code: def get_beta_accumulators(opt, dtype):
      local_step = tf.cast(opt.iterations + 1, dtype)
      beta_1_t = tf.cast(opt._get_hyper("beta_1"), dtype)
      beta_1_power = tf.math.pow(beta_1_t, local_step)
      beta_2_t = tf.cast(opt._get_hyper("beta_2"), dtype)
      beta_2_power = tf.math.pow(beta_2_t, local_step)
      return (beta_1_power, beta_2_power)
  
imports: import numpy
  from numpy import linalg
  import pytest
  import tensorflow
  from tensorflow_addons.optimizers import lamb
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 3 for calling a global function with example usage: get_beta_accumulators(opt, dtype) and returns: beta_1_power,  beta_2_power