def test_returns_value_with_federated_type_at_clients(self):
value = [
eager_tf_executor.EagerValue(10.0, None, tf.float32),
eager_tf_executor.EagerValue(11.0, None, tf.float32),
eager_tf_executor.EagerValue(12.0, None, tf.float32),
]
type_signature = type_factory.at_clients(tf.float32)
value = federating_executor.FederatingExecutorValue(value, type_signature)
result = self.run_sync(value.compute())
self.assertEqual(result, [10.0, 11.0, 12.0])
def test_returns_value_with_federated_type_at_clients(self):
tensor_type = computation_types.TensorType(tf.float32, shape=[])
value = [
eager_tf_executor.EagerValue(10.0, tensor_type),
eager_tf_executor.EagerValue(11.0, tensor_type),
eager_tf_executor.EagerValue(12.0, tensor_type),
]
type_signature = computation_types.at_clients(tf.float32)
value = federated_resolving_strategy.FederatedResolvingStrategyValue(
value, type_signature)
result = self.run_sync(value.compute())
self.assertEqual(result, [10.0, 11.0, 12.0])
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_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_eager_value_constructor_with_int_constant(self):
int_tensor_type = computation_types.TensorType(dtype=tf.int32, shape=[])
normalized_value = eager_tf_executor.to_representation_for_type(
10, {}, int_tensor_type)
v = eager_tf_executor.EagerValue(normalized_value, int_tensor_type)
self.assertEqual(str(v.type_signature), 'int32')
self.assertIsInstance(v.internal_representation, tf.Tensor)
self.assertEqual(v.internal_representation, 10)
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 = federated_resolving_strategy.FederatedResolvingStrategyValue(
value, type_signature)
result = self.run_sync(value.compute())
self.assertEqual(result, 10.0)
def test_returns_value_with_embedded_value(self):
tensor_type = computation_types.TensorType(tf.float32, shape=[])
value = eager_tf_executor.EagerValue(10.0, tensor_type)
type_signature = computation_types.TensorType(tf.float32)
value = federated_resolving_strategy.FederatedResolvingStrategyValue(
value, type_signature)
result = self.run_sync(value.compute())
self.assertEqual(result, 10.0)
def test_returns_value_with_federated_type_at_clients_all_equal(self):
value = [eager_tf_executor.EagerValue(10.0, None, tf.float32)]
type_signature = computation_types.at_clients(tf.float32,
all_equal=True)
value = federated_resolving_strategy.FederatedResolvingStrategyValue(
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)
def test_returns_value_with_structure_value(self):
element = eager_tf_executor.EagerValue(10.0, None, tf.float32)
element_type = computation_types.TensorType(tf.float32)
names = ['a', 'b', 'c']
value = structure.Struct((n, element) for n in names)
type_signature = computation_types.StructType(
(n, element_type) for n in names)
value = federated_resolving_strategy.FederatedResolvingStrategyValue(
value, type_signature)
result = self.run_sync(value.compute())
expected_result = structure.Struct((n, 10.0) for n in names)
self.assertEqual(result, expected_result)
def test_eager_value_constructor_with_int_constant(self):
v = eager_tf_executor.EagerValue(10, {}, tf.int32)
self.assertEqual(str(v.type_signature), 'int32')
self.assertIsInstance(v.internal_representation, tf.Tensor)
self.assertEqual(v.internal_representation, 10)
