def test_stamp_computed_value_into_graph_with_undefined_tensor_dims(self):
v_type = computation_types.TensorType(tf.int32, [None])
v_value = np.array([1, 2, 3], dtype=np.int32)
v = reference_executor.ComputedValue(v_value, v_type)
with tf.Graph().as_default() as graph:
stamped_v = reference_executor.stamp_computed_value_into_graph(v, graph)
with tf.Session(graph=graph) as sess:
v_result = graph_utils.fetch_value_in_session(sess, stamped_v)
self.assertTrue(np.array_equal(v_result, np.array([1, 2, 3])))
def test_stamp_computed_value_into_graph_with_tuples_of_tensors(self):
v_val = anonymous_tuple.AnonymousTuple([('x', 10),
('y',
anonymous_tuple.AnonymousTuple(
[('z', 0.6)]))])
v_type = [('x', tf.int32), ('y', [('z', tf.float32)])]
v = reference_executor.ComputedValue(
reference_executor.to_representation_for_type(v_val, v_type), v_type)
with tf.Graph().as_default() as graph:
stamped_v = reference_executor.stamp_computed_value_into_graph(v, graph)
with tf.Session(graph=graph) as sess:
v_val = graph_utils.fetch_value_in_session(sess, stamped_v)
self.assertEqual(str(v_val), '<x=10,y=<z=0.6>>')
