code: def _Normalize(x, ord, axis):
      if isinstance(axis, (list, tuple)):
          norm = np.linalg.norm(x, ord, tuple(axis))
          if axis[0] < axis[1]:
              # This prevents axis to be inserted in-between
              # e.g. when (-2, -1)
              for d in reversed(axis):
                  norm = np.expand_dims(norm, d)
          else:
              for d in axis:
                  norm = np.expand_dims(norm, d)
          return x / norm
      elif axis is None:
          # Tensorflow handles None differently
          norm = np.linalg.norm(x.flatten(), ord, axis)
          return x / norm
      else:
          norm = np.apply_along_axis(np.linalg.norm, axis, x, ord)
          return x / np.expand_dims(norm, axis)
  
file_path: tensorflow-upstream/tensorflow/python/kernel_tests/linalg/normalize_op_test.py
imports: import numpy
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import nn_impl
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling a global function with example usage: _Normalize(x, ord, axis) and returns: unknown, unknown, unknown