code: def _compute_error(grad):
      if isinstance(grad, tuple):
          grad = [grad]
      error = 0
      for j_t, j_n in grad:
          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.framework import constant_op
  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
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 9 for calling a global function with example usage: _compute_error(grad) and returns: error