code: def forward(
      self,
      hidden_states,
      attention_mask=None,
      head_mask=None,
      use_cache=False,
      layer_past=None,
      output_attentions=False,
  ):
      residual = hidden_states
      ln_out = self.input_layernorm(hidden_states)
      attention_layer_outputs, attn_bias = self.attention(
          ln_out,
          attention_mask=attention_mask,
          layer_past=layer_past,
          head_mask=head_mask,
          use_cache=use_cache,
          output_attentions=output_attentions,
      )
      attn_output = attention_layer_outputs[
          0
      ]  # output_attn: a, present, (attentions)
      outputs = attention_layer_outputs[1:]
  
      # attn_output = (atten_output + bias) + residual
      attn_output = bias_dropout_add(
          attn_output,
          bias=attn_bias.expand_as(residual)
          if attn_bias is not None
          else attn_bias,
          residual=residual,
          prob=self.hidden_dropout,
          training=self.training,
      )
      mlp_output = self.mlp(self.post_attention_layernorm(attn_output))
  
      # attn_output = (mlp_output + mlp_bias) + atten_output
      attn_output = bias_dropout_add(
          mlp_output,
          bias=None,
          residual=attn_output,
          prob=self.hidden_dropout,
          training=self.training,
      )
  
      if use_cache:
          outputs = (attn_output,) + outputs
      else:
          outputs = (attn_output,) + outputs[1:]
  
      return outputs
  
imports: from typing import Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import Tensor, nn
  from torch.nn import CrossEntropyLoss
  from ...activations import ACT2FN
  from ...file_utils import add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings
  from ...modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
  from ...modeling_utils import PreTrainedModel
  from ...utils import logging
  from .configuration_gpt_neox_japanese import GPTNeoXJapaneseConfig
label_desc: Use image node_id 2 for calling the GPTNeoXJapaneseLayer obj's underlying member method code with example usage: obj.forward(hidden_states, attention_mask, head_mask, use_cache, layer_past, output_attentions) and returns: outputs