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import operator_benchmark as op_bench
import benchmark_caffe2 as op_bench_c2
from benchmark_caffe2 import Caffe2BenchmarkBase # noqa: F401
from caffe2.python import core
"""Microbenchmarks for element-wise Add operator. Supports both Caffe2/PyTorch."""
# Configs for C2 add operator
add_long_configs = op_bench.cross_product_configs(
M=[8, 64, 128],
N=range(2, 10, 3),
K=[2 ** x for x in range(0, 3)],
dtype=["int", "float"],
tags=["long"]
)
add_short_configs = op_bench.config_list(
attrs=[
[8, 16, 32, "int"],
[16, 16, 64, "float"],
[64, 64, 128, "int"],
],
attr_names=["M", "N", "K", "dtype"],
tags=["short"],
)
class AddBenchmark(op_bench_c2.Caffe2BenchmarkBase):
def init(self, M, N, K, dtype):
self.input_one = self.tensor([M, N, K], dtype)
self.input_two = self.tensor([M, N, K], dtype)
self.output = self.tensor([M, N, K], dtype)
self.set_module_name("add")
def forward(self):
op = core.CreateOperator(
"Add", [self.input_one, self.input_two], self.output, **self.args
)
return op
op_bench_c2.generate_c2_test(add_long_configs + add_short_configs, AddBenchmark)
if __name__ == "__main__":
op_bench.benchmark_runner.main()
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