code: def _compare(self, b, h, w, d, block_size, crop_beg, crop_end):
      block_size_sq = block_size * block_size
      x = (
          np.random.normal(0, 1, b * h * w * d * block_size_sq)
          .astype(np.float32)
          .reshape([b * block_size * block_size, h, w, d])
      )
      crops = np.array(
          [[crop_beg, crop_end], [crop_beg, crop_end]], dtype=np.int32
      )
  
      self._checkGrad(x, crops, block_size)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  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 gen_array_ops
  from tensorflow.python.ops import gradient_checker
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the BatchToSpaceGradientTest obj's underlying member method code with example usage: obj._compare(b, h, w, d, block_size, crop_beg, crop_end) without return types