mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-31 20:02:53 +08:00
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
"""
|
|
# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
"""
|
|
|
|
import paddle
|
|
from paddle.nn.quant import weight_dequantize
|
|
|
|
from fastdeploy.model_executor.layers.quantization.weight_only import (
|
|
GPUWeightOnlyLinearMethod,
|
|
WeightOnlyConfig,
|
|
)
|
|
|
|
|
|
class DCUWeightOnlyLinearMethod(GPUWeightOnlyLinearMethod):
|
|
"""
|
|
Weight only quantization method for linear layer on GPU
|
|
The weights are loaded in the BF16 numerical format. After loading, the quantization coefficients will be computed,
|
|
and the weights will be quantized to int8 or int4.
|
|
"""
|
|
|
|
def __init__(
|
|
self,
|
|
quant_config: WeightOnlyConfig,
|
|
) -> None:
|
|
super().__init__(quant_config)
|
|
|
|
def apply(self, layer, x):
|
|
dequant_out = weight_dequantize(
|
|
x=layer.weight,
|
|
scale=layer.weight_scale,
|
|
algo=self.quant_config.algo,
|
|
out_dtype=paddle.get_default_dtype(),
|
|
)
|
|
linear_out = paddle.matmul(x, dequant_out)
|
|
if layer.bias is not None:
|
|
linear_out = paddle.add(linear_out, layer.bias)
|
|
return linear_out
|