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don't duplicate modules_to_not_convert

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Disty0
2026-05-21 20:44:28 +03:00
parent 9adf20a47c
commit cfafbed868
1 changed files with 3 additions and 2 deletions
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modules/sdnq/quantizer.py
+3 -2
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@@ -369,16 +369,17 @@ def apply_sdnq_to_module(model, quantization_config: "SDNQConfig", torch_dtype:
if hasattr(module, "weight") and module.weight is not None:
param_name = param_name + ".weight"
layer_class_name = module.__class__.__name__
param_in_modules_to_not_convert = check_param_name_in(param_name, quantization_config.modules_to_not_convert)
if (
layer_class_name in allowed_types
and module.weight.dtype in {torch.float64, torch.float32, torch.float16, torch.bfloat16}
and check_param_name_in(param_name, quantization_config.modules_to_not_convert) is None
and param_in_modules_to_not_convert is None
and not (layer_class_name in embedding_types and not quantization_config.quant_embedding)
and not ((layer_class_name in conv_types or layer_class_name in conv_transpose_types) and not quantization_config.quant_conv)
):
module, quantization_config = sdnq_quantize_layer(module, quantization_config, torch_dtype=torch_dtype, param_name=param_name)
setattr(model, module_name, module)
else:
elif param_in_modules_to_not_convert is None:
quantization_config.modules_to_not_convert.append(param_name)
module, quantization_config = apply_sdnq_to_module(module, quantization_config, torch_dtype=torch_dtype, full_param_name=param_name)