📝 Add visualizer docs, fix :raise indents

InnerEye/ML/model_testing.py

@@ -129,7 +129,7 @@ def segmentation_model_test_epoch(config: SegmentationModelBase,
  :param execution_mode: Is the model evaluated on train, test, or validation set?
  :param results_folder: The folder where to store the results.
  :param epoch_and_split: A string that should uniquely identify the epoch and the data split (train/val/test).
-  :raises TypeError: If the arguments are of the wrong type.
+ :raises TypeError: If the arguments are of the wrong type.
  :raises ValueError: When there are issues loading the model.
  :return: A list with the mean dice score (across all structures apart from background) for each image.
  """

InnerEye/ML/utils/io_util.py

@@ -209,7 +209,7 @@ def load_nifti_image(path: PathOrString, image_type: Optional[Type] = float) ->
  :return: A numpy array of the image and header data if applicable.
 
  :param image_type: The type to load the image in, set to None to not cast, default is float
-  :raises ValueError: If the path is invalid or the image is not 3D.
+ :raises ValueError: If the path is invalid or the image is not 3D.
  """
 
  def _is_valid_image_path(_path: Path) -> bool:

InnerEye/ML/utils/ml_util.py

@@ -82,8 +82,8 @@ def validate_dataset_paths(
  Validates that the required dataset csv file exists in the given path.
 
  :param dataset_path: The base path
- :param custom_dataset_csv : The name of the dataset csv file
-  :raise ValueError if the dataset does not exist.
+ :param custom_dataset_csv: The name of the dataset csv file
+ :raise ValueError if the dataset does not exist.
  """
  if not dataset_path.is_dir():
  raise ValueError("The dataset_path argument should be the path to the base directory of the data "
@@ -117,7 +117,7 @@ def check_size_matches(arg1: Union[np.ndarray, torch.Tensor],
 
  :param arg1_name: If provided, all error messages will use that string to instead of "arg1"
  :param arg2_name: If provided, all error messages will use that string to instead of "arg2"
-  :raise ValueError if shapes don't match
+ :raise ValueError if shapes don't match
  """
  if arg1 is None or arg2 is None:
  raise Exception("arg1 and arg2 cannot be None.")
@@ -132,7 +132,7 @@ def check_dim(expected: int, actual_shape: Any, name: str) -> None:
  :param expected: expected shape
  :param actual_shape:
  :param name: variable name
-  :raise ValueError if not the same shape
+ :raise ValueError if not the same shape
  """
  if len(actual_shape) != expected:
  raise ValueError("'{}' was expected to have ndim == {}, but is {}. Shape is {}"
@@ -176,7 +176,7 @@ def is_test_from_execution_mode(execution_mode: ModelExecutionMode) -> bool:
  Returns a boolean by checking the execution type. The output is used to determine the properties
  of the forward pass, e.g. model gradient updates or metric computation.
  :return: True if execution mode is VAL or TEST, False if TRAIN
-  :raise ValueError if the execution mode is invalid
+ :raise ValueError if the execution mode is invalid
  """
  if execution_mode == ModelExecutionMode.TRAIN:
  return False

docs/source/rst/api/ML/visualizers/index.rst

@@ -1,2 +1,20 @@
 Visualizers
 ===========
+
+Below you will find all classes and functions related to the visualization of models and outputs.
+
+.. automodule:: InnerEye.ML.visualizers.activation_maps
+
+.. automodule:: InnerEye.ML.visualizers.metrics_scatterplot
+
+.. automodule:: InnerEye.ML.visualizers.model_hooks
+
+.. automodule:: InnerEye.ML.visualizers.model_summary
+
+.. automodule:: InnerEye.ML.visualizers.patch_sampling
+
+.. automodule:: InnerEye.ML.visualizers.plot_cross_validation
+
+.. automodule:: InnerEye.ML.visualizers.regression_visualization
+
+.. automodule:: InnerEye.ML.visualizers.reliability_curve