Remove outdated docstring (#1652)

Summary:
Pull Request resolved: #1652

No longer true after D83107514 stack.
Also fix camel case for function naming

Reviewed By: yangaaapaul

Differential Revision: D83206370

fbshipit-source-id: 34ef68a579259c18ac54f22e1bc21163065160a6

Author: sarahtranfb

captum/attr/_core/shapley_value.py

@@ -130,10 +130,6 @@ def attribute(
         show_progress: bool = False,
     ) -> TensorOrTupleOfTensorsGeneric:
         r"""
-        NOTE: The feature_mask argument differs from other perturbation based
-        methods, since feature indices can overlap across tensors. See the
-        description of the feature_mask argument below for more details.
-
         Args:
 
                 inputs (Tensor or tuple[Tensor, ...]): Input for which Shapley value
@@ -225,8 +221,7 @@ def attribute(
                             all tensors should be integers in the range 0 to
                             num_features - 1, and indices corresponding to the same
                             feature should have the same value.
-                            Note that features are grouped across tensors
-                            (unlike feature ablation and occlusion), so
+                            Note that features are grouped across tensors, so
                             if the same index is used in different tensors, those
                             features are still grouped and added simultaneously.
                             If the forward function returns a single scalar per batch,
@@ -521,7 +516,7 @@ def attribute_future(
             prev_result_tuple: Future[
                 Tuple[Tensor, Tensor, Size, List[Tensor], bool]
             ] = initial_eval.then(
-                lambda inp=initial_eval: self._initialEvalToPrevResultsTuple(  # type: ignore # noqa: E501 line too long
+                lambda inp=initial_eval: self._initial_eval_to_prev_results_tuple(  # type: ignore # noqa: E501 line too long
                     inp,
                     num_examples,
                     perturbations_per_eval,
@@ -537,7 +532,7 @@ def attribute_future(
                 total_features, n_samples
             ):
                 prev_result_tuple = prev_result_tuple.then(
-                    lambda inp=prev_result_tuple: self._setPrevResultsToInitialEval(inp)  # type: ignore # noqa: E501 line too long
+                    lambda inp=prev_result_tuple: self._set_prev_results_to_initial_eval(inp)  # type: ignore # noqa: E501 line too long
                 )
 
                 iter_count += 1
@@ -590,7 +585,7 @@ def attribute_future(
                     ] = collect_all([prev_result_tuple, modified_eval])
 
                     prev_result_tuple = eval_futs.then(
-                        lambda evals=eval_futs, masks=current_masks: self._evalFutToPrevResultsTuple(  # type: ignore # noqa: E501 line too long
+                        lambda evals=eval_futs, masks=current_masks: self._eval_fut_to_prev_results_tuple(  # type: ignore # noqa: E501 line too long
                             evals, num_examples, inputs_tuple, masks
                         )
                     )
@@ -602,14 +597,14 @@ def attribute_future(
             # formatted attributions.
             formatted_attr: Future[Union[Tensor, tuple[Tensor, ...]]] = (
                 prev_result_tuple.then(
-                    lambda inp=prev_result_tuple: self._prevResultTupleToFormattedAttr(  # type: ignore # noqa: E501 line too long
+                    lambda inp=prev_result_tuple: self._prev_result_tuple_to_formatted_attr(  # type: ignore # noqa: E501 line too long
                         inp, iter_count, is_inputs_tuple
                     )
                 )
             )
         return cast(Future[TensorOrTupleOfTensorsGeneric], formatted_attr)
 
-    def _initialEvalToPrevResultsTuple(
+    def _initial_eval_to_prev_results_tuple(
         self,
         initial_eval: Future[Tensor],
         num_examples: int,
@@ -657,7 +652,7 @@ def _initialEvalToPrevResultsTuple(
             ) from e
         return result
 
-    def _setPrevResultsToInitialEval(
+    def _set_prev_results_to_initial_eval(
         self,
         processed_initial_eval: Future[Tuple[Tensor, Tensor, Size, List[Tensor], bool]],
     ) -> Tuple[Tensor, Tensor, Size, List[Tensor], bool]:
@@ -669,7 +664,7 @@ def _setPrevResultsToInitialEval(
         prev_results = initial_eval
         return (initial_eval, prev_results, output_shape, total_attrib, agg_output_mode)
 
-    def _evalFutToPrevResultsTuple(
+    def _eval_fut_to_prev_results_tuple(
         self,
         eval_futs: Future[
             List[
@@ -755,7 +750,7 @@ def _evalFutToPrevResultsTuple(
         )
         return result
 
-    def _prevResultTupleToFormattedAttr(
+    def _prev_result_tuple_to_formatted_attr(
         self,
         prev_result_tuple: Future[
             Tuple[Tensor, Tensor, Tuple[int], List[Tensor], bool]