code: def mlp(self, enable_training=False):
      intermediate_ff = self.client_module.ffn.lin1
  
      return (
          intermediate_ff.weight,
          intermediate_ff.bias,
          self.client_module.ffn.lin2.weight,
          self.client_module.ffn.lin2.bias,
      )
  
file_path: DeepSpeed/deepspeed/module_inject/containers/distil_bert.py
imports: from .base import *
  from deepspeed.model_implementations.transformers.ds_bert import DeepSpeedBERTInference
  import torch
  from torch.nn.parameter import Parameter
  from ..policy import TransformerPolicy
label_desc: Use image node_id 4 for calling the HFDistilBertLayerPolicy obj's underlying member method code with example usage: obj.mlp(enable_training) and returns: intermediate_ff,  intermediate_ff,  self,  self