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Address black + isort fbsource linter warnings

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Summary: Address black + isort fbsource linter warnings from D20558374 (previous diff)

Reviewed By: nikhilaravi

Differential Revision: D20558373

fbshipit-source-id: d3607de4a01fb24c0d5269634563a7914bddf1c8
This commit is contained in:
Patrick Labatut
2020-03-29 14:46:33 -07:00
committed by Facebook GitHub Bot
parent eb512ffde3
commit d57daa6f85
110 changed files with 705 additions and 1850 deletions
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14
tests/test_cubify.py
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@@ -1,8 +1,8 @@
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
import unittest
import torch
import torch
from pytorch3d.ops import cubify
@@ -33,9 +33,7 @@ class TestCubify(unittest.TestCase):
# 1st-check
verts, faces = meshes.get_mesh_verts_faces(0)
self.assertTrue(
torch.allclose(faces.max(), torch.tensor([verts.size(0) - 1]))
)
self.assertTrue(torch.allclose(faces.max(), torch.tensor([verts.size(0) - 1])))
self.assertTrue(
torch.allclose(
verts,
@@ -80,9 +78,7 @@ class TestCubify(unittest.TestCase):
)
# 2nd-check
verts, faces = meshes.get_mesh_verts_faces(1)
self.assertTrue(
torch.allclose(faces.max(), torch.tensor([verts.size(0) - 1]))
)
self.assertTrue(torch.allclose(faces.max(), torch.tensor([verts.size(0) - 1])))
self.assertTrue(
torch.allclose(
verts,
@@ -275,9 +271,7 @@ class TestCubify(unittest.TestCase):
@staticmethod
def cubify_with_init(batch_size: int, V: int):
device = torch.device("cuda:0")
voxels = torch.rand(
(batch_size, V, V, V), dtype=torch.float32, device=device
)
voxels = torch.rand((batch_size, V, V, V), dtype=torch.float32, device=device)
torch.cuda.synchronize()
def convert():