class_docstr: bilstmcrf class for sequence labeling.
code: def call(self, inputs, training=None, mask=None):
      input_x = inputs["input_x"]
      # [batch_size, max_len, embed_len]
      out = self.embed(input_x)
      # [batch_size, features]
      if self.use_pretrained_model:
          logging.info(
              "use_pretrained_model: {}, {}".format(
                  self.pretrained_model_name, self.pretrained_model_mode
              )
          )
          if (
              self.pretrained_model_name == "bert"
              and self.pretrained_model_mode == "fine-tune"
          ):
              out = self.get_pre_train_graph(input_x)
          else:
              input_px = self.get_pre_train_graph(input_x)
              out = tf.concat([out, input_px], axis=-1)
              out = self.embed_dropout(out, training=training)
      out = self.bilstm(out)
      out = self.dropout(out, training=training)
      output = self.dense(out)
      return output
  
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 2 for calling the BilstmCrfModel obj's underlying member method code with example usage: obj.call(inputs, training, mask) and returns: output