code: def __init__(
      self,
      max_prediction_len=20,
      num_layers_encoder=1,
      num_layers_decoder=1,
      num_heads=2,
      feed_forward_dim=512,
      dropout_rate=0,
      embedding_size_encoder=768,
      embedding_size_decoder=64,
      bert_embedding_encoder=None,
      bert_embedding_decoder=None,
      embedding_encoder_trainable=True,
      embedding_decoder_trainable=True,
      max_sequence_len=10000,
  ):
      super().__init__()
      self.max_prediction_len = max_prediction_len
      self.embedding_size_encoder = embedding_size_encoder
      self.embedding_size_decoder = embedding_size_decoder
      self.num_layers_encoder = num_layers_encoder
      self.num_layers_decoder = num_layers_decoder
      self.num_heads = num_heads
      self.dropout_rate = dropout_rate
      self.feed_forward_dim = feed_forward_dim
      self.embedding_encoder_trainable = embedding_encoder_trainable
      self.embedding_decoder_trainable = embedding_decoder_trainable
      self.bert_embedding_encoder = bert_embedding_encoder
      self.bert_embedding_decoder = bert_embedding_decoder
      self.optimizer_encoder = BertSummarizer.new_optimizer_encoder()
      self.optimizer_decoder = BertSummarizer.new_optimizer_decoder()
      self.transformer = None
      self.embedding_shape_in = None
      self.embedding_shape_out = None
      self.max_sequence_len = max_sequence_len
      self.logger = get_logger(__name__)
  
imports: import os
  import pickle
  from typing import Callable
  from typing import Dict, Union
  import numpy
  import tensorflow
  from headliner.model.bert_model import Transformer, create_masks
  from headliner.model.summarizer import Summarizer
  from headliner.preprocessing.bert_vectorizer import BertVectorizer
  from headliner.preprocessing.preprocessor import Preprocessor
  from headliner.utils.logger import get_logger
label_desc: Use image node_id 1 to create a new BertSummarizer object from inherited base classes: Summarizer with example: obj = BertSummarizer(max_prediction_len, num_layers_encoder, num_layers_decoder, num_heads, feed_forward_dim, dropout_rate, embedding_size_encoder, embedding_size_decoder, bert_embedding_encoder, bert_embedding_decoder, embedding_encoder_trainable, embedding_decoder_trainable, max_sequence_len)