class_docstr: bilstmcrf class for sequence labeling.
code: def __init__(self, config, **kwargs):
      super().__init__(config, **kwargs)
  
      logging.info("Initialize BilstmModel...")
  
      self.vocab_size = config["data"]["vocab_size"]
      self.num_classes = config["data"]["task"]["classes"][
          "num_classes"
      ]
      self.seq_num_classes = self.num_classes
  
      model_config = config["model"]["net"]["structure"]
      self.dropout_rate = model_config["dropout_rate"]
      self.embedding_size = model_config["embedding_size"]
      self.num_layers = model_config["num_layers"]
      self.l2_reg_lambda = model_config["l2_reg_lambda"]
      self.batch_size = model_config["batch_size"]
      self.max_len = model_config["max_len"]
      self.num_units = model_config["num_units"]
      self.fc_dim = model_config[
          "fc_dim"
      ]  # output fully-connected layer size
  
      self.embed = tf.keras.layers.Embedding(
          input_dim=self.vocab_size,
          output_dim=self.embedding_size,
          mask_zero=True,
          input_length=self.max_len,
          embeddings_initializer=self.embed_initializer,
          trainable=True,
      )
  
      self.embed_dropout = tf.keras.layers.Dropout(self.dropout_rate)
      self.bilstm = tf.keras.layers.Bidirectional(
          tf.keras.layers.LSTM(
              units=self.num_units,
              return_sequences=True,
              recurrent_dropout=0.1,
          ),
          merge_mode="concat",
          name="BiLSTM",
      )
      self.dropout = tf.keras.layers.Dropout(self.dropout_rate)
      self.dense = tf.keras.layers.Dense(
          self.num_classes, name="fc_layer"
      )
  
      self.transitions = self.add_weight(
          name="transitions",
          shape=(self.seq_num_classes, self.seq_num_classes),
      )
  
      logging.info("Initialize BilstmCrfModel done.")
  
file_path: delta/delta/models/text_seq_label_model.py
imports: import pickle
  import delta.compat
  from absl import logging
  from delta.models.text_cls_model import TextClassModel
  from delta.utils.register import registers
label_desc: Use image node_id 1 to create a new BilstmCrfModel object from inherited base classes: SeqclassModel with example: obj = BilstmCrfModel(config)