code: def _testDynamicShape(self, input_shape, block_shape, paddings):
      block_shape = np.array(block_shape)
      paddings = np.array(paddings)
  
      # Try with sizes unknown at graph construction time.
      input_placeholder = array_ops.placeholder(dtypes.float32)
      block_shape_placeholder = array_ops.placeholder(
          dtypes.int32, shape=block_shape.shape
      )
      paddings_placeholder = array_ops.placeholder(dtypes.int32)
      t = array_ops.batch_to_space_nd(
          input_placeholder,
          block_shape_placeholder,
          paddings_placeholder,
      )
  
      with self.assertRaises(ValueError):
          _ = t.eval(
              {
                  input_placeholder: np.zeros(input_shape, np.float32),
                  block_shape_placeholder: block_shape,
                  paddings_placeholder: paddings,
              }
          )
  
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 BatchToSpaceNDErrorHandlingTest obj's underlying member method code with example usage: obj._testDynamicShape(input_shape, block_shape, paddings) without return types