code: def sgdw_update_numpy(
      param, grad_t, slot_vars, learning_rate, momentum, weight_decay
  ):
      """Numpy update function for SGDW."""
      m = slot_vars.get("m", 0)
      lr, momentum, wd = (
          v() if callable(v) else v
          for v in (learning_rate, momentum, weight_decay)
      )
      slot_vars["m"] = momentum * m + grad_t
      param_t = param * (1 - wd) - lr * slot_vars["m"]
      return param_t, slot_vars
  
imports: import importlib
  import numpy
  import pytest
  import tensorflow
  from tensorflow_addons.utils import test_utils
  from tensorflow_addons.optimizers import weight_decay_optimizers
label_desc: Use image node_id 4 for calling a global function with example usage: sgdw_update_numpy(param, grad_t, slot_vars, learning_rate, momentum, weight_decay) and returns: param_t,  slot_vars