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# /// script
# requires-python = ">=3.10"
# dependencies = [
# "numpy",
# "torch==2.8.0",
# "kernels-benchmark-tools",
# ]
#
# [tool.uv.sources]
# kernels-benchmark-tools = { path = "../../../../../tools", editable = true }
# ///
import torch
import sys
from kernels_benchmark_tools import KernelTypeEnum, run_benchmark
import torch, torch.nn.functional as F
def swiglu_eager(x):
d = x.shape[-1] // 2
return F.silu(x[..., :d]) * x[..., d:]
run_benchmark(
kernel_type=KernelTypeEnum.ACTIVATION,
impl_name="torch_eager",
impl_tags={"family":"hf-kernels", "backend":"eager"},
impl_func=swiglu_eager,
) |