code: def __init__(self, config, layer_id=0):
      super().__init__()
      self.layer_id = layer_id
      self.attention_layers = config.attention_layers
      self.attention_type = self.attention_layers[layer_id]
  
      if self.attention_type in ["global", "local"]:
          self.attention = GPTNeoSelfAttention(
              config, self.attention_type
          )
      else:
          raise NotImplementedError(
              "Only attn layer types 'global' and 'local' exist, but got `config.attention_layers`: "
              f"{config.attention_layers}. Select attn layer types from ['global', 'local'] only."
          )
  
imports: import os
  from typing import Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ...activations import ACT2FN
  from ...modeling_outputs import BaseModelOutputWithPast, BaseModelOutputWithPastAndCrossAttentions, CausalLMOutputWithCrossAttentions, CausalLMOutputWithPast, SequenceClassifierOutputWithPast
  from ...modeling_utils import PreTrainedModel
  from ...utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging
  from .configuration_gpt_neo import GPTNeoConfig
label_desc: Use image node_id 1 to create a new GPTNeoAttention object from inherited base classes: nn with example: obj = GPTNeoAttention(config, layer_id)