code: def _update_amsgrad(
      p, g, m, v, v_hat, t, alpha, beta1, beta2, eps, bias_correction
  ):
      if bias_correction:
          alpha_t = (
              alpha * np.sqrt(1.0 - beta2**t) / (1.0 - beta1**t)
          )
      else:
          alpha_t = alpha
      m[...] = beta1 * m + (1 - beta1) * g
      v[...] = beta2 * v + (1 - beta2) * g * g
      v_hat[...] = np.maximum(v_hat, v)
      p[...] = p - alpha_t * m / (np.sqrt(v_hat) + eps)
  
file_path: nnabla/python/test/solver/test_amsgrad.py
imports: import pytest
  import nnabla.solvers
  import numpy
  from solver_test_utils import solver_tester, RefSolver
  from nbla_test_utils import list_context
label_desc: Use image node_id 1 for calling a global function with example usage: _update_amsgrad(p, g, m, v, v_hat, t, alpha, beta1, beta2, eps, bias_correction) without return types