text: from typing import Dict
  
  import tensorflow as tf
  from tfaip.base.data.data import DataBase
  
  from tfaipscenarios.text.finetuningbert.datapipeline.tokenizerprocessor import TokenizerProcessorParams
  from tfaipscenarios.text.finetuningbert.params import Keys, FTBertDataParams
  
  
  class FTBertData(DataBase[FTBertDataParams]):
      @classmethod
      def default_params(cls) -> FTBertDataParams:
          p = super().default_params()
          p.pre_proc.processors = [
              TokenizerProcessorParams()
          ]
          p.post_proc.run_parallel = False
          p.post_proc.processors = [
          ]
          return p
  
      def _input_layer_specs(self) -> Dict[str, tf.TensorSpec]:
          return {
              Keys.InputWordIds: tf.TensorSpec([None], tf.int32),
              Keys.InputTypeIds: tf.TensorSpec([None], tf.int32),
              Keys.InputMask: tf.TensorSpec([None], tf.int32),
          }
  
      def _target_layer_specs(self) -> Dict[str, tf.TensorSpec]:
          return {
              Keys.Target: tf.TensorSpec([1], tf.int32),
          }
  