code: def _einsum_grad(op, grad):
      equation = op.get_attr("equation")
      if isinstance(equation, bytes):
          equation = equation.decode()
  
      inputs, output = equation.split("->")
      left, right = inputs.split(",")
  
      return [
          gen_xla_ops.xla_einsum(
              grad,
              op.inputs[1],
              equation="{},{}->{}".format(output, right, left),
              name=None,
          ),
          gen_xla_ops.xla_einsum(
              grad,
              op.inputs[0],
              equation="{},{}->{}".format(output, left, right),
              name=None,
          ),
      ]
  
imports: import collections
  import functools
  import re
  import string
  import numpy
  import opt_einsum
  from tensorflow.compiler.tf2xla.ops import gen_xla_ops
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import gen_linalg_ops
  from tensorflow.python.ops import gen_special_math_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 19 for calling a global function with example usage: _einsum_grad(op, grad) and returns: list