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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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28
tests/test_subdivide_meshes.py
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@@ -2,14 +2,13 @@
import unittest
import torch
import torch
from common_testing import TestCaseMixin
from pytorch3d.ops.subdivide_meshes import SubdivideMeshes
from pytorch3d.structures.meshes import Meshes
from pytorch3d.utils.ico_sphere import ico_sphere
from common_testing import TestCaseMixin
class TestSubdivideMeshes(TestCaseMixin, unittest.TestCase):
def test_simple_subdivide(self):
@@ -72,25 +71,14 @@ class TestSubdivideMeshes(TestCaseMixin, unittest.TestCase):
)
faces1 = torch.tensor([[0, 1, 2]], dtype=torch.int64, device=device)
verts2 = torch.tensor(
[
[0.5, 1.0, 0.0],
[1.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[1.5, 1.0, 0.0],
],
[[0.5, 1.0, 0.0], [1.0, 0.0, 0.0], [0.0, 0.0, 0.0], [1.5, 1.0, 0.0]],
dtype=torch.float32,
device=device,
requires_grad=True,
)
faces2 = torch.tensor(
[[0, 1, 2], [0, 3, 1]], dtype=torch.int64, device=device
)
faces3 = torch.tensor(
[[0, 1, 2], [0, 2, 3]], dtype=torch.int64, device=device
)
mesh = Meshes(
verts=[verts1, verts2, verts2], faces=[faces1, faces2, faces3]
)
faces2 = torch.tensor([[0, 1, 2], [0, 3, 1]], dtype=torch.int64, device=device)
faces3 = torch.tensor([[0, 1, 2], [0, 2, 3]], dtype=torch.int64, device=device)
mesh = Meshes(verts=[verts1, verts2, verts2], faces=[faces1, faces2, faces3])
subdivide = SubdivideMeshes()
new_mesh = subdivide(mesh.clone())
@@ -218,9 +206,7 @@ class TestSubdivideMeshes(TestCaseMixin, unittest.TestCase):
self.assertTrue(new_feats.requires_grad == gt_feats.requires_grad)
@staticmethod
def subdivide_meshes_with_init(
num_meshes: int = 10, same_topo: bool = False
):
def subdivide_meshes_with_init(num_meshes: int = 10, same_topo: bool = False):
device = torch.device("cuda:0")
meshes = ico_sphere(0, device=device)
if num_meshes > 1: