wehub-resource-sync
59a0a3844c
PR Test AMD / cancel-on-close (push) Has been skipped
PR Test NVIDIA ARM / scan (push) Has been skipped
PR Test NVIDIA / cancel-on-close (push) Has been skipped
PR Test AMD / scan (push) Has been skipped
PR Test NVIDIA ARM / cancel-on-close (push) Has been skipped
PR Test NVIDIA / scan (push) Has been skipped
Release Docker Images / build (cu129-torch-2.11.0) (push) Has been skipped
Release Docker Images / build (cu130-torch-2.11.0) (push) Has been skipped
Release PyPI / publish (push) Has been skipped
Scheduler Python Test / test (push) Successful in 27m19s
Docs / build (push) Successful in 28m8s
Scheduler C++ Test / test (push) Successful in 28m19s
Scheduler C++ Test / test-flat (push) Successful in 28m18s
Docs / deploy (push) Has been cancelled
PR Test AMD / finish (push) Has been cancelled
PR Test NVIDIA / finish (push) Has been cancelled
PR Test NVIDIA ARM / finish (push) Has been cancelled
PR Test NVIDIA ARM / ${{ matrix.name }} (${{ matrix.runner }}) (push) Has been cancelled
PR Test AMD / ${{ matrix.name }} (${{ matrix.runner }}) (push) Has been cancelled
PR Test NVIDIA / ${{ matrix.name }} (${{ matrix.runner }}) (push) Has been cancelled
47 lines
2.0 KiB
Python
47 lines
2.0 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.
|
|
|
|
|
|
import torch
|
|
|
|
|
|
def normalize_e4m3fn_to_e4m3fnuz(
|
|
weight: torch.Tensor,
|
|
weight_scale: torch.Tensor,
|
|
input_scale: torch.Tensor | None = None,
|
|
) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor | None]:
|
|
assert weight.dtype == torch.float8_e4m3fn
|
|
# The bits pattern 10000000(-128) represents zero in e4m3fn
|
|
# but NaN in e4m3fnuz. So here we set it to 0.
|
|
# https://onnx.ai/onnx/technical/float8.html
|
|
weight_as_int8 = weight.view(torch.int8)
|
|
ROCM_FP8_NAN_AS_INT = -128
|
|
weight_as_int8[weight_as_int8 == ROCM_FP8_NAN_AS_INT] = 0
|
|
weight = weight_as_int8.view(torch.float8_e4m3fnuz)
|
|
|
|
# For the same bits representation, e4m3fnuz value is half of
|
|
# the e4m3fn value, so we should double the scaling factor to
|
|
# get the same dequantized value.
|
|
# https://onnx.ai/onnx/technical/float8.html
|
|
weight_scale = weight_scale * 2.0
|
|
if input_scale is not None:
|
|
input_scale = input_scale * 2.0
|
|
return weight, weight_scale, input_scale
|