code: def __init__(
      self,
      learning_rate=0.001,
      beta1=0.9,
      beta2=0.999,
      epsilon=1e-8,
      schedule_decay=0.004,
      **kwargs,
  ):
      super(ONadam, self).__init__(
          learning_rate=learning_rate, **kwargs
      )
      self.beta1 = beta1
      self.beta2 = beta2
      self.epsilon = epsilon
      self.schedule_decay = schedule_decay
      self.m_schedule = 1.0
  
file_path: insightface/alignment/heatmap/optimizer.py
imports: import mxnet
  import mxnet.optimizer
  from mxnet.ndarray import NDArray, zeros, clip, sqrt, cast, maximum, abs
label_desc: Use image node_id 1 to create a new ONadam object from inherited base classes: optimizer with example: obj = ONadam(learning_rate, beta1, beta2, epsilon, schedule_decay)