class_docstr: python reference implemenation of sparse adam
code: def __init__(
      self,
      learning_rate=0.001,
      beta1=0.9,
      beta2=0.999,
      epsilon=1e-8,
      lazy_update=False,
      **kwargs,
  ):
      super(PySparseAdam, self).__init__(
          learning_rate=learning_rate, **kwargs
      )
      self.beta1 = beta1
      self.beta2 = beta2
      self.epsilon = epsilon
      self.lazy_update = lazy_update
  
imports: import itertools
  import numpy
  import itertools
  import mxnet
  import mxnet.lr_scheduler
  from mxnet import gluon
  import unittest
  import pytest
  import math
  from mxnet.test_utils import *
  from common import retry, xfail_when_nonstandard_decimal_separator
label_desc: Use image node_id 1 to create a new PySparseAdam object from inherited base classes: mx.optimizer with example: obj = PySparseAdam(learning_rate, beta1, beta2, epsilon, lazy_update)