class_docstr: Test that ResizeBilinearGrad operates reproducibly.
  
  Inheriting from test_base.ResizeBilinearOpTestBase ensures that regular op
  functionality is correct when the deterministic code-path is selected.
code: def _randomNDArray(self, shape):
      return 2 * np.random.random_sample(shape) - 1
  
imports: import numpy
  from absl.testing import parameterized
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors_impl
  from tensorflow.python.framework import random_seed
  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 image_grad_test_base
  from tensorflow.python.ops import image_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the ResizeBilinearOpDeterministicTest obj's underlying member method code with example usage: obj._randomNDArray(shape) and returns: unknown