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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
48 lines
1.2 KiB
Python
48 lines
1.2 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 itertools
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import torch
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from fvcore.common.benchmark import benchmark
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from pytorch3d.ops import estimate_pointcloud_normals
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from tests.test_points_normals import TestPCLNormals
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def to_bm(num_points, use_symeig_workaround):
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device = torch.device("cuda:0")
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points_padded, _normals = TestPCLNormals.init_spherical_pcl(
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num_points=num_points, device=device, use_pointclouds=False
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)
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torch.cuda.synchronize()
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def run():
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estimate_pointcloud_normals(
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points_padded, use_symeig_workaround=use_symeig_workaround
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)
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torch.cuda.synchronize()
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return run
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def bm_points_normals() -> None:
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case_grid = {
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"use_symeig_workaround": [True, False],
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"num_points": [3000, 6000],
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}
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test_cases = itertools.product(*case_grid.values())
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kwargs_list = [dict(zip(case_grid.keys(), case)) for case in test_cases]
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benchmark(
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to_bm,
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"normals",
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kwargs_list,
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warmup_iters=1,
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)
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if __name__ == "__main__":
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bm_points_normals()
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