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Convert directory fbcode/vision to use the Ruff Formatter
Summary:
Converts the directory specified to use the Ruff formatter in pyfmt
ruff_dog
If this diff causes merge conflicts when rebasing, please run
`hg status -n -0 --change . -I '**/*.{py,pyi}' | xargs -0 arc pyfmt`
on your diff, and amend any changes before rebasing onto latest.
That should help reduce or eliminate any merge conflicts.
allow-large-files
Reviewed By: bottler
Differential Revision: D66472063
fbshipit-source-id: 35841cb397e4f8e066e2159550d2f56b403b1bef
This commit is contained in:
committed by
Facebook GitHub Bot
parent
f6c2ca6bfc
commit
055ab3a2e3
@@ -576,7 +576,6 @@ class TestConfig(unittest.TestCase):
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a: int = 9
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for Unprocessed in [UnprocessedConfigurable, UnprocessedReplaceable]:
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self.assertFalse(_is_actually_dataclass(Unprocessed))
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unprocessed = Unprocessed()
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self.assertTrue(_is_actually_dataclass(Unprocessed))
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@@ -71,7 +71,6 @@ class TestEvaluation(unittest.TestCase):
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for diff in 10 ** torch.linspace(-5, 0, 6):
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for crop in (0, 5):
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pred = gt + (torch.rand_like(gt) - 0.5) * 2 * diff
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# scaled prediction test
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@@ -74,7 +74,6 @@ class TestGenericModel(unittest.TestCase):
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eval_test: bool = True,
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bw_test: bool = True,
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):
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R, T = look_at_view_transform(azim=torch.rand(n_train_cameras) * 360)
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cameras = PerspectiveCameras(R=R, T=T, device=device)
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@@ -171,9 +171,7 @@ def _make_random_json_dataset_map_provider_v2_data(
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Image.fromarray(
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(mask * 255.0).astype(np.uint8),
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mode="L",
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).convert(
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"L"
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).save(mask_path)
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).convert("L").save(mask_path)
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fa = FrameAnnotation(
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sequence_name=seq_name,
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@@ -65,7 +65,6 @@ class TestModelVisualize(unittest.TestCase):
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visdom_show_preds = Visdom().check_connection()
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for load_dataset_pointcloud in [True, False]:
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model = _PointcloudRenderingModel(
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train_dataset,
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show_sequence_name,
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@@ -142,7 +142,6 @@ class TestViewsampling(unittest.TestCase):
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expand_args_fields(ViewSampler)
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for masked_sampling in (True, False):
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view_sampler = ViewSampler(masked_sampling=masked_sampling)
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feats_sampled, masks_sampled = view_sampler(
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@@ -275,7 +275,6 @@ class TestVoxelGrids(TestCaseMixin, unittest.TestCase):
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return torch.cat(result)
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def test_interpolation(self):
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with self.subTest("1D interpolation"):
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points = self.get_random_normalized_points(
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n_grids=4, n_points=5, dimension=1
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