code: def ref_grad_clip_by_norm(x, dy, clip_norm, axes, **kw):
      dx = np.copy(dy)
      dx = (
          clip_norm
          * dy
          / np.broadcast_to(
              np.sqrt(np.sum(dy**2, axis=axes, keepdims=True)),
              dy.shape,
          )
      )
      return dx.flatten()
  
imports: import pytest
  import numpy
  import nnabla.functions
  from nbla_test_utils import list_context
label_desc: Use image node_id 2 for calling a global function with example usage: ref_grad_clip_by_norm(x, dy, clip_norm, axes) and returns: dx