| # 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_packed_to_padded import TestPackedToPadded | |
| def bm_packed_to_padded() -> None: | |
| kwargs_list = [] | |
| backend = ["cpu"] | |
| if torch.cuda.is_available(): | |
| backend.append("cuda:0") | |
| num_meshes = [2, 10, 32] | |
| num_verts = [100, 1000] | |
| num_faces = [300, 3000] | |
| num_ds = [0, 1, 16] | |
| test_cases = product(num_meshes, num_verts, num_faces, num_ds, backend) | |
| for case in test_cases: | |
| n, v, f, d, b = case | |
| kwargs_list.append( | |
| {"num_meshes": n, "num_verts": v, "num_faces": f, "num_d": d, "device": b} | |
| ) | |
| benchmark( | |
| TestPackedToPadded.packed_to_padded_with_init, | |
| "PACKED_TO_PADDED", | |
| kwargs_list, | |
| warmup_iters=1, | |
| ) | |
| benchmark( | |
| TestPackedToPadded.packed_to_padded_with_init_torch, | |
| "PACKED_TO_PADDED_TORCH", | |
| kwargs_list, | |
| warmup_iters=1, | |
| ) | |
| if __name__ == "__main__": | |
| bm_packed_to_padded() | |