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c0ed38e644
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
56 lines
1.4 KiB
Python
56 lines
1.4 KiB
Python
import operator_benchmark as op_bench
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import torch
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"""Microbenchmarks for ClipRanges operator."""
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torch.ops.load_library("//caffe2/torch/fb/sparsenn:sparsenn_operators")
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# Configs for C2 ClipRanges operator
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clip_ranges_long_configs = op_bench.cross_product_configs(
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LENGTH=range(1, 100),
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M=[1],
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N=[2],
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MAX_LENGTH=range(1, 100),
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device=["cpu", "cuda"],
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dtype=[torch.int32],
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tags=["long"],
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)
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clip_ranges_short_configs = op_bench.config_list(
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attrs=[
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[6, 1, 2, 1, torch.int32],
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[7, 1, 2, 2, torch.int32],
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[8, 1, 2, 3, torch.int32],
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[9, 1, 2, 4, torch.int32],
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[10, 1, 2, 5, torch.int32],
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],
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attr_names=["LENGTH", "M", "N", "MAX_LENGTH", "dtype"],
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cross_product_configs={
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"device": ["cpu", "cuda"],
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},
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tags=["short"],
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)
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class ClipRangesBenchmark(op_bench.TorchBenchmarkBase):
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def init(self, LENGTH, M, N, MAX_LENGTH, device, dtype):
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self.inputs = {
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"input": torch.rand(LENGTH, M, N, device=device).type(dtype),
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"max_length": MAX_LENGTH,
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}
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self.set_module_name("clip_ranges")
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def forward(self, input, max_length: int):
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return torch.ops.fb.clip_ranges(input, max_length)
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op_bench.generate_pt_test(
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clip_ranges_long_configs + clip_ranges_short_configs, ClipRangesBenchmark
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)
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if __name__ == "__main__":
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op_bench.benchmark_runner.main()
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