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055ab3a2e3
Summary:
Converts the directory specified to use the Ruff formatter in pyfmt
ruff_dog
If this diff causes merge conflicts when rebasing, please run
`hg status -n -0 --change . -I '**/*.{py,pyi}' | xargs -0 arc pyfmt`
on your diff, and amend any changes before rebasing onto latest.
That should help reduce or eliminate any merge conflicts.
allow-large-files
Reviewed By: bottler
Differential Revision: D66472063
fbshipit-source-id: 35841cb397e4f8e066e2159550d2f56b403b1bef
79 lines
2.3 KiB
Python
79 lines
2.3 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the BSD-style license found in the
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# LICENSE file in the root directory of this source tree.
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from copy import deepcopy
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from itertools import product
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from fvcore.common.benchmark import benchmark
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from tests.test_points_alignment import TestCorrespondingPointsAlignment, TestICP
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def bm_iterative_closest_point() -> None:
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case_grid = {
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"batch_size": [1, 10],
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"dim": [3, 20],
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"n_points_X": [100, 1000],
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"n_points_Y": [100, 1000],
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"use_pointclouds": [False],
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}
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test_args = sorted(case_grid.keys())
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test_cases = product(*case_grid.values())
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kwargs_list = [dict(zip(test_args, case)) for case in test_cases]
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# add the use_pointclouds=True test cases whenever we have dim==3
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kwargs_to_add = []
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for entry in kwargs_list:
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if entry["dim"] == 3:
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entry_add = deepcopy(entry)
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entry_add["use_pointclouds"] = True
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kwargs_to_add.append(entry_add)
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kwargs_list.extend(kwargs_to_add)
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benchmark(
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TestICP.iterative_closest_point,
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"IterativeClosestPoint",
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kwargs_list,
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warmup_iters=1,
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)
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def bm_corresponding_points_alignment() -> None:
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case_grid = {
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"allow_reflection": [True, False],
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"batch_size": [1, 10, 100],
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"dim": [3, 20],
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"estimate_scale": [True, False],
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"n_points": [100, 10000],
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"random_weights": [False, True],
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"use_pointclouds": [False],
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}
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test_args = sorted(case_grid.keys())
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test_cases = product(*case_grid.values())
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kwargs_list = [dict(zip(test_args, case)) for case in test_cases]
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# add the use_pointclouds=True test cases whenever we have dim==3
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kwargs_to_add = []
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for entry in kwargs_list:
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if entry["dim"] == 3:
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entry_add = deepcopy(entry)
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entry_add["use_pointclouds"] = True
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kwargs_to_add.append(entry_add)
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kwargs_list.extend(kwargs_to_add)
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benchmark(
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TestCorrespondingPointsAlignment.corresponding_points_alignment,
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"CorrespodingPointsAlignment",
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kwargs_list,
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warmup_iters=1,
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)
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if __name__ == "__main__":
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bm_corresponding_points_alignment()
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bm_iterative_closest_point()
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