code: def __init__(self, config):
      super().__init__(config)
      self.config = config
  
      self.embed_in = nn.Embedding(
          config.vocab_size, config.hidden_size
      )
      self.layers = nn.ModuleList(
          [
              GPTNeoXJapaneseLayer(config=config, layer_number=i)
              for i in range(config.num_hidden_layers)
          ]
      )
      self.final_layer_norm = nn.LayerNorm(
          config.hidden_size, eps=config.layer_norm_eps
      )
  
      # Initialize weights and apply final processing
      self.post_init()
  
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 1 to create a new GPTNeoXJapaneseModel object from inherited base classes: GPTNeoXJapanesePreTrainedModel with example: obj = GPTNeoXJapaneseModel(config)