[PR response]: deleted unneeded changes from merge and fixed the doc-string.

Author: nabenabe0928

.gitignore

@@ -138,7 +138,3 @@ dask-worker-space/
 # Test output
 tmp/
 .tmp_evaluation
-
-# private
-grep.py
-private/

autoPyTorch/datasets/base_dataset.py

@@ -161,9 +161,9 @@ def update_transform(self, transform: Optional[torchvision.transforms.Compose],
 
     def __getitem__(self, index: int, train: bool = True) -> Tuple[np.ndarray, ...]:
         """
-        The base dataset uses a Subset of the data. Nevertheless, the base dataset expect
-        both validation and test data to be present in the same dataset, which is motivated
-        by the need to dynamically give train/test data with the __getitem__ command.
+        The base dataset uses a Subset of the data. Nevertheless, the base dataset expects
+        both validation and test data to be present in the same dataset, which motivates
+        the need to dynamically give train/test data with the __getitem__ command.
 
         This method yields a datapoint of the whole data (after a Subset has selected a given
         item, based on the resampling strategy) and applies a train/testing transformation, if any.

autoPyTorch/pipeline/components/training/trainer/StandardTrainer.py

@@ -56,8 +56,6 @@ def get_properties(dataset_properties: typing.Optional[typing.Dict[str, typing.A
     def get_hyperparameter_search_space(dataset_properties: typing.Optional[typing.Dict] = None,
                                         weighted_loss: typing.Tuple[typing.Tuple, bool] = ((True, False), True)
                                         ) -> ConfigurationSpace:
-        weighted_loss = CategoricalHyperparameter("weighted_loss", choices=weighted_loss[0],
-                                                  default_value=weighted_loss[1])
         cs = ConfigurationSpace()
         if dataset_properties is not None:
             if STRING_TO_TASK_TYPES[dataset_properties['task_type']] in CLASSIFICATION_TASKS:

autoPyTorch/pipeline/components/training/trainer/base_trainer_choice.py

@@ -98,11 +98,11 @@ def get_components(self) -> Dict[str, autoPyTorchComponent]:
         return components
 
     def get_hyperparameter_search_space(
-            self,
-            dataset_properties: Optional[Dict[str, str]] = None,
-            default: Optional[str] = None,
-            include: Optional[List[str]] = None,
-            exclude: Optional[List[str]] = None,
+        self,
+        dataset_properties: Optional[Dict[str, str]] = None,
+        default: Optional[str] = None,
+        include: Optional[List[str]] = None,
+        exclude: Optional[List[str]] = None,
     ) -> ConfigurationSpace:
         """Returns the configuration space of the current chosen components
 

test/test_pipeline/components/test_tabular_column_transformer.py

@@ -12,11 +12,6 @@
     TabularColumnTransformer
 )
 
-@pytest.mark.parametrize("fit_dictionary", ['fit_dictionary_numerical_only',
-                                            'fit_dictionary_categorical_only',
-                                            'fit_dictionary_num_and_categorical'], indirect=True)
-class TestTabularTransformer:
-    def test_tabular_preprocess(self, fit_dictionary):
 
 @pytest.mark.parametrize("fit_dictionary_tabular", ['classification_numerical_only',
                                                     'classification_categorical_only',