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lint fixes

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Summary:
Ran the linter.
TODO: need to update the linter as per D21353065.

Reviewed By: bottler

Differential Revision: D21362270

fbshipit-source-id: ad0e781de0a29f565ad25c43bc94a19b1828c020
This commit is contained in:
Nikhila Ravi
2020-05-04 09:55:03 -07:00
committed by Facebook GitHub Bot
parent 0c595dcf5b
commit 0eca74fa5f
15 changed files with 73 additions and 57 deletions
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7
tests/test_chamfer.py
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@@ -35,6 +35,8 @@ class TestChamfer(TestCaseMixin, unittest.TestCase):
low = 0 if allow_empty else 1
p1_lengths = torch.randint(low, P1, size=(N,), dtype=torch.int64, device=device)
p2_lengths = torch.randint(low, P2, size=(N,), dtype=torch.int64, device=device)
P1 = p1_lengths.max().item()
P2 = p2_lengths.max().item()
weights = torch.rand((N,), dtype=torch.float32, device=device)
# list of points and normals tensors
@@ -109,9 +111,8 @@ class TestChamfer(TestCaseMixin, unittest.TestCase):
torch.arange(P2, device=y.device)[None] >= y_lengths[:, None]
) # shape [N, P2]
is_x_heterogeneous = ~(x_lengths == P1).all()
is_y_heterogeneous = ~(y_lengths == P2).all()
is_x_heterogeneous = (x_lengths != P1).any()
is_y_heterogeneous = (y_lengths != P2).any()
# Only calculate the distances for the points which are not masked
for n in range(N):
for i1 in range(x_lengths[n]):