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chore: import upstream snapshot with attribution
2026-07-13 12:32:31 +08:00

63 lines
2.1 KiB
Python

# Copyright (c) 2026 LightSeek Foundation
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
"""RMSNorm ops: rmsnorm_fused_parallel (fused parallel RMSNorm for two inputs)."""
import functools
from pathlib import Path
import torch
@functools.cache
def _load_rmsnorm_module():
import tvm_ffi
objs_dir = Path(__file__).parent / "objs" / "rmsnorm_fused_parallel"
so_path = objs_dir / "rmsnorm_fused_parallel.so"
if not so_path.exists():
raise RuntimeError(
f"tokenspeed_kernel rmsnorm library not found at {so_path}. "
"Run: pip install -e tokenspeed_kernel/python/"
)
return tvm_ffi.load_module(str(so_path))
def rmsnorm_fused_parallel(
input1: torch.Tensor,
weight1: torch.Tensor,
output1: torch.Tensor,
input2: torch.Tensor,
weight2: torch.Tensor,
output2: torch.Tensor,
eps: float = 1e-6,
enable_pdl: bool = False,
) -> None:
_load_rmsnorm_module().rmsnorm_fused_parallel(
input1,
weight1,
output1,
input2,
weight2,
output2,
float(eps),
bool(enable_pdl),
)