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chore: import upstream snapshot with attribution
2026-07-13 12:49:27 +08:00

48 lines
1.5 KiB
Python

# LICENSE HEADER MANAGED BY add-license-header
#
# Copyright 2018 Kornia Team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from itertools import product
import torch
from torch.utils import benchmark
# Compare takes a list of measurements which we'll save in results.
results = []
sizes = [1, 64, 1024]
for b, _ in product(sizes, sizes):
# label and sub_label are the rows
# description is the column
label = "get_perspective_transform"
sub_label = f"[{b}, {4}, {2}]"
x = torch.rand((b, 4, 2))
for num_threads in [1, 4, 16, 32]:
results.append(
benchmark.Timer(
stmt="get_perspective_transform(x, x)",
setup="from kornia.geometry import get_perspective_transform",
globals={"x": x},
num_threads=num_threads,
label=label,
sub_label=sub_label,
description="get_perspective_transform",
).blocked_autorange(min_run_time=1)
)
compare = benchmark.Compare(results)
compare.print()