| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # All rights reserved. | |
| # | |
| # This source code is licensed under the BSD-style license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| from itertools import product | |
| import torch | |
| from fvcore.common.benchmark import benchmark | |
| from tests.test_sample_points_from_meshes import TestSamplePoints | |
| def bm_sample_points() -> None: | |
| backend = ["cpu"] | |
| if torch.cuda.is_available(): | |
| backend.append("cuda:0") | |
| kwargs_list = [] | |
| num_meshes = [2, 10, 32] | |
| num_verts = [100, 1000] | |
| num_faces = [300, 3000] | |
| num_samples = [5000, 10000] | |
| test_cases = product(num_meshes, num_verts, num_faces, num_samples, backend) | |
| for case in test_cases: | |
| n, v, f, s, b = case | |
| kwargs_list.append( | |
| { | |
| "num_meshes": n, | |
| "num_verts": v, | |
| "num_faces": f, | |
| "num_samples": s, | |
| "device": b, | |
| } | |
| ) | |
| benchmark( | |
| TestSamplePoints.sample_points_with_init, | |
| "SAMPLE_MESH", | |
| kwargs_list, | |
| warmup_iters=1, | |
| ) | |
| if __name__ == "__main__": | |
| bm_sample_points() | |