code: def __init__(
      self,
      vocab_size=40478,
      n_positions=512,
      n_embd=768,
      n_layer=12,
      n_head=12,
      afn="gelu",
      resid_pdrop=0.1,
      embd_pdrop=0.1,
      attn_pdrop=0.1,
      layer_norm_epsilon=1e-5,
      initializer_range=0.02,
      predict_special_tokens=True,
      summary_type="cls_index",
      summary_use_proj=True,
      summary_activation=None,
      summary_proj_to_labels=True,
      summary_first_dropout=0.1,
      **kwargs,
  ):
      self.vocab_size = vocab_size
      self.n_positions = n_positions
      self.n_embd = n_embd
      self.n_layer = n_layer
      self.n_head = n_head
      self.afn = afn
      self.resid_pdrop = resid_pdrop
      self.embd_pdrop = embd_pdrop
      self.attn_pdrop = attn_pdrop
      self.layer_norm_epsilon = layer_norm_epsilon
      self.initializer_range = initializer_range
      self.predict_special_tokens = predict_special_tokens
      self.summary_type = summary_type
      self.summary_use_proj = summary_use_proj
      self.summary_activation = summary_activation
      self.summary_first_dropout = summary_first_dropout
      self.summary_proj_to_labels = summary_proj_to_labels
      super().__init__(**kwargs)
  
imports: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new OpenAIGPTConfig object from inherited base classes: PretrainedConfig with example: obj = OpenAIGPTConfig(vocab_size, n_positions, n_embd, n_layer, n_head, afn, resid_pdrop, embd_pdrop, attn_pdrop, layer_norm_epsilon, initializer_range, predict_special_tokens, summary_type, summary_use_proj, summary_activation, summary_proj_to_labels, summary_first_dropout)