message: Explicitly use int64 data type for row splits when creating RaggedTensorValues.
diff: @@ -41,11 +41,12 @@ class CompositeTensorTest(test_util.TensorFlowTestCase):
  sparse_tensor.SparseTensorValue([[0, 0]], [1], [1, 1])))
  self.assertTrue(
  composite_tensor_utils.is_composite_or_composite_value(
  - ragged_tensor.RaggedTensor.from_row_splits([0, 1, 2], [0, 1, 3])))
  + ragged_tensor.RaggedTensor.from_row_splits(
  + np.array([0, 1, 2]), np.array([0, 1, 3], dtype=np.int64))))
  self.assertTrue(
  composite_tensor_utils.is_composite_or_composite_value(
  ragged_tensor_value.RaggedTensorValue(
  - np.array([0, 1, 2]), np.array([0, 1, 3]))))
  + np.array([0, 1, 2]), np.array([0, 1, 3], dtype=np.int64))))
  # Test that numpy arrays and tensors return false.
  self.assertFalse(
  @@ -76,9 +77,9 @@ class CompositeTensorTest(test_util.TensorFlowTestCase):
  def test_ragged_concatenation(self):
  tensor_1 = ragged_tensor.RaggedTensor.from_row_splits(
  - np.array([0, 1, 2]), np.array([0, 1, 3]))
  + np.array([0, 1, 2]), np.array([0, 1, 3], dtype=np.int64))
  tensor_2 = ragged_tensor.RaggedTensor.from_row_splits(
  - np.array([3, 4, 5]), np.array([0, 2, 3]))
  + np.array([3, 4, 5]), np.array([0, 2, 3], dtype=np.int64))
  concatenated_tensor = composite_tensor_utils.append_composite_tensor(
  tensor_1, tensor_2)
  evaluated_tensor = self.evaluate(concatenated_tensor)
  @@ -88,9 +89,9 @@ class CompositeTensorTest(test_util.TensorFlowTestCase):
  def test_ragged_value_concatenation(self):
  tensor_1 = ragged_tensor_value.RaggedTensorValue(
  - np.array([0, 1, 2]), np.array([0, 1, 3]))
  + np.array([0, 1, 2]), np.array([0, 1, 3], dtype=np.int64))
  tensor_2 = ragged_tensor_value.RaggedTensorValue(
  - np.array([3, 4, 5]), np.array([0, 2, 3]))
  + np.array([3, 4, 5]), np.array([0, 2, 3], dtype=np.int64))
  concatenated_tensor = composite_tensor_utils.append_composite_tensor(
  tensor_1, tensor_2)
  