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import operator_benchmark as op_bench
import torch
import torch.nn as nn
"""
Microbenchmarks for the hardsigmoid operator.
"""
# Configs for hardsigmoid ops
hardsigmoid_configs_short = op_bench.config_list(
attr_names=[
'N', 'C', 'H', 'W'
],
attrs=[
[1, 3, 256, 256],
[4, 3, 256, 256],
],
cross_product_configs={
'device': ['cpu'],
},
tags=['short']
)
hardsigmoid_configs_long = op_bench.cross_product_configs(
N=[8, 16],
C=[3],
H=[256, 512],
W=[256, 512],
device=['cpu'],
tags=['long']
)
hardsigmoid_ops_list = op_bench.op_list(
attr_names=['op_name', 'op_func'],
attrs=[
['Hardsigmoid', nn.Hardsigmoid],
],
)
class HardsigmoidBenchmark(op_bench.TorchBenchmarkBase):
def init(self, N, C, H, W, device, op_func):
self.inputs = {
"input_one": torch.rand(N, C, H, W, device=device)
}
self.op_func = op_func()
def forward(self, input_one):
return self.op_func(input_one)
op_bench.generate_pt_tests_from_op_list(hardsigmoid_ops_list,
hardsigmoid_configs_short + hardsigmoid_configs_long,
HardsigmoidBenchmark)
if __name__ == "__main__":
op_bench.benchmark_runner.main()
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