mirror of
https://github.com/facebookresearch/pytorch3d.git
synced 2025-08-02 03:42:50 +08:00
a0e2d2e3c3
Summary: Move benchmarks to a separate directory as tests/ is getting big. Reviewed By: nikhilaravi Differential Revision: D32885462 fbshipit-source-id: a832662a494ee341ab77d95493c95b0af0a83f43
81 lines
2.3 KiB
Python
81 lines
2.3 KiB
Python
# Copyright (c) Facebook, Inc. and its 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 copy import deepcopy
|
|
from itertools import product
|
|
|
|
from fvcore.common.benchmark import benchmark
|
|
from test_points_alignment import TestCorrespondingPointsAlignment, TestICP
|
|
|
|
|
|
def bm_iterative_closest_point() -> None:
|
|
|
|
case_grid = {
|
|
"batch_size": [1, 10],
|
|
"dim": [3, 20],
|
|
"n_points_X": [100, 1000],
|
|
"n_points_Y": [100, 1000],
|
|
"use_pointclouds": [False],
|
|
}
|
|
|
|
test_args = sorted(case_grid.keys())
|
|
test_cases = product(*case_grid.values())
|
|
kwargs_list = [dict(zip(test_args, case)) for case in test_cases]
|
|
|
|
# add the use_pointclouds=True test cases whenever we have dim==3
|
|
kwargs_to_add = []
|
|
for entry in kwargs_list:
|
|
if entry["dim"] == 3:
|
|
entry_add = deepcopy(entry)
|
|
entry_add["use_pointclouds"] = True
|
|
kwargs_to_add.append(entry_add)
|
|
kwargs_list.extend(kwargs_to_add)
|
|
|
|
benchmark(
|
|
TestICP.iterative_closest_point,
|
|
"IterativeClosestPoint",
|
|
kwargs_list,
|
|
warmup_iters=1,
|
|
)
|
|
|
|
|
|
def bm_corresponding_points_alignment() -> None:
|
|
|
|
case_grid = {
|
|
"allow_reflection": [True, False],
|
|
"batch_size": [1, 10, 100],
|
|
"dim": [3, 20],
|
|
"estimate_scale": [True, False],
|
|
"n_points": [100, 10000],
|
|
"random_weights": [False, True],
|
|
"use_pointclouds": [False],
|
|
}
|
|
|
|
test_args = sorted(case_grid.keys())
|
|
test_cases = product(*case_grid.values())
|
|
kwargs_list = [dict(zip(test_args, case)) for case in test_cases]
|
|
|
|
# add the use_pointclouds=True test cases whenever we have dim==3
|
|
kwargs_to_add = []
|
|
for entry in kwargs_list:
|
|
if entry["dim"] == 3:
|
|
entry_add = deepcopy(entry)
|
|
entry_add["use_pointclouds"] = True
|
|
kwargs_to_add.append(entry_add)
|
|
kwargs_list.extend(kwargs_to_add)
|
|
|
|
benchmark(
|
|
TestCorrespondingPointsAlignment.corresponding_points_alignment,
|
|
"CorrespodingPointsAlignment",
|
|
kwargs_list,
|
|
warmup_iters=1,
|
|
)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
bm_corresponding_points_alignment()
|
|
bm_iterative_closest_point()
|