code: def diet_adam_optimizer_params():
      """Default hyperparameters for a DietAdamOptimizer.
  
      Returns:
        a hyperparameters object.
      """
      return hparam.HParams(
          quantize=True,  # use 16-bit fixed-point
          quantization_scale=10.0 / tf.int16.max,
          optimizer="DietAdam",
          learning_rate=1.0,
          learning_rate_warmup_steps=2000,
          learning_rate_decay_scheme="noam",  # "noam" or "none"
          epsilon=1e-10,
          beta1=0.0,  # we can save memory if beta1=0
          beta2=0.98,
          factored_second_moment_accumulator=True,  # this saves memory
      )
  
imports: from collections import defaultdict
  import copy
  import math
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import hparam
  import tensorflow.compat.v1
label_desc: Use image node_id 1 for calling a global function with example usage: diet_adam_optimizer_params() and returns: hparam