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https://github.com/zebrajr/pytorch.git
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f3ddc08ddc
The list of added operators: add_, addcmul, arange, baddbmm…, bmm, clamp, div, div_, gelu, index_add, logical_and, mul_, sub_, topk, where This pull request is the same as a previous one: https://github.com/pytorch/pytorch/pull/145121 which inadvertently got deleted while merging. Pull Request resolved: https://github.com/pytorch/pytorch/pull/145625 Approved by: https://github.com/jeffdaily
47 lines
1.1 KiB
Python
47 lines
1.1 KiB
Python
import operator_benchmark as op_bench
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import torch
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"""Microbenchmarks for topk operator"""
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topk_configs_short = op_bench.config_list(
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attr_names=["shape", "k", "dim"],
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attrs=[
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[(16, 4), 4, 1],
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[(1024 * 1024,), 16, 0],
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],
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cross_product_configs={"device": ["cpu"], "dtype": [torch.float]},
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tags=["short"],
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)
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topk_configs_long = op_bench.cross_product_configs(
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shape=[(64, 2), (1024 * 1024,), (128,)],
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k=[1, 2, 4, 16, 32],
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dim=[0],
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device=["cpu", "cuda"],
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dtype=[torch.float, torch.bfloat16],
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tags=["long"],
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)
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class TopkBenchmark(op_bench.TorchBenchmarkBase):
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def init(self, shape, k, dim, dtype, device):
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self.inputs = {
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"input": torch.randn(shape, device=device, dtype=dtype),
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"k": k,
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"dim": dim,
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}
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self.set_module_name("topk")
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def forward(self, input, k, dim):
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return torch.topk(input, k=k, dim=dim)
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op_bench.generate_pt_test(topk_configs_short + topk_configs_long, TopkBenchmark)
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if __name__ == "__main__":
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op_bench.benchmark_runner.main()
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