[doc] Add the reference to the fit_dictionary

Author: nabenabe0928

autoPyTorch/evaluation/train_evaluator.py

@@ -366,6 +366,8 @@ def _fit_and_predict(self, pipeline: BaseEstimator, fold: int, train_indices: Un
 
         self.indices[fold] = ((train_indices, test_indices))
 
+        # See autoPyTorch/pipeline/components/base_component.py::autoPyTorchComponent for more details
+        # about fit_dictionary
         X = {'train_indices': train_indices,
              'val_indices': test_indices,
              'split_id': fold,

autoPyTorch/pipeline/components/preprocessing/tabular_preprocessing/utils.py

@@ -12,8 +12,12 @@ def get_tabular_preprocessers(X: Dict[str, Any]) -> Dict[str, List[BaseEstimator
     Creates a dictionary with two keys,
     numerical- containing list of numerical preprocessors
     categorical- containing list of categorical preprocessors
+
     Args:
         X: fit dictionary
+            See autoPyTorch/pipeline/components/base_component.py::autoPyTorchComponent for more details
+            about fit_dictionary
+
     Returns:
         (Dict[str, List[BaseEstimator]]): dictionary with list of numerical and categorical preprocessors
     """

autoPyTorch/utils/common.py

@@ -158,6 +158,8 @@ def get_device_from_fit_dictionary(X: Dict[str, Any]) -> torch.device:
 
     Args:
         X (Dict[str, Any]): A fit dictionary to control how the pipeline is fitted
+            See autoPyTorch/pipeline/components/base_component.py::autoPyTorchComponent for more details
+            about fit_dictionary
 
     Returns:
         torch.device: Device to be used for training/inference