class_docstr: Univariate BERT-based scorer.
class_docstr_tok: ["Univariate","BERT-based","scorer","."]
code: def __init__(
      self,
      encoder: tf.keras.Model,
      bert_output_dropout: float,
      name: str = "tfrbert",
      **kwargs,
  ):
      self.encoder = encoder
      self._dropout_layer = tf.keras.layers.Dropout(
          rate=bert_output_dropout
      )
      self._score_layer = tf.keras.layers.Dense(units=1, name="score")
  
imports: import dataclasses
  import os
  import time
  from typing import Dict, Mapping, Optional, Tuple
  from absl import logging
  import numpy
  import tensorflow
  from official.core import task_factory
  from official.modeling.hyperparams import base_config
  from official.nlp.configs import encoders
  from tensorflow_ranking.extension import task
  from tensorflow_ranking.python.keras import metrics
  from tensorflow_ranking.python.keras import model
label_desc: Use image node_id 1 to create a new TFRBertScorer object from inherited base classes: tfr_model with example: obj = TFRBertScorer(encoder, bert_output_dropout, name)