def test_raises_type_error_with_bad_type(self):
value = 10.0
type_signature = tf.int32
with self.assertRaises(TypeError):
tensorflow_computation_factory.create_constant(
value, type_signature)
def test_raises_type_error_with_non_scalar_value(self):
value = np.zeros([1])
type_signature = tf.int32
with self.assertRaises(TypeError):
tensorflow_computation_factory.create_constant(
value, type_signature)
def create_dummy_computation_tensorflow_constant():
"""Returns a tensorflow computation and type `( -> float32)`."""
value = 10.0
tensor_type = computation_types.TensorType(tf.float32)
value, type_signature = tensorflow_computation_factory.create_constant(
value, tensor_type)
return value, type_signature
def create_dummy_computation_tensorflow_constant():
"""Returns a tensorflow computation and type `( -> float32)`."""
value = 10.0
type_spec = tf.float32
value = tensorflow_computation_factory.create_constant(value, type_spec)
type_signature = computation_types.FunctionType(None, type_spec)
return value, type_signature
def test_to_value_for_computations(self):
tensor_type = computation_types.TensorType(tf.int32)
computation_proto, _ = tensorflow_computation_factory.create_constant(
10, tensor_type)
computation = computation_impl.ConcreteComputation(
computation_proto, context_stack_impl.context_stack)
value = value_impl.to_value(computation, None)
self.assertIsInstance(value, value_impl.Value)
self.assertEqual(value.type_signature.compact_representation(),
'( -> int32)')
def test_intrinsic_construction_raises_outside_symbol_binding_context(
self):
type_signature = computation_types.TensorType(tf.int32)
computation_proto, _ = tensorflow_computation_factory.create_constant(
2, type_signature)
return_2 = computation_impl.ConcreteComputation(
computation_proto, context_stack_impl.context_stack)
with context_stack_impl.context_stack.install(
runtime_error_context.RuntimeErrorContext()):
with self.assertRaises(context_base.ContextError):
intrinsics.federated_eval(return_2, placements.SERVER)
def test_returns_computation(self, value, type_signature, expected_result):
proto, _ = tensorflow_computation_factory.create_constant(
value, type_signature)
self.assertIsInstance(proto, pb.Computation)
actual_type = type_serialization.deserialize_type(proto.type)
expected_type = computation_types.FunctionType(None, type_signature)
expected_type.check_assignable_from(actual_type)
actual_result = test_utils.run_tensorflow(proto)
if isinstance(expected_result, list):
self.assertCountEqual(actual_result, expected_result)
else:
self.assertEqual(actual_result, expected_result)
def test_returns_computation_with_tuple_unnamed(self):
value = 10
type_signature = computation_types.NamedTupleType([tf.int32] * 3)
proto = tensorflow_computation_factory.create_constant(
value, type_signature)
self.assertIsInstance(proto, pb.Computation)
actual_type = type_serialization.deserialize_type(proto.type)
expected_type = computation_types.FunctionType(None, type_signature)
self.assertEqual(actual_type, expected_type)
expected_value = [value] * 3
actual_value = test_utils.run_tensorflow(proto, expected_value)
self.assertCountEqual(actual_value, expected_value)
def test_returns_computation_with_tensor_float(self):
value = 10.0
type_signature = computation_types.TensorType(tf.float32, [3])
proto = tensorflow_computation_factory.create_constant(
value, type_signature)
self.assertIsInstance(proto, pb.Computation)
actual_type = type_serialization.deserialize_type(proto.type)
expected_type = computation_types.FunctionType(None, type_signature)
self.assertEqual(actual_type, expected_type)
expected_value = [value] * 3
actual_value = test_utils.run_tensorflow(proto, expected_value)
self.assertCountEqual(actual_value, expected_value)
def test_invoke_returns_value_with_correct_type(self):
tensor_type = computation_types.TensorType(tf.int32)
computation_proto, _ = tensorflow_computation_factory.create_constant(
10, tensor_type)
computation = computation_impl.ConcreteComputation(
computation_proto, context_stack_impl.context_stack)
context = federated_computation_context.FederatedComputationContext(
context_stack_impl.context_stack)
with context_stack_impl.context_stack.install(context):
result = context.invoke(computation, None)
self.assertIsInstance(result, value_impl.Value)
self.assertEqual(str(result.type_signature), 'int32')
def test_federated_select_server_val_must_be_server_placed(
self, federated_select):
client_keys, max_key, server_val, select_fn = (
self.basic_federated_select_args())
del server_val
bad_server_val_proto, _ = tensorflow_computation_factory.create_constant(
tf.constant(['first', 'second', 'third']),
computation_types.TensorType(dtype=tf.string, shape=[3]))
bad_server_val = computation_impl.ConcreteComputation(
bad_server_val_proto, context_stack_impl.context_stack)
bad_server_val = bad_server_val()
with self.assertRaises(TypeError):
federated_select(client_keys, max_key, bad_server_val, select_fn)
async def embed_tf_scalar_constant(executor, type_spec, value):
"""Embeds a constant `val` of TFF type `type_spec` in `executor`.
Args:
executor: An instance of `tff.framework.Executor`.
type_spec: An instance of `tff.Type`.
value: A scalar value.
Returns:
An instance of `tff.framework.ExecutorValue` containing an embedded value.
"""
py_typecheck.check_type(executor, executor_base.Executor)
proto = tensorflow_computation_factory.create_constant(value, type_spec)
type_signature = type_serialization.deserialize_type(proto.type)
result = await executor.create_value(proto, type_signature)
return await executor.create_call(result)
async def embed_tf_constant(executor, type_spec, value):
"""Embeds a constant `val` of TFF type `type_spec` in `executor`.
Args:
executor: An instance of `tff.framework.Executor`.
type_spec: An instance of `tff.Type`.
value: A value, must be a tensor or nested structure of tensors with the
structure matching `type_spec`.
Returns:
An instance of `tff.framework.ExecutorValue` containing an embedded value.
"""
py_typecheck.check_type(executor, executor_base.Executor)
proto, type_signature = tensorflow_computation_factory.create_constant(
value, type_spec)
result = await executor.create_value(proto, type_signature)
return await executor.create_call(result)
def test_raises_type_error(self, value, type_signature):
with self.assertRaises(TypeError):
tensorflow_computation_factory.create_constant(
value, type_signature)
def create_dummy_computation_tensorflow_constant(value=10.0):
"""Returns a tensorflow computation and type `( -> T)`."""
type_spec = type_utils.infer_type(value)
value = tensorflow_computation_factory.create_constant(value, type_spec)
type_signature = computation_types.FunctionType(None, type_spec)
return value, type_signature
