mirror of
https://github.com/facebookresearch/pytorch3d.git
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ff19c642cb
Summary: Updates to the Renderer to enable barycentric clipping. This is important when there is blurring in the rasterization step. Also added support for flat shading. Reviewed By: jcjohnson Differential Revision: D19934259 fbshipit-source-id: 036e48636cd80d28a04405d7a29fcc71a2982904
65 lines
2.1 KiB
Python
65 lines
2.1 KiB
Python
#!/usr/bin/env python3
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# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
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import unittest
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import torch
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from pytorch3d.renderer.utils import TensorProperties
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from common_testing import TestCaseMixin
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# Example class for testing
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class TensorPropertiesTestClass(TensorProperties):
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def __init__(self, x=None, y=None, device="cpu"):
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super().__init__(device=device, x=x, y=y)
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def clone(self):
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other = TensorPropertiesTestClass()
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return super().clone(other)
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class TestTensorProperties(TestCaseMixin, unittest.TestCase):
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def test_init(self):
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example = TensorPropertiesTestClass(x=10.0, y=(100.0, 200.0))
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# Check kwargs set as attributes + converted to tensors
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self.assertTrue(torch.is_tensor(example.x))
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self.assertTrue(torch.is_tensor(example.y))
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# Check broadcasting
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self.assertTrue(example.x.shape == (2,))
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self.assertTrue(example.y.shape == (2,))
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self.assertTrue(len(example) == 2)
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def test_to(self):
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# Check to method
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example = TensorPropertiesTestClass(x=10.0, y=(100.0, 200.0))
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device = torch.device("cuda:0")
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new_example = example.to(device=device)
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self.assertTrue(new_example.device == device)
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def test_clone(self):
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# Check clone method
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example = TensorPropertiesTestClass(x=10.0, y=(100.0, 200.0))
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new_example = example.clone()
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self.assertSeparate(example.x, new_example.x)
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self.assertSeparate(example.y, new_example.y)
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def test_get_set(self):
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# Test getitem returns an accessor which can be used to modify
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# attributes at a particular index
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example = TensorPropertiesTestClass(x=10.0, y=(100.0, 200.0, 300.0))
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# update y1
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example[1].y = 5.0
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self.assertTrue(example.y[1] == 5.0)
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# Get item and get value
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ex0 = example[0]
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self.assertTrue(ex0.y == 100.0)
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def test_empty_input(self):
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example = TensorPropertiesTestClass(x=(), y=())
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self.assertTrue(len(example) == 0)
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self.assertTrue(example.isempty())
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