mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
dd3a77bc96
Signed-off-by: Edward Z. Yang <ezyang@meta.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/105928 Approved by: https://github.com/albanD
45 lines
1.0 KiB
Python
45 lines
1.0 KiB
Python
import torch
|
|
|
|
import operator_benchmark as op_bench
|
|
|
|
|
|
"""Microbenchmarks for Split operator"""
|
|
|
|
|
|
# Configs for PT Split operator
|
|
split_configs_short = op_bench.config_list(
|
|
attr_names=["M", "N", "parts"],
|
|
attrs=[
|
|
[8, 8, 2],
|
|
[256, 512, 2],
|
|
[512, 512, 2],
|
|
],
|
|
cross_product_configs={
|
|
"device": ["cpu", "cuda"],
|
|
},
|
|
tags=["short"],
|
|
)
|
|
|
|
split_configs_long = op_bench.cross_product_configs(
|
|
M=[128, 1024], N=[128, 1024], parts=[2, 4], device=["cpu", "cuda"], tags=["long"]
|
|
)
|
|
|
|
|
|
class SplitBenchmark(op_bench.TorchBenchmarkBase):
|
|
def init(self, M, N, parts, device):
|
|
self.inputs = {
|
|
"input": torch.rand(M, N, device=device),
|
|
"split_size": int(M * N / parts),
|
|
}
|
|
self.set_module_name("split")
|
|
|
|
def forward(self, input, split_size: int):
|
|
return torch.split(input, split_size)
|
|
|
|
|
|
op_bench.generate_pt_test(split_configs_short + split_configs_long, SplitBenchmark)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
op_bench.benchmark_runner.main()
|