code: def merge_scales(self):
      all_scales = []
      for dense_scale, qkv_scale, m4hh_scale, mh4h_scale in zip(
          self.dense_scales,
          self.qkv_scales,
          self.mlp4hh_scales,
          self.mlph4h_scales,
      ):
          all_scales.append(
              self.merge_layer_scales(
                  [qkv_scale, dense_scale, mh4h_scale, m4hh_scale]
              )
          )
      return torch.cat(all_scales)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/DeepSpeed/deepspeed/runtime/weight_quantizer.py
imports: import torch
  from ..module_inject.replace_policy import HFBertLayerPolicy, replace_policies
label_desc: Use image node_id 7 for calling the WeightQuantization obj's underlying member method code with example usage: obj.merge_scales() and returns: torch