Make _should_skip_inputs_and_warn a free function #1667
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Summary: This diff makes a change to the `_should_skip_inputs_and_warn` function in the `captum/attr/_core/feature_ablation.py` file. The function is now a free function instead of being a method of a class. The function checks two conditions that would cause a feature group to be skipped during attribution computation: 1. If `min_examples_per_batch_grouped` is specified and any input tensor in the feature group has a batch size (0th dimension) smaller than this threshold. 2. If all input tensors in the feature group are empty Differential Revision: D87300652
Summary: This diff makes a change to the `_should_skip_inputs_and_warn` function in the `captum/attr/_core/feature_ablation.py` file. The function is now a free function instead of being a method of a class. The function checks two conditions that would cause a feature group to be skipped during attribution computation: 1. If `min_examples_per_batch_grouped` is specified and any input tensor in the feature group has a batch size (0th dimension) smaller than this threshold. 2. If all input tensors in the feature group are empty Differential Revision: D87300652
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Summary: This diff makes a change to the
_should_skip_inputs_and_warnfunction in thecaptum/attr/_core/feature_ablation.pyfile. The function is now a free function instead of being a method of a class. The function checks two conditions that would cause a feature group to be skipped during attribution computation: 1. Ifmin_examples_per_batch_groupedis specified and any input tensor in the feature group has a batch size (0th dimension) smaller than this threshold. 2. If all input tensors in the feature group are emptyDifferential Revision: D87300652