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# 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() | |