docstr: Test unflattening with int and float types.
code: def test_flatten_batch_to_2d_unflatten_types(self, dtype):
      """Test unflattening with int and float types."""
      data = np.ones(shape=(2, 2, 3, 2), dtype=dtype)
      sizes = ((3, 2), (1, 3))
      desired_unflattened = data
      desired_unflattened[0, 1, 2, :] = 0
      desired_unflattened[1, 0, 1:, :] = 0
  
      flat, unflatten = utils.flatten_batch_to_2d(data, sizes=sizes)
      data_unflattened = unflatten(flat)
  
      self.assertEqual(
          data.dtype, data_unflattened.dtype.as_numpy_dtype
      )
      self.assertAllEqual(data_unflattened, desired_unflattened)
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import linalg
  import tensorflow
  from tensorflow_graphics.geometry.convolution import utils
  from tensorflow_graphics.util import test_case
label_desc: Use image node_id 9 for calling the UtilsFlattenBatchTo2dTests obj's underlying member method code with example usage: obj.test_flatten_batch_to_2d_unflatten_types(dtype) without return types