PR 590 Review changes:

- quicktest.yaml: commenting out trigger on pull request
- FastSurferCNN.utils.metrics.py: docstring changes

Author: taha-abdullah

.github/workflows/quicktest.yaml

@@ -1,6 +1,6 @@
 name: quicktest-runner
 
-# File: quicktest.yaml
+# File: quicktest_runner.yaml
 # Author: Taha Abdullah
 # Created on: 2023-07-10
 # Functionality: This workflow runs FastSurfer on MRI data and runs pytest to check if the results are acceptable. It
@@ -16,25 +16,19 @@ name: quicktest-runner
 #  - FS_LICENSE: Path to the FreeSurfer license file.
 
 on:
-  pull_request:
-    branches:
-      - dev
-      - stable
+#  pull_request:
+#    branches:
+#      - dev
+#      - stable
   workflow_dispatch:
 
 jobs:
-  # Checkout repo
-  checkout:
+  run-quicktest:
     runs-on: self-hosted
     steps:
+    # Checkout fastsurfer
     - uses: actions/checkout@v2
-
-  # Create conda environment, install packages, and run Fastsurfer
-  run-fastsurfer:
-    runs-on: self-hosted
-    needs: checkout
-    steps:
-      # Check if the Environment Variables used in further steps are present
+    # Check if the Environment Variables used in further steps are present
     - name: Check Environment Variables
       run: |
         REQUIRED_ENV_VARS=(
@@ -71,17 +65,12 @@ jobs:
         export THIS_RUN_OUTDIR=${GITHUB_SHA:0:7}
         mkdir -p $SUBJECTS_DIR/$THIS_RUN_OUTDIR
         export TEST_DIR=$THIS_RUN_OUTDIR
+        export TQDM_DISABLE=1
         ./brun_fastsurfer.sh --subject_list $RUNNER_FS_MRI_DATA/subjects_list.txt \
                              --sd $SUBJECTS_DIR/$THIS_RUN_OUTDIR \
                              --parallel --threads 4 --3T --parallel_subjects surf
-
-  # Test fastsurfer output
-  run-pytest:
-    runs-on: self-hosted
-    if: always()
-    needs: run-fastsurfer
-    steps:
+    # run pytest checks for data consistency/quality
     - name: Run pytest
       run: |
         source /venv-pytest/bin/activate
-        python -m pytest test/quick_test
+        python -m pytest test/quick_test

FastSurferCNN/utils/metrics.py

@@ -109,17 +109,20 @@ class DiceScore:
     """
     Accumulating the component of the dice coefficient i.e. the union and intersection.
 
-    Args:
-        op (callable): a callable to update accumulator. Method's signature is `(accumulator, output)`.
-            For example, to compute arithmetic mean value, `op = lambda a, x: a + x`.
-        output_transform (callable, optional): a callable that is used to transform the
-            :class:`~ignite.engine.Engine`'s `process_function`'s output into the
-            form expected by the metric. This can be useful if, for example, you have a multi-output model and
-            you want to compute the metric with respect to one of the outputs.
-        device (str of torch.device, optional): device specification in case of distributed computation usage.
-            In most of the cases, it can be defined as "cuda:local_rank" or "cuda"
-            if already set `torch.cuda.set_device(local_rank)`. By default, if a distributed process group is
-            initialized and available, device is set to `cuda`.
+    Parameters
+    ----------
+    op : callable
+        A callable to update the accumulator. Method's signature is `(accumulator, output)`.
+        For example, to compute arithmetic mean value, `op = lambda a, x: a + x`.
+    output_transform : callable, optional
+        A callable that is used to transform the :class:`~ignite.engine.Engine`'s `process_function`'s output into the
+        form expected by the metric. This can be useful if, for example, you have a multi-output model and
+        you want to compute the metric with respect to one of the outputs.
+    device : str or torch.device, optional
+        Device specification in case of distributed computation usage.
+        In most cases, it can be defined as "cuda:local_rank" or "cuda"
+        if already set `torch.cuda.set_device(local_rank)`. By default, if a distributed process group is
+        initialized and available, the device is set to `cuda`.
     """
     def __init__(
         self,
@@ -154,8 +157,8 @@ def _check_output_type(self, output):
         """
         Check the type of the output and raise an error if it doesn't match expectations.
 
-        Parameters:
-        -----------
+        Parameters
+        ----------
         output : tuple
             The output to be checked, expected to be a tuple.
         """
@@ -168,8 +171,8 @@ def _update_union_intersection(self, batch_output, labels_batch):
         """
         Update the union and intersection matrices based on batch predictions and labels.
 
-        Parameters:
-        -----------
+        Parameters
+        ----------
         batch_output : torch.Tensor
             Batch predictions from the model.