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polish code with new pre-commit rule (#2923)

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Zero Rains
2025-07-19 23:19:27 +08:00
committed by GitHub
parent b8676d71a8
commit 25698d56d1
424 changed files with 14307 additions and 13518 deletions
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32
fastdeploy/model_executor/layers/quantization/block_wise_fp8.py
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@@ -13,6 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
"""
from typing import Optional
import paddle
@@ -49,17 +50,20 @@ class BlockWiseFP8Config(QuantConfigBase):
return cls(weight_block_size)
def get_quant_method(self, layer) -> Optional[QuantMethodBase]:
'''
"""
Get quantization method.
'''
"""
if isinstance(layer, FusedMoE):
if self.use_deep_gemm:
from fastdeploy.model_executor.layers.moe.fused_moe_deepgemm_backend import \
DeepGemmFusedMoeMethod
from fastdeploy.model_executor.layers.moe.fused_moe_deepgemm_backend import (
DeepGemmFusedMoeMethod,
)
return DeepGemmFusedMoeMethod(self)
else:
from fastdeploy.model_executor.layers.moe.fused_moe_triton_backend import \
BlockWiseFP8MoEMethod
from fastdeploy.model_executor.layers.moe.fused_moe_triton_backend import (
BlockWiseFP8MoEMethod,
)
return BlockWiseFP8MoEMethod(self)
else:
return BlockWiseFP8LinearMethod(self)
@@ -81,8 +85,8 @@ class BlockWiseFP8LinearMethod(QuantMethodBase):
layer.weight_shape.reverse()
layer.weight_scale = layer.create_parameter(
shape=[
(layer.output_size + self.quant_config.weight_block_size[0] -
1) // self.quant_config.weight_block_size[0],
(layer.output_size + self.quant_config.weight_block_size[0] - 1)
// self.quant_config.weight_block_size[0],
(layer.input_size + self.quant_config.weight_block_size[1] - 1)
// self.quant_config.weight_block_size[1],
],
@@ -93,8 +97,7 @@ class BlockWiseFP8LinearMethod(QuantMethodBase):
def process_loaded_weights(self, layer, weights) -> None:
weight_tensor = weights.transpose([1, 0])
quanted_weight_tensor, weight_block_scale_tensor = (
per_block_cast_to_fp8(weight_tensor))
quanted_weight_tensor, weight_block_scale_tensor = per_block_cast_to_fp8(weight_tensor)
layer.weight.copy_(quanted_weight_tensor, False)
layer.weight_scale.set_value(weight_block_scale_tensor)
@@ -113,10 +116,11 @@ class BlockWiseFP8LinearMethod(QuantMethodBase):
def apply(self, layer, x):
x, x_scale_tensor = fastdeploy.model_executor.ops.gpu.per_token_quant_padding(
x, self.quant_config.weight_block_size[0])
linear_out = paddle.empty((x.shape[0], layer.output_size),
dtype=paddle.bfloat16)
import fastdeploy.model_executor.ops.gpu.deep_gemm as deep_gemm
x, self.quant_config.weight_block_size[0]
)
linear_out = paddle.empty((x.shape[0], layer.output_size), dtype=paddle.bfloat16)
from fastdeploy.model_executor.ops.gpu import deep_gemm
deep_gemm.gemm_fp8_fp8_bf16_nt(
(x, x_scale_tensor),
(layer.weight, layer.weight_scale),