code: def max_error(grad1, grad2):
      """Computes maximum elementwise gap.
  
      Computes the maximum elementwise gap between two lists of tensors of the same
      shape.
  
      Args:
        grad1: a lists of tensors.
        grad2: a lists of tensors with the same shape as grad1.
  
      Returns:
        The maximum elementwise gap between the two.
      """
      error = 0
      for j_t, j_n in zip(grad1, grad2):
          if j_t.size or j_n.size:  # Handle zero size tensors correctly
              error = np.maximum(error, np.fabs(j_t - j_n).max())
      return error
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import indexed_slices
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 10 for calling a global function with example usage: max_error(grad1, grad2) and returns: error