code: def _SparseReorderGrad(
      op: ops.Operation, unused_output_indices_grad, output_values_grad
  ):
      """Gradients for the SparseReorder op.
  
      Args:
        op: the SparseReorder op
        unused_output_indices_grad: the incoming gradients of the output indices
        output_values_grad: the incoming gradients of the output values
  
      Returns:
        Gradient for each of the 3 input tensors:
          (input_indices, input_values, input_shape)
        The gradients for input_indices and input_shape is None.
      """
      input_indices = op.inputs[0]
      input_shape = op.inputs[2]
  
      num_entries = array_ops.shape(input_indices)[0]
      entry_indices = math_ops.range(num_entries)
      sp_unordered = sparse_tensor.SparseTensor(
          input_indices, entry_indices, input_shape
      )
      sp_ordered = sparse_ops.sparse_reorder(sp_unordered)
      inverted_permutation = array_ops.invert_permutation(
          sp_ordered.values
      )
  
      return (
          None,
          array_ops.gather(output_values_grad, inverted_permutation),
          None,
      )
  
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_sparse_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import sparse_ops
label_desc: Use image node_id 1 for calling a global function with example usage: _SparseReorderGrad(op, unused_output_indices_grad, output_values_grad) and returns: None,  array_ops,  None