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Update.
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@ -928,6 +928,7 @@ def mixed_precision_ops(quant_config={}, compute_dtype=torch.bfloat16, full_prec
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weight = state_dict.pop(weight_key, None)
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if weight is None:
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logging.warning(f"Missing weight for layer {layer_name}")
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self.weight = None
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return
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manually_loaded_keys = [weight_key]
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@ -1034,6 +1035,9 @@ def mixed_precision_ops(quant_config={}, compute_dtype=torch.bfloat16, full_prec
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if self.bias is not None:
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sd["{}bias".format(prefix)] = self.bias
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if self.weight is None:
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return sd
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if isinstance(self.weight, QuantizedTensor):
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sd_out = self.weight.state_dict("{}weight".format(prefix))
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for k in sd_out:
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