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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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35
fastdeploy/model_executor/layers/quantization/w8a8.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
@@ -30,8 +31,13 @@ class W8A8Config(QuantConfigBase):
quantization config for weight 8bits and activation 8bits
"""
def __init__(self, weight_scale_dict, act_scale_dict, use_gemm_dequant,
use_smooth_quant) -> None:
def __init__(
self,
weight_scale_dict,
act_scale_dict,
use_gemm_dequant,
use_smooth_quant,
) -> None:
super().__init__()
self.weight_scale_dict = weight_scale_dict
self.act_scale_dict = act_scale_dict
@@ -73,27 +79,22 @@ class W8A8LinearMethod(QuantMethodBase):
layer.weight_dtype = "int8"
if self.quant_config.use_smooth_quant:
self.smooth_quant_method.create_weights(layer)
weight_scale = self.quant_config.weight_scale_dict.get(layer.prefix +
".weight_scale")
in_scale = self.quant_config.act_scale_dict.get(layer.prefix +
".activation_scale")
weight_scale = self.quant_config.weight_scale_dict.get(layer.prefix + ".weight_scale")
in_scale = self.quant_config.act_scale_dict.get(layer.prefix + ".activation_scale")
self.skip_quant = False
if weight_scale is None or in_scale is None:
self.skip_quant = True
return
max_range = 127.0
linear_out_scale = paddle.to_tensor(
weight_scale /
(max_range * max_range * in_scale)).astype("float32")
linear_out_scale = paddle.to_tensor(weight_scale / (max_range * max_range * in_scale)).astype("float32")
layer.linear_out_scale = layer.create_parameter(
shape=[layer.embed_dim],
dtype="float32",
is_bias=False,
default_initializer=paddle.nn.initializer.Constant(0),
)
layer.linear_out_scale.set_value(
convert_to_npu_dequant_scale(linear_out_scale))
layer.linear_out_scale.set_value(convert_to_npu_dequant_scale(linear_out_scale))
def process_loaded_weights(self, layer, weights) -> None:
if self.quant_config.use_smooth_quant:
@@ -113,11 +114,13 @@ class W8A8LinearMethod(QuantMethodBase):
return linear_out
if self.quant_config.use_gemm_dequant:
linear_out = fastdeploy.model_executor.ops.gpu.gemm_dequant(
x, layer.weight, layer.linear_out_scale, layer._dtype)
x, layer.weight, layer.linear_out_scale, layer._dtype
)
else:
linear_out = paddle.matmul(x, layer.weight, False, True)
linear_out = fastdeploy.model_executor.ops.gpu.dequant_int8(
linear_out, layer.linear_out_scale, layer._dtype)
linear_out, layer.linear_out_scale, layer._dtype
)
return linear_out
@@ -149,8 +152,7 @@ class SmoothQuantLinearMethod(QuantMethodBase):
def process_loaded_weights(self, layer, weights) -> None:
if layer.shift_key in layer.state_dict:
shift_tensor = get_tensor(layer.state_dict.pop(
layer.shift_key)).astype(paddle.get_default_dtype())
shift_tensor = get_tensor(layer.state_dict.pop(layer.shift_key)).astype(paddle.get_default_dtype())
else:
shift_tensor = paddle.zeros(
shape=layer.linear_shift_shape,
@@ -158,8 +160,7 @@ class SmoothQuantLinearMethod(QuantMethodBase):
)
layer.linear_shift.set_value(shift_tensor)
if layer.smooth_key in layer.state_dict:
smooth_tensor = get_tensor(layer.state_dict.pop(
layer.smooth_key)).astype(paddle.get_default_dtype())
smooth_tensor = get_tensor(layer.state_dict.pop(layer.smooth_key)).astype(paddle.get_default_dtype())
else:
smooth_tensor = paddle.ones(
shape=[layer.linear_smooth_shape],