class_docstr: Test that CropAndResizeBackprop{Image|Boxes} operates reproducibly.
  
  Inheriting from test_base.CropAndResizeOpTestBase ensures that regular op
  functionality is correct when the deterministic code-path is selected.
code: def _genParams(self, dtype=dtypes.float32):
      batch_size = 16
      input_height = 64
      input_width = 64
      depth = 1
      input_shape = (batch_size, input_height, input_width, depth)
      np.random.seed(456)
      image = self._randomFloats(
          input_shape, low=-1.0, high=1.0, dtype=dtype
      )
      box_count = 4 * batch_size
      boxes = self._randomFloats(
          (box_count, 4), low=0.0, high=1.01, dtype=dtypes.float32
      )
      box_indices = self._randomInts(
          (box_count,), low=0, high=batch_size
      )
      crop_size = [input_height * 2, input_width * 2]
      output_shape = (box_count, *crop_size, depth)
      # The output of this op is always float32, regardless of image data type
      injected_gradients = self._randomFloats(
          output_shape, low=-0.001, high=0.001, dtype=dtypes.float32
      )
      return image, boxes, box_indices, crop_size, injected_gradients
  
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 3 for calling the CropAndResizeOpDeterministicTest obj's underlying member method code with example usage: obj._genParams(dtype) and returns: image,  boxes,  box_indices,  crop_size,  injected_gradients