def test_raises_type_error_with_value_and_bad_type(self):
value = eager_tf_executor.EagerValue(10.0, None, tf.float32)
bad_type_signature = None
with self.assertRaises(TypeError):
federating_executor.FederatingExecutorValue(
value, bad_type_signature)
def test_raises_runtime_error_with_unsupported_value_or_type(self):
value = 10.0
type_signature = computation_types.TensorType(tf.float32)
value = federating_executor.FederatingExecutorValue(value, type_signature)
with self.assertRaises(RuntimeError):
self.run_sync(value.compute())
def test_raises_type_error_with_unembedded_federated_type(self):
value = [10.0, 11.0, 12.0]
type_signature = type_factory.at_clients(tf.float32)
value = federating_executor.FederatingExecutorValue(value, type_signature)
with self.assertRaises(TypeError):
self.run_sync(value.compute())
def test_returns_value_with_federated_type_at_server(self):
value = [eager_tf_executor.EagerValue(10.0, None, tf.float32)]
type_signature = type_factory.at_server(tf.float32)
value = federating_executor.FederatingExecutorValue(value, type_signature)
result = self.run_sync(value.compute())
self.assertEqual(result, 10.0)
def test_returns_value_with_embedded_value(self):
value = eager_tf_executor.EagerValue(10.0, None, tf.float32)
type_signature = computation_types.TensorType(tf.float32)
value = federating_executor.FederatingExecutorValue(value, type_signature)
result = self.run_sync(value.compute())
self.assertEqual(result, 10.0)
def test_returns_value_with_anonymous_tuple_value(self):
element = eager_tf_executor.EagerValue(10.0, None, tf.float32)
element_type = computation_types.TensorType(tf.float32)
names = ['a', 'b', 'c']
value = anonymous_tuple.AnonymousTuple((n, element) for n in names)
type_signature = computation_types.NamedTupleType(
(n, element_type) for n in names)
value = federating_executor.FederatingExecutorValue(value, type_signature)
result = self.run_sync(value.compute())
expected_result = anonymous_tuple.AnonymousTuple((n, 10.0) for n in names)
self.assertEqual(result, expected_result)
