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
  )
def diet_adam_optimizer_params ( ) : return hparam . HParams ( quantize = True , quantization_scale = 10.0 / tf . int16 . max , optimizer = "DietAdam" , learning_rate = 1.0 , learning_rate_warmup_steps = 2000 , learning_rate_decay_scheme = "noam" , epsilon = 1e-10 , beta1 = 0.0 , beta2 = 0.98 , factored_second_moment_accumulator = True , )
Default hyperparameters for a DietAdamOptimizer.

  Returns:
    a hyperparameters object.