code: def _testGradientVariableSize2DTape(self):
      # Regression test for bug in slice. A low-level bug in Eigen was causing
      # incorrect results for negative indices in multi-dimensional tensors.
      # See b/114318298.
      with backprop.GradientTape(persistent=True) as tape:
          x = constant_op.constant(
              [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 7]]
          )
          tape.watch(x)
          loss1 = math_ops.reduce_sum(x[:-1, :-1] * 1.0)
          loss2 = math_ops.reduce_sum(x[:-1][:, :-1])
  
      g1 = tape.gradient(loss1, x)
      g2 = tape.gradient(loss2, x)
      g1_val, g2_val = self.evaluate([g1, g2])
      self.assertAllEqual(g1_val, g2_val)
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 22 for calling the SliceTest obj's underlying member method code with example usage: obj._testGradientVariableSize2DTape() without return types