code: def new_optimizer_encoder(
      learning_rate_start=5e-4, warmup_steps=20000
  ) -> tf.keras.optimizers.Optimizer:
      learning_rate = CustomSchedule(
          warmup_steps=warmup_steps,
          learning_rate_start=learning_rate_start,
      )
      optimizer = tf.keras.optimizers.Adam(
          learning_rate,
          beta_1=0.9,
          beta_2=0.999,
      )
      return optimizer
  
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 10 for calling the BertSummarizer obj's underlying member method code with example usage: obj.new_optimizer_encoder(learning_rate_start, warmup_steps) and returns: optimizer