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SDNQ Flux lora, use shape from sdnq_dequantizer

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Disty0
2025-08-18 19:53:57 +03:00
parent 0f72024999
commit 47154db8b1
2 changed files with 9 additions and 14 deletions
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modules/sdnq/__init__.py
+1 -10
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@@ -245,15 +245,6 @@ def apply_sdnq_to_module(model, weights_dtype="int8", torch_dtype=None, group_si
return model
class SDNQParameter(torch.nn.Parameter):
def __new__(cls, data=None, requires_grad=False):
return super().__new__(cls, data, requires_grad)
def __init__(self, data=None, requires_grad=False): # pylint: disable=unused-argument
self.original_shape = data.shape
super().__init__()
class SDNQQuantizer(DiffusersQuantizer):
r"""
Diffusers Quantizer for SDNQ
@@ -342,7 +333,7 @@ class SDNQQuantizer(DiffusersQuantizer):
param_value = param_value.to(target_device, non_blocking=self.quantization_config.non_blocking).to(dtype=torch.float32)
layer, _ = get_module_from_name(model, param_name)
layer.weight = SDNQParameter(param_value, requires_grad=False)
layer.weight = torch.nn.Parameter(param_value, requires_grad=False)
layer = sdnq_quantize_layer(
layer,
weights_dtype=weights_dtype,