code: def _run1(  # type: ignore
      self,
      r,
      t,
      x,
      g,
      v,
      h,
      alpha=None,
      beta=None,
      epsilon=None,
      norm_coefficient=None,
      norm_coefficient_post=None,
  ):
      x_new, v_new, h_new = _apply_adam(
          r,
          t,
          x,
          g,
          v,
          h,
          norm_coefficient,
          norm_coefficient_post,
          alpha,
          beta,
          epsilon,
      )
      return x_new, v_new, h_new
  
imports: import numpy
  from onnx.reference.ops.aionnx_preview_training._op_run_training import OpRunTraining
label_desc: Use image node_id 2 for calling the Adam obj's underlying member method code with example usage: obj._run1(r, t, x, g, v, h, alpha, beta, epsilon, norm_coefficient, norm_coefficient_post) and returns: x_new,  v_new,  h_new