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https://github.com/facebookresearch/pytorch3d.git
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34f648ede0
Summary: Move testing targets from pytorch3d/tests/TARGETS to pytorch3d/TARGETS. Reviewed By: shapovalov Differential Revision: D36186940 fbshipit-source-id: a4c52c4d99351f885e2b0bf870532d530324039b
58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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import unittest
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import numpy as np
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import torch
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from pytorch3d.common.workaround import _safe_det_3x3
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from .common_testing import TestCaseMixin
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class TestSafeDet3x3(TestCaseMixin, unittest.TestCase):
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def setUp(self) -> None:
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super().setUp()
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torch.manual_seed(42)
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np.random.seed(42)
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def _test_det_3x3(self, batch_size, device):
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t = torch.rand((batch_size, 3, 3), dtype=torch.float32, device=device)
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actual_det = _safe_det_3x3(t)
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expected_det = t.det()
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self.assertClose(actual_det, expected_det, atol=1e-7)
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def test_empty_batch(self):
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self._test_det_3x3(0, torch.device("cpu"))
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self._test_det_3x3(0, torch.device("cuda:0"))
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def test_manual(self):
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t = torch.Tensor(
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[
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[[1, 0, 0], [0, 1, 0], [0, 0, 1]],
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[[2, -5, 3], [0, 7, -2], [-1, 4, 1]],
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[[6, 1, 1], [4, -2, 5], [2, 8, 7]],
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]
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).to(dtype=torch.float32)
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expected_det = torch.Tensor([1, 41, -306]).to(dtype=torch.float32)
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self.assertClose(_safe_det_3x3(t), expected_det)
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device_cuda = torch.device("cuda:0")
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self.assertClose(
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_safe_det_3x3(t.to(device=device_cuda)), expected_det.to(device=device_cuda)
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)
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def test_regression(self):
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tries = 32
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device_cpu = torch.device("cpu")
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device_cuda = torch.device("cuda:0")
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batch_sizes = np.random.randint(low=1, high=128, size=tries)
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for batch_size in batch_sizes:
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self._test_det_3x3(batch_size, device_cpu)
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self._test_det_3x3(batch_size, device_cuda)
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