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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/28731 as title Test Plan: ``` Before: buck run mode/opt caffe2/benchmarks/operator_benchmark:benchmark_all_test -- --operator sigmoid Invalidating internal cached state: Buck configuration options changed between invocations. This may cause slower builds. Changed value project.buck_out='buck-out/opt' (was 'buck-out/dev') ... and 69 more. See logs for all changes Parsing buck files: finished in 7.2 sec Creating action graph: finished in 10.0 sec Building: finished in 06:38.4 min (100%) 29890/29890 jobs, 29890 updated Total time: 06:55.7 min # ---------------------------------------- # PyTorch/Caffe2 Operator Micro-benchmarks # ---------------------------------------- # Tag : short # Benchmarking PyTorch: sigmoid With this diff buck run mode/opt caffe2/benchmarks/operator_benchmark:benchmark_all_test -- --operator sigmoid Parsing buck files: finished in 6.4 sec Creating action graph: finished in 9.8 sec Building: finished in 06:35.9 min (100%) 29892/29892 jobs, 29892 updated Total time: 06:52.1 min Reviewed By: hl475 Differential Revision: D18152071 fbshipit-source-id: 80c29570581bbd2f0e78e2df32734c17a2b036ee
53 lines
1.4 KiB
Python
53 lines
1.4 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import operator_benchmark as op_bench
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import benchmark_caffe2 as op_bench_c2
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from benchmark_caffe2 import Caffe2BenchmarkBase # noqa
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from caffe2.python import core
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"""Microbenchmarks for element-wise Add operator. Supports both Caffe2/PyTorch."""
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# Configs for C2 add operator
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add_long_configs = op_bench.cross_product_configs(
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M=[8, 64, 128],
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N=range(2, 10, 3),
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K=[2 ** x for x in range(0, 3)],
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dtype=["int", "float"],
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tags=["long"]
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)
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add_short_configs = op_bench.config_list(
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attrs=[
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[8, 16, 32, "int"],
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[16, 16, 64, "float"],
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[64, 64, 128, "int"],
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],
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attr_names=["M", "N", "K", "dtype"],
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tags=["short"],
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)
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class AddBenchmark(op_bench_c2.Caffe2BenchmarkBase):
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def init(self, M, N, K, dtype):
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self.input_one = self.tensor([M, N, K], dtype)
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self.input_two = self.tensor([M, N, K], dtype)
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self.output = self.tensor([M, N, K], dtype)
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self.set_module_name("add")
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def forward(self):
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op = core.CreateOperator(
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"Add", [self.input_one, self.input_two], self.output, **self.args
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)
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return op
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op_bench_c2.generate_c2_test(add_long_configs + add_short_configs, AddBenchmark)
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if __name__ == "__main__":
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op_bench.benchmark_runner.main()
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