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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
from fvcore.common.benchmark import benchmark
from tests.test_iou_box3d import TestIoU3D
def bm_iou_box3d() -> None:
# Realistic use cases
N = [30, 100]
M = [5, 10, 100]
kwargs_list = []
test_cases = product(N, M)
for case in test_cases:
n, m = case
kwargs_list.append({"N": n, "M": m, "device": "cuda:0"})
benchmark(TestIoU3D.iou, "3D_IOU", kwargs_list, warmup_iters=1)
# Comparison of C++/CUDA
kwargs_list = []
N = [1, 4, 8, 16]
devices = ["cpu", "cuda:0"]
test_cases = product(N, N, devices)
for case in test_cases:
n, m, d = case
kwargs_list.append({"N": n, "M": m, "device": d})
benchmark(TestIoU3D.iou, "3D_IOU", kwargs_list, warmup_iters=1)
# Naive PyTorch
N = [1, 4]
kwargs_list = []
test_cases = product(N, N)
for case in test_cases:
n, m = case
kwargs_list.append({"N": n, "M": m, "device": "cuda:0"})
benchmark(TestIoU3D.iou_naive, "3D_IOU_NAIVE", kwargs_list, warmup_iters=1)
# Sampling based method
num_samples = [2000, 5000]
kwargs_list = []
test_cases = product(N, N, num_samples)
for case in test_cases:
n, m, s = case
kwargs_list.append({"N": n, "M": m, "num_samples": s, "device": "cuda:0"})
benchmark(TestIoU3D.iou_sampling, "3D_IOU_SAMPLING", kwargs_list, warmup_iters=1)
if __name__ == "__main__":
bm_iou_box3d()
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