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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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12
tests/test_cameras.py
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@@ -203,7 +203,7 @@ class TestCameraHelpers(TestCaseMixin, unittest.TestCase):
+ torch.cos(elev) * torch.cos(azim)
)
grad_elev = (
-torch.sin(elev) * torch.sin(azim)
-(torch.sin(elev)) * torch.sin(azim)
+ torch.cos(elev)
- torch.sin(elev) * torch.cos(azim)
)
@@ -260,7 +260,7 @@ class TestCameraHelpers(TestCaseMixin, unittest.TestCase):
+ torch.cos(elev) * torch.cos(azim)
)
grad_elev = (
-torch.sin(elev) * torch.sin(azim)
-(torch.sin(elev)) * torch.sin(azim)
+ torch.cos(elev)
- torch.sin(elev) * torch.cos(azim)
)
@@ -395,8 +395,8 @@ class TestCamerasCommon(TestCaseMixin, unittest.TestCase):
cam_params["aspect_ratio"] = torch.rand(batch_size) * 0.5 + 0.5
else:
cam_params["top"] = torch.rand(batch_size) * 0.2 + 0.9
cam_params["bottom"] = -torch.rand(batch_size) * 0.2 - 0.9
cam_params["left"] = -torch.rand(batch_size) * 0.2 - 0.9
cam_params["bottom"] = -(torch.rand(batch_size)) * 0.2 - 0.9
cam_params["left"] = -(torch.rand(batch_size)) * 0.2 - 0.9
cam_params["right"] = torch.rand(batch_size) * 0.2 + 0.9
elif cam_type in (SfMOrthographicCameras, SfMPerspectiveCameras):
cam_params["focal_length"] = torch.rand(batch_size) * 10 + 0.1
@@ -532,7 +532,7 @@ class TestPerspectiveProjection(TestCaseMixin, unittest.TestCase):
P = cameras.get_projection_transform()
vertices = torch.tensor([1, 2, 10], dtype=torch.float32)
z1 = 1.0 # vertices at far clipping plane so z = 1.0
z2 = (20.0 / (20.0 - 1.0) * 10.0 + -(20.0) / (20.0 - 1.0)) / 10.0
z2 = (20.0 / (20.0 - 1.0) * 10.0 + -20.0 / (20.0 - 1.0)) / 10.0
projected_verts = torch.tensor(
[
[np.sqrt(3) / 10.0, 2 * np.sqrt(3) / 10.0, z1],
@@ -660,7 +660,7 @@ class TestOpenGLOrthographicProjection(TestCaseMixin, unittest.TestCase):
cameras = OpenGLOrthographicCameras(znear=near, zfar=far)
P = cameras.get_projection_transform()
vertices = torch.tensor([1.0, 2.0, 10.0], dtype=torch.float32)
z2 = 1.0 / (20.0 - 1.0) * 10.0 + -(1.0) / (20.0 - 1.0)
z2 = 1.0 / (20.0 - 1.0) * 10.0 + -1.0 / (20.0 - 1.0)
projected_verts = torch.tensor(
[[1.0, 2.0, 1.0], [1.0, 2.0, z2]], dtype=torch.float32
)