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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_meshes import TestMeshes
def bm_compute_packed_padded_meshes() -> None:
devices = ["cpu"]
if torch.cuda.is_available():
devices.append("cuda")
kwargs_list = []
num_meshes = [32, 128]
max_v = [100, 1000, 10000]
max_f = [300, 3000, 30000]
test_cases = product(num_meshes, max_v, max_f, devices)
for case in test_cases:
n, v, f, d = case
kwargs_list.append({"num_meshes": n, "max_v": v, "max_f": f, "device": d})
benchmark(
TestMeshes.compute_packed_with_init,
"COMPUTE_PACKED",
kwargs_list,
warmup_iters=1,
)
benchmark(
TestMeshes.compute_padded_with_init,
"COMPUTE_PADDED",
kwargs_list,
warmup_iters=1,
)
if __name__ == "__main__":
bm_compute_packed_padded_meshes()
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