/test_full.py
+++ b/testing/test_full.py
@@ -1250,7 +1250,9 @@ def get_parameters_after_alteration(loss_type: str) -> dict:
         "dcce_logits", 
         "tversky",
         "focal", 
-        "dc_focal"]:
+        "dc_focal",
+        "mcc"
+        "mcc_log"]:
         parameters, training_data = get_parameters_after_alteration(loss_type)
         sanitize_outputDir()
         TrainingManager(

From 58aea3e7094e240ca5f809bc49499fe6d31a3274 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:18:46 -0400
Subject: [PATCH 53/76] no need for this variable

---
 GANDLF/utils/modelio.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/GANDLF/utils/modelio.py b/GANDLF/utils/modelio.py
index 60a873006..92f4a404f 100644
--- a/GANDLF/utils/modelio.py
+++ b/GANDLF/utils/modelio.py
@@ -87,8 +87,6 @@ def optimize_and_save_model(model, params, path, onnx_export=True):
                     input_names=["input"],
                     output_names=["output"],
                 )
-
-            ov_output_dir = os.path.dirname(os.path.abspath(path))
         except RuntimeWarning:
             print("WARNING: Cannot export to ONNX model.")
             return

From 2852131cc83a9d91a4addf3782b3161f67dd9681 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:19:46 -0400
Subject: [PATCH 54/76] added doc

---
 docs/customize.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/customize.md b/docs/customize.md
index 24347f4cf..ff4b71f2c 100644
--- a/docs/customize.md
+++ b/docs/customize.md
@@ -39,7 +39,7 @@ This file contains mid-level information regarding various parameters that can b
 - Defined in the `loss_function` parameter of the model configuration.
 - By passing `weighted_loss: True`, the loss function will be weighted by the inverse of the class frequency.
 - This parameter controls the function which the model is trained. All options can be found [here](https://github.com/mlcommons/GaNDLF/blob/master/GANDLF/losses/__init__.py). Some examples are:
-    - Segmentation: dice (`dice` or `dc`), dice and cross entropy (`dcce`), focal loss (`focal`), dice and focal (`dc_focal`)
+    - Segmentation: dice (`dice` or `dc`), dice and cross entropy (`dcce`), focal loss (`focal`), dice and focal (`dc_focal`), mathews (`mcc`)
     - Classification/regression: mean squared error (`mse`)
     - And many more.
 

From 8c5808b20edb22e6dad5db8dffff47bc6d1c30fe Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:20:12 -0400
Subject: [PATCH 55/76] updated doc

---
 docs/customize.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/customize.md b/docs/customize.md
index ff4b71f2c..f6b9df16e 100644
--- a/docs/customize.md
+++ b/docs/customize.md
@@ -39,7 +39,7 @@ This file contains mid-level information regarding various parameters that can b
 - Defined in the `loss_function` parameter of the model configuration.
 - By passing `weighted_loss: True`, the loss function will be weighted by the inverse of the class frequency.
 - This parameter controls the function which the model is trained. All options can be found [here](https://github.com/mlcommons/GaNDLF/blob/master/GANDLF/losses/__init__.py). Some examples are:
-    - Segmentation: dice (`dice` or `dc`), dice and cross entropy (`dcce`), focal loss (`focal`), dice and focal (`dc_focal`), mathews (`mcc`)
+    - Segmentation: dice (`dice` or `dc`), dice and cross entropy (`dcce`), focal loss (`focal`), dice and focal (`dc_focal`), matthews (`mcc`)
     - Classification/regression: mean squared error (`mse`)
     - And many more.
 

From b26360d1ea10e2f7581e54d7c20e393b16476a5c Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 13:21:04 -0400
Subject: [PATCH 56/76] updated all options

---
 samples/config_all_options.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/samples/config_all_options.yaml b/samples/config_all_options.yaml
index 0c0d405db..0627b45af 100644
--- a/samples/config_all_options.yaml
+++ b/samples/config_all_options.yaml
@@ -110,7 +110,7 @@ scheduler:
     max_lr: 1,
   }
 # Set which loss function you want to use - options : 'dc' - for dice only, 'dcce' - for sum of dice and CE and you can guess the next (only lower-case please)
-# options: dc (dice only), dc_log (-log of dice), ce (), dcce (sum of dice and ce), mse () ...
+# options: dc (dice only), dc_log (-log of dice), ce (), dcce (sum of dice and ce), focal/dc_focal, mcc/mcc_log, mse () ...
 # mse is the MSE defined by torch and can define a variable 'reduction'; see https://pytorch.org/docs/stable/generated/torch.nn.MSELoss.html#torch.nn.MSELoss
 # focal is the focal loss and can define 2 variables: gamma and size_average
 # use mse_torch for regression/classification problems and dice for segmentation

From d68062dbfb76a5135a29c9b9e11933c012df1a49 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Sat, 5 Aug 2023 20:02:14 -0400
Subject: [PATCH 57/76] better formatting

---
 docs/usage.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/usage.md b/docs/usage.md
index ac047d07c..26bf777d7 100644
--- a/docs/usage.md
+++ b/docs/usage.md
@@ -172,6 +172,7 @@ GaNDLF requires a YAML-based configuration that controls various aspects of the
 - [Classification example](https://github.com/mlcommons/GaNDLF/blob/master/samples/config_classification.yaml)
 
 **Notes**: 
+
 - More details on the configuration options are available in the [customization page](customize.md).
 - Ensure that the configuration has valid syntax by checking the file using any YAML validator such as [yamlchecker.com](https://yamlchecker.com/) or [yamlvalidator.com](https://yamlvalidator.com/) **before** trying to train.
 

From f493d66d5b95f62f2cb7201878beb46e288c1c52 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Sun, 6 Aug 2023 10:01:32 -0400
Subject: [PATCH 58/76] updated checkout and renamed job names for clarity

---
 .github/workflows/openfl-test.yml | 5 ++---
 .github/workflows/python-test.yml | 4 ++--
 2 files changed, 4 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/openfl-test.yml b/.github/workflows/openfl-test.yml
index c33f10c79..cd3ed6628 100644
--- a/.github/workflows/openfl-test.yml
+++ b/.github/workflows/openfl-test.yml
@@ -11,7 +11,7 @@ on:
     
 
 jobs:
-  build:
+  openfl-test:
 
     runs-on: ubuntu-latest
 
@@ -25,7 +25,7 @@ jobs:
         sudo rm -rf "$ANDROID_SDK_ROOT"
         df -h
     - name: Checkout
-      uses: actions/checkout@v2
+      uses: actions/checkout@v3
     
     # Use changed-files-specific action to collect file changes.
     # The following commented condition applied to a step will run that step only if non-docs files have changed.
@@ -90,7 +90,6 @@ jobs:
         cd openfl
         git fetch --tags
         git checkout $(git describe --tags --abbrev=0)
-        # pip install "tensorboardX!=2.6.2" # https://github.com/lanpa/tensorboardX/issues/716
         sed -i -e 's/protobuf==3.19.6/protobuf/g' setup.py ## this should NOT be there
         pip install -e .
         cd ..
diff --git a/.github/workflows/python-test.yml b/.github/workflows/python-test.yml
index 5364dc8df..baefad34e 100644
--- a/.github/workflows/python-test.yml
+++ b/.github/workflows/python-test.yml
@@ -11,7 +11,7 @@ on:
     
 
 jobs:
-  build:
+  full-test:
 
     runs-on: ubuntu-latest
 
@@ -25,7 +25,7 @@ jobs:
         sudo rm -rf "$ANDROID_SDK_ROOT"
         df -h
     - name: Checkout
-      uses: actions/checkout@v2
+      uses: actions/checkout@v3
     
     # Use changed-files-specific action to collect file changes.
     # The following commented condition applied to a step will run that step only if non-docs files have changed.

From a8308f543a56866c1c4284547b9b6996b1610292 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Sun, 6 Aug 2023 10:05:25 -0400
Subject: [PATCH 59/76] updated checkout version and test name for clarity

---
 .github/workflows/openfl-test.yml | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/openfl-test.yml b/.github/workflows/openfl-test.yml
index c33f10c79..cd3ed6628 100644
--- a/.github/workflows/openfl-test.yml
+++ b/.github/workflows/openfl-test.yml
@@ -11,7 +11,7 @@ on:
     
 
 jobs:
-  build:
+  openfl-test:
 
     runs-on: ubuntu-latest
 
@@ -25,7 +25,7 @@ jobs:
         sudo rm -rf "$ANDROID_SDK_ROOT"
         df -h
     - name: Checkout
-      uses: actions/checkout@v2
+      uses: actions/checkout@v3
     
     # Use changed-files-specific action to collect file changes.
     # The following commented condition applied to a step will run that step only if non-docs files have changed.
@@ -90,7 +90,6 @@ jobs:
         cd openfl
         git fetch --tags
         git checkout $(git describe --tags --abbrev=0)
-        # pip install "tensorboardX!=2.6.2" # https://github.com/lanpa/tensorboardX/issues/716
         sed -i -e 's/protobuf==3.19.6/protobuf/g' setup.py ## this should NOT be there
         pip install -e .
         cd ..

From 66627d23dfb769b5ac63d03f5e8d9c3b6930e197 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Sun, 6 Aug 2023 10:05:54 -0400
Subject: [PATCH 60/76] updated checkout version and test name for clarity

---
 .github/workflows/python-test.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/python-test.yml b/.github/workflows/python-test.yml
index 5364dc8df..baefad34e 100644
--- a/.github/workflows/python-test.yml
+++ b/.github/workflows/python-test.yml
@@ -11,7 +11,7 @@ on:
     
 
 jobs:
-  build:
+  full-test:
 
     runs-on: ubuntu-latest
 
@@ -25,7 +25,7 @@ jobs:
         sudo rm -rf "$ANDROID_SDK_ROOT"
         df -h
     - name: Checkout
-      uses: actions/checkout@v2
+      uses: actions/checkout@v3
     
     # Use changed-files-specific action to collect file changes.
     # The following commented condition applied to a step will run that step only if non-docs files have changed.

From bd8d9845c6351d882b85137466a96d9086d2885a Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Sun, 6 Aug 2023 10:08:22 -0400
Subject: [PATCH 61/76] updated defaults for sgd

---
 GANDLF/optimizers/wrap_torch.py | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/GANDLF/optimizers/wrap_torch.py b/GANDLF/optimizers/wrap_torch.py
index fe91be096..9a0455ec5 100644
--- a/GANDLF/optimizers/wrap_torch.py
+++ b/GANDLF/optimizers/wrap_torch.py
@@ -28,10 +28,10 @@ def sgd(parameters):
     optimizer = SGD(
         parameters["model_parameters"],
         lr=parameters.get("learning_rate"),
-        momentum=parameters["optimizer"].get("momentum", 0.9),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        momentum=parameters["optimizer"].get("momentum", 0.99),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
         dampening=parameters["optimizer"].get("dampening", 0),
-        nesterov=parameters["optimizer"].get("Nesterov", False),
+        nesterov=parameters["optimizer"].get("nesterov", True),
     )
 
     return optimizer
@@ -55,7 +55,7 @@ def asgd(parameters):
         alpha=parameters["optimizer"].get("alpha", 0.75),
         t0=parameters["optimizer"].get("t0", 1e6),
         lambd=parameters["optimizer"].get("lambd", 1e-4),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
     )
 
 
@@ -177,7 +177,7 @@ def adadelta(parameters):
         lr=parameters.get("learning_rate"),
         rho=parameters["optimizer"].get("rho", 0.9),
         eps=parameters["optimizer"].get("eps", 1e-6),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
     )
 
 
@@ -199,7 +199,7 @@ def adagrad(parameters):
         lr=parameters.get("learning_rate"),
         lr_decay=parameters["optimizer"].get("lr_decay", 0),
         eps=parameters["optimizer"].get("eps", 1e-6),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
     )
 
 
@@ -222,7 +222,7 @@ def rmsprop(parameters):
         eps=parameters["optimizer"].get("eps", 1e-8),
         centered=parameters["optimizer"].get("centered", False),
         momentum=parameters["optimizer"].get("momentum", 0),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
     )
 
 
@@ -242,6 +242,6 @@ def radam(parameters):
         lr=parameters.get("learning_rate"),
         betas=parameters["optimizer"].get("betas", (0.9, 0.999)),
         eps=parameters["optimizer"].get("eps", 1e-8),
-        weight_decay=parameters["optimizer"].get("weight_decay", 0),
+        weight_decay=parameters["optimizer"].get("weight_decay", 3e-05),
         foreach=parameters["optimizer"].get("foreach", None),
     )

From 5fb7794b06f531df16c1b93324f0d7f7718958b7 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Sun, 6 Aug 2023 12:00:10 -0400
Subject: [PATCH 62/76] formatting update

---
 docs/usage.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/docs/usage.md b/docs/usage.md
index 26bf777d7..701e899f9 100644
--- a/docs/usage.md
+++ b/docs/usage.md
@@ -157,6 +157,7 @@ The following command shows how the script works:
 ```
 
 **Notes**:
+
 - For classification/regression, add a column called `ValueToPredict`. Currently, we are supporting only a single value prediction per model.
 - `SubjectID` or `PatientName` is used to ensure that the randomized split is done per-subject rather than per-image.
 - For data arrangement different to what is described above, a customized script will need to be written to generate the CSV, or you can enter the data manually into the CSV. 

From 34738842fffe1002f93c36433d840d52cfbb6b63 Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Mon, 7 Aug 2023 11:53:59 -0400
Subject: [PATCH 63/76] trying update

---
 .github/workflows/openfl-test.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/openfl-test.yml b/.github/workflows/openfl-test.yml
index cd3ed6628..0b59413f2 100644
--- a/.github/workflows/openfl-test.yml
+++ b/.github/workflows/openfl-test.yml
@@ -69,6 +69,7 @@ jobs:
     - name: Install dependencies and package
       if: steps.changed-files-specific.outputs.only_modified == 'false' # Run on any non-docs change
       run: |
+        sudo apt-get update
         sudo apt-get install libvips libvips-tools -y
         python -m pip install --upgrade pip
         python -m pip install wheel

From e95f6b17d31cabb8a2caa49efe2350f19284b1be Mon Sep 17 00:00:00 2001
From: Sarthak Pati <sarthak.pati@hotmail.com>
Date: Mon, 7 Aug 2023 11:56:57 -0400
Subject: [PATCH 64/76] apparently manual update is needed now

---
 .github/workflows/python-test.yml | 1 +
 1 file changed, 1 insertion(+)

diff --git a/.github/workflows/python-test.yml b/.github/workflows/python-test.yml
index baefad34e..112bcce1b 100644
--- a/.github/workflows/python-test.yml
+++ b/.github/workflows/python-test.yml
@@ -69,6 +69,7 @@ jobs:
     - name: Install dependencies and package
       if: steps.changed-files-specific.outputs.only_modified == 'false' # Run on any non-docs change
       run: |
+        sudo apt-get update
         sudo apt-get install libvips libvips-tools -y
         python -m pip install --upgrade pip
         python -m pip install wheel

From b68b0ee7267f5e90df01ce6f4ee5b304e8e926f6 Mon Sep 17 00:00:00 2001
From: sarthakpati <sarthak.pati@hotmail.com>
Date: Mon, 7 Aug 2023 15:40:56 -0400
Subject: [PATCH 65/76] was missing a comma

---
 testing/test_full.py | 17 ++++++++++-------
 1 file changed, 10 insertions(+), 7 deletions(-)

diff --git a/testing/test_full.py b/testing/test_full.py
index 28e2f00df..3fc1e28f2 100644
--- a/testing/test_full.py
+++ b/testing/test_full.py
@@ -1213,6 +1213,7 @@ def test_train_metrics_regression_rad_2d(device):
 
 def test_train_losses_segmentation_rad_2d(device):
     print("23: Starting 2D Rad segmentation tests for losses")
+
     # healper function to read and parse yaml and return parameters
     def get_parameters_after_alteration(loss_type: str) -> dict:
         parameters = parseConfig(
@@ -1242,17 +1243,19 @@ def get_parameters_after_alteration(loss_type: str) -> dict:
         parameters["model"]["print_summary"] = False
         parameters = populate_header_in_parameters(parameters, parameters["headers"])
         return parameters, training_data
+
     # loop through selected models and train for single epoch
     for loss_type in [
-        "dc", 
-        "dc_log", 
-        "dcce", 
-        "dcce_logits", 
+        "dc",
+        "dc_log",
+        "dcce",
+        "dcce_logits",
         "tversky",
-        "focal", 
+        "focal",
         "dc_focal",
-        "mcc"
-        "mcc_log"]:
+        "mcc",
+        "mcc_log",
+    ]:
         parameters, training_data = get_parameters_after_alteration(loss_type)
         sanitize_outputDir()
         TrainingManager(

From 7964b08b5a79a8e066fd5ffdbd6f3482413367ca Mon Sep 17 00:00:00 2001
From: hasan7n <hasankassim7@hotmail.com>
Date: Wed, 9 Aug 2023 14:54:42 +0200
Subject: [PATCH 66/76] allow custom entrypoint script for model deploy

---
 GANDLF/cli/deploy.py | 16 ++++++++++++++--
 gandlf_deploy        |  4 ++--
 2 files changed, 16 insertions(+), 4 deletions(-)

diff --git a/GANDLF/cli/deploy.py b/GANDLF/cli/deploy.py
index 9997289f8..498806fd5 100644
--- a/GANDLF/cli/deploy.py
+++ b/GANDLF/cli/deploy.py
@@ -35,6 +35,7 @@ def run_deployment(
         outputdir (str): The path to the output directory.
         target (str): The target to deploy to.
         mlcube_type (str): Either 'model' or 'metrics'
+        entrypoint_script (str): The path of entrypoint script. Only used for metrics and inference
         configfile (str, Optional): The path to the configuration file. Required for models
         modeldir (str, Optional): The path to the model directory. Required for models
         requires_gpu (str, Optional): Whether the model requires GPU. Required for models
@@ -98,6 +99,7 @@ def deploy_docker_mlcube(
     Args:
         mlcubedir (str): The path to the mlcube directory.
         outputdir (str): The path to the output directory.
+        entrypoint_script (str): The path of entrypoint script. Only used for metrics and inference
         config (str, Optional): The path to the configuration file. Required for models
         modeldir (str, Optional): The path to the model directory. Required for models
         requires_gpu (str, Optional): Whether the model requires GPU. Required for models
@@ -124,7 +126,9 @@ def deploy_docker_mlcube(
     # First grab the existing the mlcube config
     if modeldir is not None:
         # we can use that as an indicator if we are doing model or metrics deployment
-        mlcube_config = get_model_mlcube_config(mlcube_config_file, requires_gpu)
+        mlcube_config = get_model_mlcube_config(
+            mlcube_config_file, requires_gpu, entrypoint_script
+        )
     else:
         mlcube_config = get_metrics_mlcube_config(mlcube_config_file, entrypoint_script)
 
@@ -252,13 +256,14 @@ def get_metrics_mlcube_config(mlcube_config_file, entrypoint_script):
     return mlcube_config
 
 
-def get_model_mlcube_config(mlcube_config_file, requires_gpu):
+def get_model_mlcube_config(mlcube_config_file, requires_gpu, entrypoint_script):
     """
     This function returns the mlcube config for the model.
 
     Args:
         mlcube_config_file (str): Path to mlcube config file.
         requires_gpu (bool): Whether the model requires GPU.
+        entrypoint_script (str): The path of entrypoint script. Only used for infer task
     """
     mlcube_config = None
     with open(mlcube_config_file, "r") as f:
@@ -305,6 +310,13 @@ def get_model_mlcube_config(mlcube_config_file, requires_gpu):
             "--device cpu", "--device cuda"
         )
 
+    if entrypoint_script:
+        # modify the infer entrypoint to run a custom script.
+        device = "cuda" if requires_gpu else "cpu"
+        mlcube_config["tasks"]["infer"][
+            "entrypoint"
+        ] = f"python3.8 /entrypoint.py --device {device}"
+
     return mlcube_config
     # Duplicate training task into one from reset (must be explicit) and one that resumes with new data
     # In either case, the embedded model will not change persistently.
diff --git a/gandlf_deploy b/gandlf_deploy
index 6495c7005..cebb6c001 100644
--- a/gandlf_deploy
+++ b/gandlf_deploy
@@ -51,7 +51,7 @@ if __name__ == "__main__":
         "--mlcube-type",
         metavar="",
         type=str,
-        help="The mlcube type. Valid inputs are: " + ", ".join(deploy_targets) + " .",
+        help="The mlcube type. Valid inputs are: " + ", ".join(mlcube_types) + " .",
         required=True,
     )
     parser.add_argument(
@@ -83,7 +83,7 @@ if __name__ == "__main__":
         "--entrypoint",
         metavar="",
         type=str,
-        help="An optional custom python entrypoint script to use instead of the default specified in mlcube.yaml.",
+        help="An optional custom python entrypoint script to use instead of the default specified in mlcube.yaml. (Only for inference and metrics)",
         default=None,
     )
 

From 8c1543c44427390e5254104afa1c39c3f65a872d Mon Sep 17 00:00:00 2001
From: hasan7n <hasankassim7@hotmail.com>
Date: Wed, 9 Aug 2023 14:55:29 +0200
Subject: [PATCH 67/76] modify templates of mlcube.yaml

---
 mlcube/metrics_mlcube/mlcube_medperf.yaml | 2 +-
 mlcube/model_mlcube/mlcube_medperf.yaml   | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/mlcube/metrics_mlcube/mlcube_medperf.yaml b/mlcube/metrics_mlcube/mlcube_medperf.yaml
index 4aa9b7cd7..29cc0cf02 100644
--- a/mlcube/metrics_mlcube/mlcube_medperf.yaml
+++ b/mlcube/metrics_mlcube/mlcube_medperf.yaml
@@ -21,7 +21,7 @@ platform:
 
 docker:
   # The image tag that will be built/pulled/used. Change to suit your organization/model:version.
-  image: mlcommons/gandlf:0.0.1
+  image: mlcommons/gandlf-metrics:0.0.1
   
   ## Generally, these build options will only be needed by GaNDLF maintainers.
   # Docker build context relative to $MLCUBE_ROOT. (gandlf_deploy can handle this automatically.)
diff --git a/mlcube/model_mlcube/mlcube_medperf.yaml b/mlcube/model_mlcube/mlcube_medperf.yaml
index ce7e02dc1..c4d94cbf8 100644
--- a/mlcube/model_mlcube/mlcube_medperf.yaml
+++ b/mlcube/model_mlcube/mlcube_medperf.yaml
@@ -24,13 +24,13 @@ platform:
 
 docker:
   # The image tag that will be built/pulled/used. Change to suit your organization/model:version.
-  image: mlcommons/gandlf:0.0.1
+  image: mlcommons/gandlf-model:0.0.1
   
   ## Generally, these build options will only be needed by GaNDLF maintainers.
   # Docker build context relative to $MLCUBE_ROOT. (gandlf_deploy can handle this automatically.)
   build_context: "../"
   # Docker file name within docker build context. Any "Dockerfile-*" in the GaNDLF source repo is valid.
-  build_file: "Dockerfile-CUDA11.6"
+  build_file: "Dockerfile-CPU"
   
   # These settings should usually be set by global MLCube configuration, generally not per-deployment.
   # However, some sane defaults (for Docker >19.03) are here:

From 73bdb11f48f799dcffd26f3ae377d22e434ca3c9 Mon Sep 17 00:00:00 2001
From: hasan7n <hasankassim7@hotmail.com>
Date: Wed, 9 Aug 2023 14:55:45 +0200
Subject: [PATCH 68/76] add custom entrypoint example

---
 .../getting_started_3d_rad_seg.py             | 28 ++++------
 .../getting_started_3d_rad_seg.py             | 56 +++++++++++++++++++
 .../example_custom_entrypoint/template.py     | 47 ++++++++++++++++
 3 files changed, 115 insertions(+), 16 deletions(-)
 create mode 100644 mlcube/model_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py
 create mode 100644 mlcube/model_mlcube/example_custom_entrypoint/template.py

diff --git a/mlcube/metrics_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py b/mlcube/metrics_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py
index f631f2091..26f5083a2 100644
--- a/mlcube/metrics_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py
+++ b/mlcube/metrics_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py
@@ -7,21 +7,18 @@
 def create_csv(predictions, labels):
     """This function expects `predictions` to be structured in a certain way:
     it should contain the following paths: `testing/<subID>/<subID>_seg.nii.gz`
-    `labels` is expected to have a `data.csv` file containing relative paths of
-    labels"""
+    where <subID> is an integer not padded with zeros.`labels` is expected to have
+    a list of folders, each containing a 'mask.nii.gz'. Names of the folders are subject
+    IDs (integers padded with zeros to have three digit places)."""
 
-    # read and parse expected labels dict
-    labels_data_csv = os.path.join(labels, "data.csv")
-    labels_df = pd.read_csv(labels_data_csv)
-    for col in labels_df:
-        if col.lower() == "subjectid":
-            subjectid_header = col
-        if col.lower() == "label":
-            label_header = col
-    labels_records = labels_df.to_dict("records")
-    labels_dict = {
-        int(rec[subjectid_header]): rec[label_header] for rec in labels_records
-    }
+    # read and parse expected labels
+    labels_dict = {}
+    for subjectID in os.listdir(labels):
+        folder_path = os.path.join(labels, subjectID)
+        if not os.path.isdir(folder_path):
+            continue
+        label_path = os.path.join(folder_path, "mask.nii.gz")
+        labels_dict[int(subjectID)] = label_path
 
     # generate data input dict
     input_data = []
@@ -31,7 +28,6 @@ def create_csv(predictions, labels):
         )
         pred_path = os.path.abspath(pred_path)
         label_path = labels_dict[int(subjectID)]
-        label_path = os.path.join(labels, label_path)
         label_path = os.path.abspath(label_path)
         prediction_record = {
             "SubjectID": subjectID,
@@ -41,7 +37,7 @@ def create_csv(predictions, labels):
         input_data.append(prediction_record)
 
     input_data_df = pd.DataFrame(input_data)
-    input_data_df.to_csv("./data.csv")
+    input_data_df.to_csv("./data.csv", index=False)
 
 
 def run_gandlf(output_path, parameters_file):
diff --git a/mlcube/model_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py b/mlcube/model_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py
new file mode 100644
index 000000000..182489219
--- /dev/null
+++ b/mlcube/model_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py
@@ -0,0 +1,56 @@
+import os
+import argparse
+import sys
+import pandas as pd
+
+
+def create_csv(data_path):
+    """This function expects `data_path` to be structured in a certain way:
+    it should contain a list of folders: each one contains a 'image.nii.gz'.
+    """
+    input_data = []
+    for subjectID in os.listdir(data_path):
+        folder_path = os.path.join(data_path, subjectID)
+        if not os.path.isdir(folder_path):
+            continue
+        image_path = os.path.join(folder_path, "image.nii.gz")
+        image_path = os.path.abspath(image_path)
+        record = {
+            "SubjectID": subjectID,
+            "Channel_0": image_path,
+        }
+        input_data.append(record)
+
+    input_data_df = pd.DataFrame(input_data)
+    input_data_df.to_csv("./data.csv", index=False)
+
+
+def run_gandlf(output_path, device):
+    """
+    A function that calls GaNDLF's run command with the previously created csv.
+
+    Args:
+        output_path (str): The path to the output file/folder
+        device (str): device to run on (i.e. CPU or GPU)
+    """
+    exit_status = os.system(
+        "python3.8 gandlf_run --train False "
+        f"--device {device} --config /embedded_config.yml "
+        f"--modeldir /embedded_model/ -i ./data.csv -o {output_path}"
+    )
+    exit_code = os.WEXITSTATUS(exit_status)
+    sys.exit(exit_code)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--data_path", metavar="", type=str, required=True)
+    parser.add_argument("--output_path", metavar="", type=str, default=None)
+    parser.add_argument(
+        "--device", metavar="", type=str, required=True, choices=["cpu", "cuda"]
+    )
+
+    args = parser.parse_args()
+
+    create_csv(args.data_path)
+    run_gandlf(args.output_path, args.device)
diff --git a/mlcube/model_mlcube/example_custom_entrypoint/template.py b/mlcube/model_mlcube/example_custom_entrypoint/template.py
new file mode 100644
index 000000000..b0a676039
--- /dev/null
+++ b/mlcube/model_mlcube/example_custom_entrypoint/template.py
@@ -0,0 +1,47 @@
+"""If input folder to the MLCube does not contain a csv file that defines the data cases,
+a custom entrypoint is needed to create a temporary csv file before calling GaNDLF's run command.
+This script should expect the same arguments passed to the command `mlcube run --task infer`,
+i.e. it should expect the inputs and outputs defined in `mlcube.yaml` in the `infer` task.
+Note that the device argument will be set by gandlf_deploy (gandlf_deploy will run the entrypoint
+with --device)."""
+
+import os
+import argparse
+import sys
+
+
+def create_csv(data_path):
+    """A function that creates a ./data.csv file from input folder."""
+    # Add your logic here
+    raise NotImplementedError
+
+
+def run_gandlf(output_path, device):
+    """
+    A function that calls GaNDLF's generate metrics command with the previously created csv.
+
+    Args:
+        output_path (str): The path to the output file/folder
+        parameters_file (str): The path to the parameters file
+    """
+    exit_status = os.system(
+        "python3.8 gandlf_run --train False "
+        f"--device {device} --config /embedded_config.yml "
+        f"--modeldir /embedded_model/ -i ./data.csv -o {output_path}"
+    )
+    exit_code = os.WEXITSTATUS(exit_status)
+    sys.exit(exit_code)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--data_path", metavar="", type=str, required=True)
+    parser.add_argument("--output_path", metavar="", type=str, default=None)
+    parser.add_argument(
+        "--device", metavar="", type=str, required=True, choices=["cpu", "cuda"]
+    )
+
+    args = parser.parse_args()
+
+    create_csv(args.data_path)
+    run_gandlf(args.output_path, args.device)

From 30fa96cd3a07c1270bc8e7557d59712c9ff75d12 Mon Sep 17 00:00:00 2001
From: hasan7n <hasankassim7@hotmail.com>
Date: Wed, 9 Aug 2023 14:55:55 +0200
Subject: [PATCH 69/76] add tests

---
 .github/workflows/mlcube-test.yml |  82 ++++++++++++++++++++++
 testing/test_deploy.sh            | 112 ++++++++++++++++++++++++++++++
 2 files changed, 194 insertions(+)
 create mode 100644 .github/workflows/mlcube-test.yml
 create mode 100644 testing/test_deploy.sh

diff --git a/.github/workflows/mlcube-test.yml b/.github/workflows/mlcube-test.yml
new file mode 100644
index 000000000..8306011f8
--- /dev/null
+++ b/.github/workflows/mlcube-test.yml
@@ -0,0 +1,82 @@
+# This workflow will test gandlf_deploy for model and metrics MLCubes
+
+name: CI-PyTest
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    branches: [ master ]
+    
+
+jobs:
+  test-deploy:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Free space
+      run: |
+        df -h
+        sudo rm -rf /opt/ghc
+        sudo rm -rf "/usr/local/share/boost"
+        sudo rm -rf "$AGENT_TOOLSDIRECTORY"
+        sudo rm -rf "$ANDROID_SDK_ROOT"
+        df -h
+    - name: Checkout
+      uses: actions/checkout@v3
+    
+    # Use changed-files-specific action to collect file changes.
+    # The following commented condition applied to a step will run that step only if non-docs files have changed.
+    # It should be applied to all functionality-related steps.
+    # if: steps.changed-files-specific.outputs.only_modified == 'false'
+    - name: Detect and screen file changes
+      id: changed-files-specific
+      uses: tj-actions/changed-files@v34
+      with:
+          files: |
+            .github/*.md
+            .github/ISSUE_TEMPLATE/*.md
+            .github/workflows/devcontainer.yml
+            .github/workflows/docker-image.yml
+            .devcontainer/**
+            docs/**
+            mlcube/**
+            *.md
+            LICENSE
+            Dockerfile-*
+
+    - name: Summarize docs and non-docs modifications
+      run: |
+        echo "List of docs files that have changed: ${{ steps.changed-files-specific.outputs.all_modified_files }}"
+        echo "Changed non-docs files: ${{ steps.changed-files-specific.outputs.other_modified_files }}"
+    
+    # This second step is unnecessary but highly recommended because
+    # It will cache database and saves time re-downloading it if database isn't stale.
+    - name: Cache pip
+      uses: actions/cache@v3
+      with:
+        path: ~/.cache/pip
+        key: ${{ runner.os }}-pip-${{ hashFiles('**/setup.py') }}
+        restore-keys: |
+          ${{ runner.os }}-pip-
+    - name: Set up Python 3.8
+      if: steps.changed-files-specific.outputs.only_modified == 'false' # Run on any non-docs change
+      uses: actions/setup-python@v4
+      with:
+        python-version: 3.8
+    - name: Install dependencies and package
+      if: steps.changed-files-specific.outputs.only_modified == 'false' # Run on any non-docs change
+      run: |
+        sudo apt-get update
+        sudo apt-get install libvips libvips-tools -y
+        python -m pip install --upgrade pip
+        python -m pip install wheel
+        python -m pip install openvino-dev==2023.0.1 mlcube_docker
+        pip install torch==1.13.1+cpu torchvision==0.14.1+cpu torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cpu
+        pip install -e .
+    - name: Run mlcube deploy tests
+      working-directory: ./testing
+      if: steps.changed-files-specific.outputs.only_modified == 'false' # Run on any non-docs change
+      run: |
+        sh test_deploy.sh
diff --git a/testing/test_deploy.sh b/testing/test_deploy.sh
new file mode 100644
index 000000000..43ff7d531
--- /dev/null
+++ b/testing/test_deploy.sh
@@ -0,0 +1,112 @@
+###############
+#### Setup ####
+###############
+
+MODEL_MLCUBE_TEMPLATE=../../mlcube/model_mlcube/mlcube_medperf.yaml
+METRICS_MLCUBE_TEMPLATE=../../mlcube/metrics_mlcube/mlcube_medperf.yaml
+
+MODEL_MLCUBE_ENTRYPOINT=../../mlcube/model_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py
+METRICS_MLCUBE_ENTRYPOINT=../../mlcube/metrics_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py
+
+# Create a workspace
+mkdir -p test_deploy
+cd test_deploy
+
+# Download the data
+FILENAME=y8162xkq1zz5555ye3pwadry2m2e39bs.zip
+wget https://upenn.box.com/shared/static/$FILENAME
+unzip $FILENAME
+mv data/3d_rad_segmentation .
+rm $FILENAME
+rm -rf data
+
+# Setup the data CSV for training
+echo "SubjectID,Channel_0,Label
+001,3d_rad_segmentation/001/image.nii.gz,3d_rad_segmentation/001/mask.nii.gz
+002,3d_rad_segmentation/002/image.nii.gz,3d_rad_segmentation/002/mask.nii.gz
+003,3d_rad_segmentation/003/image.nii.gz,3d_rad_segmentation/003/mask.nii.gz
+004,3d_rad_segmentation/004/image.nii.gz,3d_rad_segmentation/004/mask.nii.gz
+005,3d_rad_segmentation/005/image.nii.gz,3d_rad_segmentation/005/mask.nii.gz
+006,3d_rad_segmentation/006/image.nii.gz,3d_rad_segmentation/006/mask.nii.gz
+007,3d_rad_segmentation/007/image.nii.gz,3d_rad_segmentation/007/mask.nii.gz
+008,3d_rad_segmentation/008/image.nii.gz,3d_rad_segmentation/008/mask.nii.gz
+009,3d_rad_segmentation/009/image.nii.gz,3d_rad_segmentation/009/mask.nii.gz
+010,3d_rad_segmentation/010/image.nii.gz,3d_rad_segmentation/010/mask.nii.gz" >> data.csv
+
+# Setup config file
+cp ../../samples/config_getting_started_segmentation_rad3d.yaml .
+
+##################
+#### Training ####
+##################
+
+gandlf_run \
+  -c ./config_getting_started_segmentation_rad3d.yaml \
+  -i ./data.csv \
+  -m ./trained_model_output \
+  -t True \
+  -d cpu
+
+# remove data.csv to assume that we need a custom script with gandlf deploy
+rm data.csv
+
+################
+#### deploy ####
+################
+
+# deploy model
+mkdir model_mlcube
+cp $MODEL_MLCUBE_TEMPLATE model_mlcube/mlcube.yaml
+
+gandlf_deploy \
+  -c ./config_getting_started_segmentation_rad3d.yaml \
+  -m ./trained_model_output \
+  --target docker \
+  --mlcube-root ./model_mlcube \
+  -o ./built_model_mlcube \
+  --mlcube-type model \
+  -g False \
+  --entrypoint $MODEL_MLCUBE_ENTRYPOINT
+
+# deploy metrics
+mkdir metrics_mlcube
+cp $METRICS_MLCUBE_TEMPLATE metrics_mlcube/mlcube.yaml
+
+gandlf_deploy \
+  --target docker \
+  --mlcube-root ./metrics_mlcube \
+  -o ./built_metrics_mlcube \
+  --mlcube-type metrics \
+  --entrypoint $METRICS_MLCUBE_ENTRYPOINT
+
+######################
+#### run pipeline ####
+######################
+
+mlcube run \
+    --mlcube ./built_model_mlcube \
+    --task infer \
+    data_path=../../3d_rad_segmentation \
+    output_path=../../predictions
+
+mlcube run \
+    --mlcube ./built_metrics_mlcube \
+    --task evaluate \
+    predictions=../../predictions \
+    labels=../../3d_rad_segmentation \
+    output_path=../../results.yaml \
+    parameters_file=../../config_getting_started_segmentation_rad3d.yaml
+
+
+###############
+#### check ####
+###############
+
+if [ -f "results.yaml" ]; then
+    echo "Success"
+    cd ..
+    sudo rm -rf ./test_deploy/
+else 
+    echo "Failure"
+    exit 1
+fi

From e61329b70db4a3e9df80dcc4a010f3258ced79b8 Mon Sep 17 00:00:00 2001
From: hasan7n <hasankassim7@hotmail.com>
Date: Wed, 9 Aug 2023 15:18:56 +0200
Subject: [PATCH 70/76] add shebang per codacy suggestion

---
 testing/test_deploy.sh | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/testing/test_deploy.sh b/testing/test_deploy.sh
index 43ff7d531..bb5d1dfaa 100644
--- a/testing/test_deploy.sh
+++ b/testing/test_deploy.sh
@@ -1,3 +1,5 @@
+#! /bin/sh
+
 ###############
 #### Setup ####
 ###############

From 2577803312259e93c393a67347060fa988ef749c Mon Sep 17 00:00:00 2001
From: hasan7n <hasankassim7@hotmail.com>
Date: Wed, 9 Aug 2023 15:19:11 +0200
Subject: [PATCH 71/76] fix mlcube ci test workflow name

---
 .github/workflows/mlcube-test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/mlcube-test.yml b/.github/workflows/mlcube-test.yml
index 8306011f8..0897fb573 100644
--- a/.github/workflows/mlcube-test.yml
+++ b/.github/workflows/mlcube-test.yml
@@ -1,6 +1,6 @@
 # This workflow will test gandlf_deploy for model and metrics MLCubes
 
-name: CI-PyTest
+name: MLCube-Test
 
 on:
   push:

From 1d492aa87a9cd284e87764577c15226e20563225 Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Thu, 10 Aug 2023 16:21:29 +0200
Subject: [PATCH 72/76] Use tuple for data_range in PSNR instead of range size

---
 GANDLF/metrics/synthesis.py | 7 ++++---
 1 file changed, 4 insertions(+), 3 deletions(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index fd3590a58..3b56e61b0 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -55,7 +55,7 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
     Args:
         target (torch.Tensor): The target tensor.
         prediction (torch.Tensor): The prediction tensor.
-        data_range (float, optional): If not None, this data range is used as enumerator instead of computing it from the given data. Defaults to None.
+        data_range (tuple, optional): If not None, this data range (min, max) is used as enumerator instead of computing it from the given data. Defaults to None.
         epsilon (float, optional): If not None, this epsilon is added to the denominator of the fraction to avoid infinity as output. Defaults to None.
     """
 
@@ -67,8 +67,9 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
         if data_range == None: #compute data_range like torchmetrics if not given
             min_v = 0 if torch.min(target) > 0 else torch.min(target) #look at this line
             max_v = torch.max(target)
-            data_range = max_v - min_v
-        return 10.0 * torch.log10((data_range ** 2) / (mse + epsilon))
+        else:
+            min_v, max_v = data_range
+        return 10.0 * torch.log10(((max_v-min_v) ** 2) / (mse + epsilon))
 
 
 def mean_squared_log_error(target, prediction) -> torch.Tensor:

From 5690df784311a619b900418d14b1d1e8941dcf2e Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Thu, 10 Aug 2023 16:31:00 +0200
Subject: [PATCH 73/76] Use tuple for datat range & fixed the missing range in
 the psnr_01_eps case

---
 GANDLF/cli/generate_metrics.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index 07423a3fc..aa47e5f69 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -301,14 +301,14 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
                 overall_stats_dict[current_subject_id][
                     "psnr_01"
                 ] = peak_signal_noise_ratio(
-                    gt_image_infill, output_infill, data_range=1.0
+                    gt_image_infill, output_infill, data_range=(0,1)
                 ).item()
 
                 # same as above but with epsilon for robustness
                 overall_stats_dict[current_subject_id][
                     "psnr_01_eps"
                 ] = peak_signal_noise_ratio(
-                    gt_image_infill, output_infill, epsilon=sys.float_info.epsilon
+                    gt_image_infill, output_infill, data_range=(0,1), epsilon=sys.float_info.epsilon
                 ).item()
 
     pprint(overall_stats_dict)

From 24d175f10cb95f87470bff8791325c7a261f246d Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Thu, 10 Aug 2023 17:22:00 +0200
Subject: [PATCH 74/76] Added range computation for the torchmetrics call

---
 GANDLF/metrics/synthesis.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/GANDLF/metrics/synthesis.py b/GANDLF/metrics/synthesis.py
index 3b56e61b0..9aa4da466 100644
--- a/GANDLF/metrics/synthesis.py
+++ b/GANDLF/metrics/synthesis.py
@@ -60,7 +60,7 @@ def peak_signal_noise_ratio(target, prediction, data_range=None, epsilon=None) -
     """
 
     if epsilon == None:
-        psnr = PeakSignalNoiseRatio(data_range=data_range)
+        psnr = PeakSignalNoiseRatio() if data_range == None else PeakSignalNoiseRatio(data_range=data_range[1]-data_range[0])
         return psnr(preds=prediction, target=target)
     else: # implementation of PSNR that does not give 'inf'/'nan' when 'mse==0'
         mse = mean_squared_error(target, prediction)

From 60f35d0fbcc12edda4d7f01a2d4069467ed647d1 Mon Sep 17 00:00:00 2001
From: hasan7n <hasankassim7@hotmail.com>
Date: Mon, 14 Aug 2023 03:35:26 +0200
Subject: [PATCH 75/76] add unittest for custom entrypoint

---
 testing/test_full.py | 30 +++++++++++++++++++-----------
 1 file changed, 19 insertions(+), 11 deletions(-)

diff --git a/testing/test_full.py b/testing/test_full.py
index 3fc1e28f2..2e0ad0bae 100644
--- a/testing/test_full.py
+++ b/testing/test_full.py
@@ -2941,17 +2941,25 @@ def test_generic_deploy_docker():
         reset=True,
     )
 
-    result = run_deployment(
-        os.path.join(gandlfRootDir, "mlcube/model_mlcube/"),
-        deploymentOutputDir,
-        "docker",
-        "model",
-        configfile=testingDir + "/config_segmentation.yaml",
-        modeldir=outputDir,
-        requires_gpu=True,
-    )
-
-    assert result, "run_deployment returned false"
+    custom_entrypoint = os.path.join(
+        gandlfRootDir,
+        "mlcube/model_mlcube/example_custom_entrypoint/getting_started_3d_rad_seg.py",
+    )
+    for entrypoint_script in [None, custom_entrypoint]:
+        result = run_deployment(
+            os.path.join(gandlfRootDir, "mlcube/model_mlcube/"),
+            deploymentOutputDir,
+            "docker",
+            "model",
+            entrypoint_script=entrypoint_script,
+            configfile=testingDir + "/config_segmentation.yaml",
+            modeldir=outputDir,
+            requires_gpu=True,
+        )
+        msg = "run_deployment returned false"
+        if entrypoint_script:
+            msg += " with custom entrypoint script"
+        assert result, msg
     sanitize_outputDir()
 
     print("passed")

From bc0d3fa6c25b75728fbd9796380d9b82c5a2583f Mon Sep 17 00:00:00 2001
From: FelixSteinbauer <43598998+FelixSteinbauer@users.noreply.github.com>
Date: Thu, 24 Aug 2023 18:28:25 +0200
Subject: [PATCH 76/76] Added parameter to toggle NCC computation

Introduced a parameter (compute_ncc, defaut=True) that allows to turn off the (time-consuming) computation of the 4 NCC metrics.
---
 GANDLF/cli/generate_metrics.py | 26 ++++++++++++++------------
 1 file changed, 14 insertions(+), 12 deletions(-)

diff --git a/GANDLF/cli/generate_metrics.py b/GANDLF/cli/generate_metrics.py
index aa47e5f69..eaef3f77f 100644
--- a/GANDLF/cli/generate_metrics.py
+++ b/GANDLF/cli/generate_metrics.py
@@ -253,18 +253,20 @@ def __percentile_clip(input_tensor, reference_tensor=None, p_min=0.5, p_max=99.5
             ] = structural_similarity_index(gt_image_infill, output_infill, mask).item()
 
             # ncc metrics
-            overall_stats_dict[current_subject_id]["ncc_mean"] = ncc_mean(
-                gt_image_infill, output_infill
-            )
-            overall_stats_dict[current_subject_id]["ncc_std"] = ncc_std(
-                gt_image_infill, output_infill
-            )
-            overall_stats_dict[current_subject_id]["ncc_max"] = ncc_max(
-                gt_image_infill, output_infill
-            )
-            overall_stats_dict[current_subject_id]["ncc_min"] = ncc_min(
-                gt_image_infill, output_infill
-            )
+            compute_ncc = parameters.get("compute_ncc", True)
+            if compute_ncc:
+                overall_stats_dict[current_subject_id]["ncc_mean"] = ncc_mean(
+                    gt_image_infill, output_infill
+                )
+                overall_stats_dict[current_subject_id]["ncc_std"] = ncc_std(
+                    gt_image_infill, output_infill
+                )
+                overall_stats_dict[current_subject_id]["ncc_max"] = ncc_max(
+                    gt_image_infill, output_infill
+                )
+                overall_stats_dict[current_subject_id]["ncc_min"] = ncc_min(
+                    gt_image_infill, output_infill
+                )
 
             # only voxels that are to be inferred (-> flat array)
             # these are required for mse, psnr, etc.