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allow float fill for integer images in F.pad #7950
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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) |
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Same as above
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Thanks Philip!
Conflicts: test/test_transforms_v2_refactored.py
Reviewed By: matteobettini Differential Revision: D49600774 fbshipit-source-id: 3671923921f6da913ce94c327e075e4304f2e964
Fixes #7948
cc @vfdev-5