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benchmark.py
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benchmark.py
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import glob
import os
import torch
from speed_benchmark import speed_benchmark
from torch.utils.cpp_extension import load
def ncrelu(x):
return torch.cat([x.clamp(min=0), x.clamp(max=0)], dim=1)
def main():
b = 8
h = 128
w = 128
experiment_name = "cmake"
device = "cuda"
if "setup" in experiment_name:
import ops
if "jit" in experiment_name:
ops = load(
name="ops",
sources=glob.glob("ops/**/*.cpp", recursive=True)
+ glob.glob("ops/**/*.cu", recursive=True),
extra_include_paths=[os.path.abspath("ops/include")],
)
elif "cmake" in experiment_name:
torch.ops.load_library("build/libops.so")
ops = torch.ops.ops
funcs = [
ncrelu,
ops.ncrelu_forward,
torch.nn.functional.relu,
ops.relu_forward,
]
args = {
"main_arg_name": "c",
"data": {
c: {
"args": [torch.randn((b, c, h, w), device=device)],
}
for c in [10, 100, 200, 300]
+ ([] if device == "cpu" else [500, 700, 800, 1000])
},
}
speed_benchmark(
funcs,
args,
repeat=10,
num=10,
experiment_name=experiment_name,
check_result=False,
)
if __name__ == "__main__":
main()