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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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31
tests/test_rasterize_points.py
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@@ -1,10 +1,11 @@
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
import numpy as np
import unittest
import torch
import numpy as np
import torch
from common_testing import TestCaseMixin
from pytorch3d import _C
from pytorch3d.renderer.points.rasterize_points import (
rasterize_points,
@@ -12,8 +13,6 @@ from pytorch3d.renderer.points.rasterize_points import (
)
from pytorch3d.structures.pointclouds import Pointclouds
from common_testing import TestCaseMixin
class TestRasterizePoints(TestCaseMixin, unittest.TestCase):
def test_python_simple_cpu(self):
@@ -38,9 +37,7 @@ class TestRasterizePoints(TestCaseMixin, unittest.TestCase):
self._test_behind_camera(rasterize_points, torch.device("cpu"))
def test_cuda_behind_camera(self):
self._test_behind_camera(
rasterize_points, torch.device("cuda"), bin_size=0
)
self._test_behind_camera(rasterize_points, torch.device("cuda"), bin_size=0)
def test_cpp_vs_naive_vs_binned(self):
# Make sure that the backward pass runs for all pathways
@@ -167,20 +164,8 @@ class TestRasterizePoints(TestCaseMixin, unittest.TestCase):
points_cuda = points_cpu.cuda().detach().requires_grad_(True)
pointclouds_cpu = Pointclouds(points=points_cpu)
pointclouds_cuda = Pointclouds(points=points_cuda)
args_cpu = (
pointclouds_cpu,
image_size,
radius,
points_per_pixel,
bin_size,
)
args_cuda = (
pointclouds_cuda,
image_size,
radius,
points_per_pixel,
bin_size,
)
args_cpu = (pointclouds_cpu, image_size, radius, points_per_pixel, bin_size)
args_cuda = (pointclouds_cuda, image_size, radius, points_per_pixel, bin_size)
self._compare_impls(
rasterize_points,
rasterize_points,
@@ -332,9 +317,7 @@ class TestRasterizePoints(TestCaseMixin, unittest.TestCase):
], device=device)
# fmt: on
dists1_expected = torch.zeros(
(5, 5, 2), dtype=torch.float32, device=device
)
dists1_expected = torch.zeros((5, 5, 2), dtype=torch.float32, device=device)
# fmt: off
dists1_expected[:, :, 0] = torch.tensor([
[-1.00, -1.00, 0.16, -1.00, -1.00], # noqa: E241