code: def __init__(
      self,
      vocab_size=30522,
      hidden_size=768,
      retriever_proj_size=128,
      num_hidden_layers=12,
      num_attention_heads=12,
      num_candidates=8,
      intermediate_size=3072,
      hidden_act="gelu_new",
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      max_position_embeddings=512,
      type_vocab_size=2,
      initializer_range=0.02,
      layer_norm_eps=1e-12,
      span_hidden_size=256,
      max_span_width=10,
      reader_layer_norm_eps=1e-3,
      reader_beam_size=5,
      reader_seq_len=320,  # 288 + 32
      num_block_records=13353718,
      searcher_beam_size=5000,
      searcher_seq_len=64,
      pad_token_id=1,
      bos_token_id=0,
      eos_token_id=2,
      **kwargs,
  ):
      super().__init__(
          pad_token_id=pad_token_id,
          bos_token_id=bos_token_id,
          eos_token_id=eos_token_id,
          **kwargs,
      )
  
      # Common config
      self.vocab_size = vocab_size
      self.max_position_embeddings = max_position_embeddings
      self.hidden_size = hidden_size
      self.retriever_proj_size = retriever_proj_size
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.num_candidates = num_candidates
      self.intermediate_size = intermediate_size
      self.hidden_act = hidden_act
      self.hidden_dropout_prob = hidden_dropout_prob
      self.attention_probs_dropout_prob = attention_probs_dropout_prob
      self.initializer_range = initializer_range
      self.type_vocab_size = type_vocab_size
      self.layer_norm_eps = layer_norm_eps
  
      # Reader config
      self.span_hidden_size = span_hidden_size
      self.max_span_width = max_span_width
      self.reader_layer_norm_eps = reader_layer_norm_eps
      self.reader_beam_size = reader_beam_size
      self.reader_seq_len = reader_seq_len
  
      # Retrieval config
      self.num_block_records = num_block_records
      self.searcher_beam_size = searcher_beam_size
      self.searcher_seq_len = searcher_seq_len
  
imports: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
label_desc: Use image node_id 1 to create a new RealmConfig object from inherited base classes: PretrainedConfig with example: obj = RealmConfig(vocab_size, hidden_size, retriever_proj_size, num_hidden_layers, num_attention_heads, num_candidates, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, max_position_embeddings, type_vocab_size, initializer_range, layer_norm_eps, span_hidden_size, max_span_width, reader_layer_norm_eps, reader_beam_size, reader_seq_len, num_block_records, searcher_beam_size, searcher_seq_len, pad_token_id, bos_token_id, eos_token_id)