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See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. Most changes are auto-generated by linter. You can review these PRs via: ```bash git diff --ignore-all-space --ignore-blank-lines HEAD~1 ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/129754 Approved by: https://github.com/ezyang
57 lines
1.2 KiB
Python
57 lines
1.2 KiB
Python
import operator_benchmark as op_bench
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import torch
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import torch.nn as nn
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"""
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Microbenchmarks for the hardsigmoid operator.
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"""
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# Configs for hardsigmoid ops
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hardsigmoid_configs_short = op_bench.config_list(
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attr_names=["N", "C", "H", "W"],
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attrs=[
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[1, 3, 256, 256],
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[4, 3, 256, 256],
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],
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cross_product_configs={
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"device": ["cpu"],
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},
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tags=["short"],
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)
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hardsigmoid_configs_long = op_bench.cross_product_configs(
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N=[8, 16], C=[3], H=[256, 512], W=[256, 512], device=["cpu"], tags=["long"]
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)
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hardsigmoid_ops_list = op_bench.op_list(
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attr_names=["op_name", "op_func"],
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attrs=[
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["Hardsigmoid", nn.Hardsigmoid],
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],
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)
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class HardsigmoidBenchmark(op_bench.TorchBenchmarkBase):
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def init(self, N, C, H, W, device, op_func):
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self.inputs = {"input_one": torch.rand(N, C, H, W, device=device)}
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self.op_func = op_func()
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def forward(self, input_one):
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return self.op_func(input_one)
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op_bench.generate_pt_tests_from_op_list(
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hardsigmoid_ops_list,
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hardsigmoid_configs_short + hardsigmoid_configs_long,
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HardsigmoidBenchmark,
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)
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if __name__ == "__main__":
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op_bench.benchmark_runner.main()
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