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Fix scale and zero_point not being moved by tensor.to

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Disty0
2025-05-28 17:46:06 +03:00
parent dd0dbc476f
commit dd33c4d583
1 changed files with 6 additions and 6 deletions
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modules/model_quant_sdnq.py
+6 -6
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@@ -345,10 +345,10 @@ class AsymmetricWeightsDecompressor(torch.nn.Module):
super().__init__()
self.weights_dtype = weights_dtype
self.use_quantized_matmul = False
self.scale = scale
self.zero_point = zero_point
self.result_dtype = result_dtype
self.result_shape = result_shape
self.register_buffer("scale", scale)
self.register_buffer("zero_point", zero_point)
def pack_weight(self, weight: torch.Tensor) -> torch.Tensor:
return weight.to(dtype=dtype_dict[self.weights_dtype]["torch_dtype"])
@@ -370,9 +370,9 @@ class SymmetricWeightsDecompressor(torch.nn.Module):
super().__init__()
self.weights_dtype = weights_dtype
self.use_quantized_matmul = use_quantized_matmul
self.scale = scale
self.result_dtype = result_dtype
self.result_shape = result_shape
self.register_buffer("scale", scale)
def pack_weight(self, weight: torch.Tensor) -> torch.Tensor:
return weight.to(dtype=dtype_dict[self.weights_dtype]["torch_dtype"])
@@ -394,11 +394,11 @@ class INT4AsymmetricWeightsDecompressor(torch.nn.Module):
super().__init__()
self.weights_dtype = "uint4"
self.use_quantized_matmul = False
self.scale = scale
self.zero_point = zero_point
self.compressed_weight_shape = compressed_weight_shape
self.result_dtype = result_dtype
self.result_shape = result_shape
self.register_buffer("scale", scale)
self.register_buffer("zero_point", zero_point)
def pack_weight(self, weight: torch.Tensor) -> torch.Tensor:
return pack_uint4(weight.to(dtype=torch.uint8))
@@ -420,10 +420,10 @@ class INT4SymmetricWeightsDecompressor(torch.nn.Module):
super().__init__()
self.weights_dtype = "int4"
self.use_quantized_matmul = use_quantized_matmul
self.scale = scale
self.compressed_weight_shape = compressed_weight_shape
self.result_dtype = result_dtype
self.result_shape = result_shape
self.register_buffer("scale", scale)
def pack_weight(self, weight: torch.Tensor) -> torch.Tensor:
return pack_int4(weight.to(dtype=torch.int8))