Files
pytorch/benchmarks/operator_benchmark/pt/sum_test.py
Xuehai Pan 26f4f10ac8 [5/N][Easy] fix typo for usort config in pyproject.toml (kown -> known): sort torch (#127126)
The `usort` config in `pyproject.toml` has no effect due to a typo. Fixing the typo make `usort` do more and generate the changes in the PR. Except `pyproject.toml`, all changes are generated by `lintrunner -a --take UFMT --all-files`.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/127126
Approved by: https://github.com/kit1980
2024-05-27 14:49:57 +00:00

47 lines
1.3 KiB
Python

import operator_benchmark as op_bench
import torch
"""Microbenchmarks for sum reduction operator."""
# Configs for PT add operator
sum_configs = op_bench.cross_product_configs(
R=[64, 256], # Length of reduced dimension
V=[32, 512], # Length of other dimension
dim=[0, 1],
contiguous=[True, False],
device=["cpu", "cuda"],
tags=["short"],
) + op_bench.cross_product_configs(
R=[1024, 8192],
V=[512, 1024],
dim=[0, 1],
contiguous=[True, False],
device=["cpu", "cuda"],
tags=["long"],
)
class SumBenchmark(op_bench.TorchBenchmarkBase):
def init(self, R, V, dim, contiguous, device):
shape = (R, V) if dim == 0 else (V, R)
tensor = torch.rand(shape, device=device)
if not contiguous:
storage = torch.empty([s * 2 for s in shape], device=device)
storage[::2, ::2] = tensor
self.input_tensor = storage[::2, ::2]
else:
self.input_tensor = tensor
self.inputs = {"input_tensor": self.input_tensor, "dim": dim}
self.set_module_name("sum")
def forward(self, input_tensor, dim: int):
return input_tensor.sum(dim=dim)
op_bench.generate_pt_test(sum_configs, SumBenchmark)
if __name__ == "__main__":
op_bench.benchmark_runner.main()