Update FeatureAblation to handle precision loss when baseline is more granular than input when cross tensor attribution is enabled #1644
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This pull request was exported from Phabricator. Differential Revision: D81980219 |
… granular than input when cross tensor attribution is enabled (pytorch#1644) Summary: Noticed when flipping the flag, this test case failed: https://www.internalfb.com/code/fbsource/[faf71541b1ec0fae639f82d487b81fb18ea3e523]/fbcode/pytorch/captum/tests/attr/test_dataloader_attr.py?lines=138%2C134 The ablated tensor was `tensor([0])` instead of `tensor([[0.1])` since the baseline was a float-type and the input tensors were int tensors. https://www.internalfb.com/code/fbsource/[f2fcc926a6f3669602bac4d28c2d92e4197c96b9]/fbcode/pytorch/captum/captum/attr/_core/feature_ablation.py?lines=707-709 `ablated_input` is just a copy of the `input_tensor`, so during assignment, the ablated feature tensor incorrectly gets cast to an int tensor for this case. Differential Revision: D81980219
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Summary:
Noticed when flipping the flag, this test case failed:
https://www.internalfb.com/code/fbsource/[faf71541b1ec0fae639f82d487b81fb18ea3e523]/fbcode/pytorch/captum/tests/attr/test_dataloader_attr.py?lines=138%2C134
The ablated tensor was
tensor([0])instead oftensor([[0.1])since the baseline was a float-type and the input tensors were int tensors.https://www.internalfb.com/code/fbsource/[f2fcc926a6f3669602bac4d28c2d92e4197c96b9]/fbcode/pytorch/captum/captum/attr/_core/feature_ablation.py?lines=707-709
ablated_inputis just a copy of theinput_tensor, so during assignment, the ablated feature tensor incorrectly gets cast to an int tensor for this case.Differential Revision: D81980219