code: def test_ema_no_debias(self):
      orig_value_expect = np.array([100.0, -1.0])
      for m in [i / 10.0 for i in range(1, 10)]:
          x = objax.ModuleList(
              [
                  objax.TrainVar(jn.array(orig_value_expect)),
                  objax.TrainVar(jn.array(orig_value_expect[::-1])),
              ]
          )
          ema = objax.optimizer.ExponentialMovingAverage(
              x.vars(), momentum=m, debias=False
          )
          ema()
          ema_value_expect = (1 - m) * orig_value_expect
  
          def get_tensors():
              return x.vars().tensors()
  
          get_tensors_ema = ema.replace_vars(get_tensors)
          ema_value = get_tensors_ema()
          orig_value = get_tensors()
  
          np.testing.assert_allclose(
              ema_value[0], ema_value_expect, rtol=1e-6
          )
          np.testing.assert_allclose(
              ema_value[1], ema_value_expect[::-1], rtol=1e-6
          )
          np.testing.assert_allclose(
              orig_value[0], orig_value_expect, rtol=1e-6
          )
          np.testing.assert_allclose(
              orig_value[1], orig_value_expect[::-1], rtol=1e-6
          )
  
imports: import math
  import unittest
  import jax.numpy
  import numpy
  import objax
  from objax.variable import TrainVar, VarCollection
label_desc: Use image node_id 1 for calling the TestEma obj's underlying member method code with example usage: obj.test_ema_no_debias() and returns: x