allow float fill for integer images in F.pad #7950
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pmeier
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Sep 8, 2023
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| # turns all warnings into errors for this module | ||
| pytestmark = pytest.mark.filterwarnings("error") |
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This makes sure, we never miss a warning coming from the transforms again.
| @@ -312,11 +312,12 @@ def adapt_fill(value, *, dtype): | |||
| return value | |||
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| max_value = get_max_value(dtype) | |||
| value_type = float if dtype.is_floating_point else int | |||
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If we adapt the fill value, we also want to adapt the type. I've checked and this does not hide the errors that we are fixing here.
| if isinstance(input, tv_tensors.Mask) and isinstance(value, (tuple, list)): | ||
| pytest.skip("F.pad_mask doesn't support non-scalar fill.") | ||
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| kwargs["fill"] = adapt_fill( |
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I've missed to adapt the value here.
| @@ -3478,6 +3487,8 @@ def test_transform_errors(self): | |||
| def test_image_correctness(self, padding, padding_mode, fill, fn): | |||
| image = make_image(dtype=torch.uint8, device="cpu") | |||
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| fill = adapt_fill(fill, dtype=torch.uint8) | |||
pmeier
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Conflicts: test/test_transforms_v2_refactored.py
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Reviewed By: matteobettini Differential Revision: D49600774 fbshipit-source-id: 3671923921f6da913ce94c327e075e4304f2e964
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Fixes #7948
cc @vfdev-5