code: def __init__(
      self,
      vocab_size=50265,
      d_model=1024,
      decoder_layers=12,
      decoder_attention_heads=16,
      decoder_ffn_dim=4096,
      activation_function="gelu",
      max_position_embeddings=512,
      dropout=0.1,
      attention_dropout=0.0,
      activation_dropout=0.0,
      decoder_start_token_id=2,
      classifier_dropout=0.0,
      init_std=0.02,
      decoder_layerdrop=0.0,
      use_cache=True,
      scale_embedding=False,
      use_learned_position_embeddings=True,
      layernorm_embedding=True,
      pad_token_id=1,
      bos_token_id=0,
      eos_token_id=2,
      **kwargs,
  ):
      self.vocab_size = vocab_size
      self.d_model = d_model
      self.decoder_layers = decoder_layers
      self.decoder_attention_heads = decoder_attention_heads
      self.decoder_ffn_dim = decoder_ffn_dim
      self.activation_function = activation_function
      self.max_position_embeddings = max_position_embeddings
      self.dropout = dropout
      self.attention_dropout = attention_dropout
      self.activation_dropout = activation_dropout
      self.classifier_dropout = classifier_dropout
      self.init_std = init_std
      self.decoder_layerdrop = decoder_layerdrop
      self.use_cache = use_cache
      self.scale_embedding = scale_embedding
      self.use_learned_position_embeddings = (
          use_learned_position_embeddings
      )
      self.layernorm_embedding = layernorm_embedding
  
      super().__init__(
          pad_token_id=pad_token_id,
          bos_token_id=bos_token_id,
          eos_token_id=eos_token_id,
          decoder_start_token_id=decoder_start_token_id,
          **kwargs,
      )
  
imports: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new TrOCRConfig object from inherited base classes: PretrainedConfig with example: obj = TrOCRConfig(vocab_size, d_model, decoder_layers, decoder_attention_heads, decoder_ffn_dim, activation_function, max_position_embeddings, dropout, attention_dropout, activation_dropout, decoder_start_token_id, classifier_dropout, init_std, decoder_layerdrop, use_cache, scale_embedding, use_learned_position_embeddings, layernorm_embedding, pad_token_id, bos_token_id, eos_token_id)