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load hadamard_block_size from config (#3797)

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This commit is contained in:
Yuan Xiaolan
2025-09-05 17:07:58 +08:00
committed by GitHub
parent 41aee08982
commit 2cf55168ca
10 changed files with 60 additions and 30 deletions
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6
fastdeploy/model_executor/layers/quantization/w4afp8.py
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@@ -31,7 +31,7 @@ class W4AFP8Config(QuantConfigBase):
quantization config for weight 4bits and activation fp8
"""
def __init__(self, weight_scale_dict, act_scale_dict, is_permuted) -> None:
def __init__(self, weight_scale_dict, act_scale_dict, is_permuted, hadamard_block_size) -> None:
super().__init__()
self.weight_scale_dict = weight_scale_dict
self.act_scale_dict = act_scale_dict
@@ -39,6 +39,7 @@ class W4AFP8Config(QuantConfigBase):
self.quant_min_bound = -448
self.quant_round_type = 1
self.is_permuted = is_permuted
self.hadamard_block_size = hadamard_block_size
def name(self) -> str:
return "w4afp8"
@@ -48,7 +49,8 @@ class W4AFP8Config(QuantConfigBase):
weight_scale_dict = config.get("weight_scale_dict", None)
act_scale_dict = config.get("act_scale_dict", None)
is_permuted = config.get("is_permuted", True)
return cls(weight_scale_dict, act_scale_dict, is_permuted)
hadamard_block_size = config.get("hadamard_block_size", 128)
return cls(weight_scale_dict, act_scale_dict, is_permuted, hadamard_block_size)
def get_quant_method(self, layer) -> Optional[QuantMethodBase]:
if isinstance(layer, FusedMoE):