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10 changes: 2 additions & 8 deletions neural_compressor/torch/algorithms/weight_only/gptq.py
Original file line number Diff line number Diff line change
Expand Up @@ -930,12 +930,7 @@ def tmp(_, inp, out):

logger.info("Quantization done")
# self.model.config.use_cache = self.use_cache

# obtain model (all weight only quantization API function should return)
for k, v in gptq_config.items():
for m, n in v.items():
gptq_config[k][m] = n.tolist()
return self.model, gptq_config
return self.model


class GPTQ:
Expand Down Expand Up @@ -1379,9 +1374,8 @@ def convert(self, model, *args, **kwargs):
self.gptq_quantizer.model = model
self.gptq_quantizer.remove_prepare_for_calibration()

q_model, gptq_config = self.gptq_quantizer.execute_quantization()
q_model = self.gptq_quantizer.execute_quantization()
if not self.gptq_quantizer.use_layer_wise:
q_model = q_model.to(self.model_device)
q_model.gptq_config = gptq_config
logger.info("GPTQ quantizing done.")
return q_model
5 changes: 0 additions & 5 deletions neural_compressor/torch/algorithms/weight_only/save_load.py
Original file line number Diff line number Diff line change
Expand Up @@ -53,11 +53,6 @@ def save(model, output_dir="./saved_results"):
# saving process
save_config_mapping(model.qconfig, qconfig_file_path)

if hasattr(model, "gptq_config") and model.gptq_config:
gptq_config_path = os.path.join(os.path.abspath(os.path.expanduser(output_dir)), "gptq_config.json")
with open(gptq_config_path, "w") as f:
json.dump(model.gptq_config, f, indent=4)

# MethodType 'save' not in state_dict
del model.save
torch.save(model.state_dict(), qmodel_weight_file_path)
Expand Down