def test_raises_type_error_with_unembedded_comp(self): executor = create_test_executor() comp, _ = executor_test_utils.create_dummy_computation_tensorflow_identity() arg, arg_type = executor_test_utils.create_dummy_value_unplaced() arg = self.run_sync(executor.create_value(arg, arg_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg))
class FederatingExecutorCreateCallTest(executor_test_utils.AsyncTestCase, parameterized.TestCase): # pyformat: disable @parameterized.named_parameters([ ('intrinsic_def_federated_aggregate', *executor_test_utils.create_dummy_intrinsic_def_federated_aggregate(), [ executor_test_utils.create_dummy_value_at_clients(), executor_test_utils.create_dummy_value_unplaced(), executor_test_utils.create_dummy_computation_tensorflow_add(), executor_test_utils.create_dummy_computation_tensorflow_add(), executor_test_utils.create_dummy_computation_tensorflow_identity( ) ], 43.0), ('intrinsic_def_federated_apply', *executor_test_utils.create_dummy_intrinsic_def_federated_apply(), [ executor_test_utils.create_dummy_computation_tensorflow_identity( ), executor_test_utils.create_dummy_value_at_server() ], 10.0), ('intrinsic_def_federated_broadcast', *executor_test_utils.create_dummy_intrinsic_def_federated_broadcast(), [executor_test_utils.create_dummy_value_at_server()], 10.0), ('intrinsic_def_federated_collect', *executor_test_utils.create_dummy_intrinsic_def_federated_collect(), [executor_test_utils.create_dummy_value_at_clients()], tf.data.Dataset.from_tensor_slices([10.0, 11.0, 12.0])), ('intrinsic_def_federated_eval_at_clients', *executor_test_utils. create_dummy_intrinsic_def_federated_eval_at_clients(), [executor_test_utils.create_dummy_computation_tensorflow_constant() ], [10.0] * 3), ('intrinsic_def_federated_eval_at_server', *executor_test_utils. create_dummy_intrinsic_def_federated_eval_at_server(), [executor_test_utils.create_dummy_computation_tensorflow_constant() ], 10.0), ('intrinsic_def_federated_map', *executor_test_utils.create_dummy_intrinsic_def_federated_map(), [ executor_test_utils.create_dummy_computation_tensorflow_identity( ), executor_test_utils.create_dummy_value_at_clients() ], [10.0, 11.0, 12.0]), ('intrinsic_def_federated_map_all_equal', *executor_test_utils. create_dummy_intrinsic_def_federated_map_all_equal(), [ executor_test_utils.create_dummy_computation_tensorflow_identity( ), executor_test_utils.create_dummy_value_at_clients_all_equal() ], 10.0), ('intrinsic_def_federated_mean', *executor_test_utils.create_dummy_intrinsic_def_federated_mean(), [executor_test_utils.create_dummy_value_at_clients()], 11.0), ('intrinsic_def_federated_sum', *executor_test_utils.create_dummy_intrinsic_def_federated_sum(), [executor_test_utils.create_dummy_value_at_clients()], 33.0), ('intrinsic_def_federated_reduce', *executor_test_utils.create_dummy_intrinsic_def_federated_reduce(), [ executor_test_utils.create_dummy_value_at_clients(), executor_test_utils.create_dummy_value_unplaced(), executor_test_utils.create_dummy_computation_tensorflow_add() ], 43.0), ('intrinsic_def_federated_value_at_clients', *executor_test_utils. create_dummy_intrinsic_def_federated_value_at_clients(), [executor_test_utils.create_dummy_value_unplaced()], 10.0), ('intrinsic_def_federated_value_at_server', *executor_test_utils. create_dummy_intrinsic_def_federated_value_at_server(), [executor_test_utils.create_dummy_value_unplaced()], 10.0), ('intrinsic_def_federated_weighted_mean', *executor_test_utils. create_dummy_intrinsic_def_federated_weighted_mean(), [ executor_test_utils.create_dummy_value_at_clients(), executor_test_utils.create_dummy_value_at_clients() ], 11.060606), ('intrinsic_def_federated_zip_at_clients', *executor_test_utils. create_dummy_intrinsic_def_federated_zip_at_clients(), [ executor_test_utils.create_dummy_value_at_clients(), executor_test_utils.create_dummy_value_at_clients() ], [ anonymous_tuple.AnonymousTuple([(None, 10.0), (None, 10.0)]), anonymous_tuple.AnonymousTuple([(None, 11.0), (None, 11.0)]), anonymous_tuple.AnonymousTuple([(None, 12.0), (None, 12.0)]) ]), ('intrinsic_def_federated_zip_at_server', *executor_test_utils. create_dummy_intrinsic_def_federated_zip_at_server(), [ executor_test_utils.create_dummy_value_at_server(), executor_test_utils.create_dummy_value_at_server() ], anonymous_tuple.AnonymousTuple([(None, 10.0), (None, 10.0)])), ('computation_intrinsic', *executor_test_utils.create_dummy_computation_intrinsic(), [executor_test_utils.create_dummy_computation_tensorflow_constant() ], 10.0), ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_identity(), [executor_test_utils.create_dummy_value_unplaced()], 10.0), ]) # pyformat: enable def test_returns_value_with_comp_and_arg(self, comp, comp_type, args, expected_result): executor = create_test_executor() comp = self.run_sync(executor.create_value(comp, comp_type)) elements = [self.run_sync(executor.create_value(*x)) for x in args] if len(elements) > 1: arg = self.run_sync(executor.create_tuple(elements)) else: arg = elements[0] result = self.run_sync(executor.create_call(comp, arg)) self.assertIsInstance(result, federating_executor.FederatingExecutorValue) self.assertEqual(result.type_signature.compact_representation(), comp_type.result.compact_representation()) actual_result = self.run_sync(result.compute()) if (all_isinstance([actual_result, expected_result], list) or all_isinstance([actual_result, expected_result], tf.data.Dataset)): for actual_element, expected_element in zip( actual_result, expected_result): self.assertEqual(actual_element, expected_element) else: self.assertEqual(actual_result, expected_result) def test_returns_value_with_intrinsic_def_federated_value_at_server_and_tuple( self): executor = create_test_executor(number_of_clients=3) arg, arg_type = executor_test_utils.create_dummy_computation_tuple() intrinsic_def = intrinsic_defs.FEDERATED_VALUE_AT_SERVER comp_type = computation_types.FunctionType( arg_type, type_factory.at_server(arg_type)) comp = pb.Computation( type=type_serialization.serialize_type(comp_type), intrinsic=pb.Intrinsic(uri=intrinsic_def.uri)) comp = self.run_sync(executor.create_value(comp, comp_type)) arg = self.run_sync(executor.create_value(arg, arg_type)) result = self.run_sync(executor.create_call(comp, arg)) self.assertIsInstance(result, federating_executor.FederatingExecutorValue) self.assertEqual(result.type_signature.compact_representation(), comp_type.result.compact_representation()) actual_result = self.run_sync(result.compute()) expected_result = [10.0] * 2 for actual_element, expected_element in zip(actual_result, expected_result): self.assertEqual(actual_element, expected_element) def test_returns_value_with_intrinsic_def_federated_eval_at_clients_and_random( self): executor = create_test_executor(number_of_clients=3) comp, comp_type = executor_test_utils.create_dummy_intrinsic_def_federated_eval_at_clients( ) arg, arg_type = executor_test_utils.create_dummy_computation_tensorflow_random( ) comp = self.run_sync(executor.create_value(comp, comp_type)) arg = self.run_sync(executor.create_value(arg, arg_type)) result = self.run_sync(executor.create_call(comp, arg)) self.assertIsInstance(result, federating_executor.FederatingExecutorValue) self.assertEqual(result.type_signature.compact_representation(), comp_type.result.compact_representation()) actual_result = self.run_sync(result.compute()) unique_results = set([x.numpy() for x in actual_result]) if len(actual_result) != len(unique_results): self.fail( 'Expected the result to contain different random numbers, found {}.' .format(actual_result)) # pyformat: disable @parameterized.named_parameters([ ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_empty()), ]) # pyformat: enable def test_returns_value_with_comp_only(self, comp, comp_type): executor = create_test_executor() comp = self.run_sync(executor.create_value(comp, comp_type)) result = self.run_sync(executor.create_call(comp)) self.assertIsInstance(result, federating_executor.FederatingExecutorValue) self.assertEqual(result.type_signature.compact_representation(), comp_type.result.compact_representation()) actual_result = self.run_sync(result.compute()) expected_result = [] self.assertCountEqual(actual_result, expected_result) def test_raises_type_error_with_unembedded_comp(self): executor = create_test_executor() comp, _ = executor_test_utils.create_dummy_computation_tensorflow_identity( ) arg, arg_type = executor_test_utils.create_dummy_value_unplaced() arg = self.run_sync(executor.create_value(arg, arg_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) def test_raises_type_error_with_unembedded_arg(self): executor = create_test_executor() comp, comp_type = executor_test_utils.create_dummy_computation_tensorflow_identity( ) arg, _ = executor_test_utils.create_dummy_value_unplaced() comp = self.run_sync(executor.create_value(comp, comp_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) # pyformat: disable @parameterized.named_parameters([ ('computation_intrinsic', *executor_test_utils.create_dummy_computation_intrinsic()), ('computation_lambda', *executor_test_utils.create_dummy_computation_lambda_identity()), ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_identity()), ] + get_named_parameters_for_supported_intrinsics()) # pyformat: enable def test_raises_type_error_with_comp_and_bad_arg(self, comp, comp_type): executor = create_test_executor() bad_arg = 'string' bad_arg_type = computation_types.TensorType(tf.string) comp = self.run_sync(executor.create_value(comp, comp_type)) arg = self.run_sync(executor.create_value(bad_arg, bad_arg_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) # pyformat: disable @parameterized.named_parameters([ ('computation_lambda', *executor_test_utils.create_dummy_computation_lambda_empty()), ('computation_placement', *executor_test_utils.create_dummy_computation_placement()), ('computation_tuple', *executor_test_utils.create_dummy_computation_tuple()), ('federated_type_at_clients', *executor_test_utils.create_dummy_value_at_clients()), ('federated_type_at_clients_all_equal', *executor_test_utils.create_dummy_value_at_clients_all_equal()), ('federated_type_at_server', *executor_test_utils.create_dummy_value_at_server()), ('unplaced_type', *executor_test_utils.create_dummy_value_unplaced()), ]) # pyformat: enable def test_raises_value_error_with_comp(self, comp, comp_type): executor = create_test_executor() comp = self.run_sync(executor.create_value(comp, comp_type)) with self.assertRaises(ValueError): self.run_sync(executor.create_call(comp)) def test_raises_not_implemented_error_with_intrinsic_def_federated_secure_sum( self): executor = create_test_executor() comp, comp_type = executor_test_utils.create_dummy_intrinsic_def_federated_secure_sum( ) arg_1, arg_1_type = executor_test_utils.create_dummy_value_at_clients() arg_2, arg_2_type = executor_test_utils.create_dummy_value_unplaced() comp = self.run_sync(executor.create_value(comp, comp_type)) arg_1 = self.run_sync(executor.create_value(arg_1, arg_1_type)) arg_2 = self.run_sync(executor.create_value(arg_2, arg_2_type)) args = self.run_sync(executor.create_tuple([arg_1, arg_2])) with self.assertRaises(NotImplementedError): self.run_sync(executor.create_call(comp, args)) def test_raises_not_implemented_error_with_unimplemented_intrinsic(self): executor = create_test_executor() dummy_intrinsic = intrinsic_defs.IntrinsicDef( 'DUMMY_INTRINSIC', 'dummy_intrinsic', computation_types.AbstractType('T')) comp = pb.Computation(intrinsic=pb.Intrinsic(uri='dummy_intrinsic'), type=type_serialization.serialize_type(tf.int32)) comp = self.run_sync(executor.create_value(comp)) with self.assertRaises(NotImplementedError): self.run_sync(executor.create_call(comp))
class FederatingExecutorCreateCallTest(executor_test_utils.AsyncTestCase, parameterized.TestCase): # pyformat: disable @parameterized.named_parameters([ ('intrinsic_def', *executor_test_utils.create_dummy_intrinsic_def(), *executor_test_utils.create_dummy_computation_tensorflow_constant()), ('computation_impl', *executor_test_utils.create_dummy_computation_impl(), *executor_test_utils.create_dummy_value_unplaced()), ('computation_intrinsic', *executor_test_utils.create_dummy_computation_intrinsic(), *executor_test_utils.create_dummy_computation_tensorflow_constant()), ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_identity(), *executor_test_utils.create_dummy_value_unplaced()), ]) # pyformat: enable def test_returns_value_with_comp_and_arg(self, comp, comp_type, arg, arg_type): executor = create_test_executor(num_clients=3) comp = self.run_sync(executor.create_value(comp, comp_type)) arg = self.run_sync(executor.create_value(arg, arg_type)) result = self.run_sync(executor.create_call(comp, arg)) self.assertIsInstance(result, federating_executor.FederatingExecutorValue) self.assertEqual(result.type_signature.compact_representation(), comp_type.result.compact_representation()) # pyformat: disable @parameterized.named_parameters([ ('computation_lambda', *executor_test_utils.create_dummy_computation_lambda_empty()), ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_empty()), ]) # pyformat: enable def test_returns_value_with_comp_only(self, comp, comp_type): executor = create_test_executor(num_clients=3) comp = self.run_sync(executor.create_value(comp, comp_type)) result = self.run_sync(executor.create_call(comp)) self.assertIsInstance(result, federating_executor.FederatingExecutorValue) self.assertEqual(result.type_signature.compact_representation(), comp_type.result.compact_representation()) # pyformat: disable @parameterized.named_parameters([ ('intrinsic_def', *executor_test_utils.create_dummy_intrinsic_def()), ('computation_impl', *executor_test_utils.create_dummy_computation_impl()), ('computation_intrinsic', *executor_test_utils.create_dummy_computation_intrinsic()), ('computation_lambda', *executor_test_utils.create_dummy_computation_lambda_identity()), ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_identity()), ]) # pyformat: enable def test_raises_type_error_with_comp_and_bad_arg(self, comp, comp_type): executor = create_test_executor(num_clients=3) bad_arg = 'string' bad_arg_type = computation_types.TensorType(tf.string) comp = self.run_sync(executor.create_value(comp, comp_type)) arg = self.run_sync(executor.create_value(bad_arg, bad_arg_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) def test_raises_type_error_with_unembedded_comp(self): executor = create_test_executor(num_clients=3) comp, _ = executor_test_utils.create_dummy_computation_tensorflow_identity( ) arg, arg_type = executor_test_utils.create_dummy_value_unplaced() arg = self.run_sync(executor.create_value(arg, arg_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) def test_raises_type_error_with_unembedded_arg(self): executor = create_test_executor(num_clients=3) comp, comp_type = executor_test_utils.create_dummy_computation_tensorflow_identity( ) arg, _ = executor_test_utils.create_dummy_value_unplaced() comp = self.run_sync(executor.create_value(comp, comp_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) # pyformat: disable @parameterized.named_parameters([ ('computation_call', *executor_test_utils.create_dummy_computation_call()), ('computation_placement', *executor_test_utils.create_dummy_computation_placement()), ('computation_selection', *executor_test_utils.create_dummy_computation_selection()), ('computation_tuple', *executor_test_utils.create_dummy_computation_tuple()), ('federated_type_clients', *executor_test_utils.create_dummy_value_clients()), ('federated_type_clients_all_equal', *executor_test_utils.create_dummy_value_clients_all_equal()), ('federated_type_server', *executor_test_utils.create_dummy_value_server()), ('unplaced_type', *executor_test_utils.create_dummy_value_unplaced()), ]) # pyformat: enable def test_raises_value_error_with_comp(self, comp, comp_type): executor = create_test_executor(num_clients=3) comp = self.run_sync(executor.create_value(comp, comp_type)) with self.assertRaises(ValueError): self.run_sync(executor.create_call(comp)) def test_raises_value_error_with_computation_lambda_and_arg(self): executor = create_test_executor(num_clients=3) comp, comp_type = executor_test_utils.create_dummy_computation_lambda_identity( ) arg, arg_type = executor_test_utils.create_dummy_value_unplaced() comp = self.run_sync(executor.create_value(comp, comp_type)) arg = self.run_sync(executor.create_value(arg, arg_type)) with self.assertRaises(ValueError): self.run_sync(executor.create_call(comp, arg)) def test_raises_not_implemented_error_with_unimplemented_intrinsic(self): executor = create_test_executor(num_clients=3) dummy_intrinsic = intrinsic_defs.IntrinsicDef( 'DUMMY_INTRINSIC', 'dummy_intrinsic', computation_types.AbstractType('T')) comp = pb.Computation(intrinsic=pb.Intrinsic(uri='dummy_intrinsic'), type=type_serialization.serialize_type(tf.int32)) comp = self.run_sync(executor.create_value(comp)) with self.assertRaises(NotImplementedError): self.run_sync(executor.create_call(comp))
class FederatingExecutorCreateCallTest(executor_test_utils.AsyncTestCase, parameterized.TestCase): # pyformat: disable @parameterized.named_parameters([ ('intrinsic_def_federated_apply', *executor_test_utils.create_dummy_intrinsic_def_federated_apply(), [ executor_test_utils.create_dummy_computation_tensorflow_identity( ), executor_test_utils.create_dummy_value_server() ], 10.0), ('intrinsic_def_federated_aggregate', *executor_test_utils.create_dummy_intrinsic_def_federated_aggregate(), [ executor_test_utils.create_dummy_value_clients(), executor_test_utils.create_dummy_value_unplaced(), executor_test_utils.create_dummy_computation_tensorflow_add(), executor_test_utils.create_dummy_computation_tensorflow_add(), executor_test_utils.create_dummy_computation_tensorflow_identity( ) ], 70.0), ('intrinsic_def_federated_broadcast', *executor_test_utils.create_dummy_intrinsic_def_federated_broadcast(), [executor_test_utils.create_dummy_value_server()], 10.0), ('intrinsic_def_federated_collect', *executor_test_utils.create_dummy_intrinsic_def_federated_collect(), [executor_test_utils.create_dummy_value_clients()], tf.data.Dataset.from_tensor_slices([10.0, 20.0, 30.0])), ('intrinsic_def_federated_eval_at_clients', *executor_test_utils. create_dummy_intrinsic_def_federated_eval_at_clients(), [executor_test_utils.create_dummy_computation_tensorflow_constant() ], [10.0] * 3), ('intrinsic_def_federated_eval_at_server', *executor_test_utils. create_dummy_intrinsic_def_federated_eval_at_server(), [executor_test_utils.create_dummy_computation_tensorflow_constant() ], 10.0), ('intrinsic_def_federated_map', *executor_test_utils.create_dummy_intrinsic_def_federated_map(), [ executor_test_utils.create_dummy_computation_tensorflow_identity( ), executor_test_utils.create_dummy_value_clients() ], [10.0, 20.0, 30.0]), ('intrinsic_def_federated_map_all_equal', *executor_test_utils. create_dummy_intrinsic_def_federated_map_all_equal(), [ executor_test_utils.create_dummy_computation_tensorflow_identity( ), executor_test_utils.create_dummy_value_clients_all_equal() ], 10.0), ('intrinsic_def_federated_mean', *executor_test_utils.create_dummy_intrinsic_def_federated_mean(), [executor_test_utils.create_dummy_value_clients()], 20.0), ('intrinsic_def_federated_sum', *executor_test_utils.create_dummy_intrinsic_def_federated_sum(), [executor_test_utils.create_dummy_value_clients()], 60.0), ('intrinsic_def_federated_reduce', *executor_test_utils.create_dummy_intrinsic_def_federated_reduce(), [ executor_test_utils.create_dummy_value_clients(), executor_test_utils.create_dummy_value_unplaced(), executor_test_utils.create_dummy_computation_tensorflow_add() ], 70.0), ('intrinsic_def_federated_value_at_clients', *executor_test_utils. create_dummy_intrinsic_def_federated_value_at_clients(), [executor_test_utils.create_dummy_value_unplaced()], 10.0), ('intrinsic_def_federated_value_at_server', *executor_test_utils. create_dummy_intrinsic_def_federated_value_at_server(), [executor_test_utils.create_dummy_value_unplaced()], 10.0), ('intrinsic_def_federated_weighted_mean', *executor_test_utils. create_dummy_intrinsic_def_federated_weighted_mean(), [ executor_test_utils.create_dummy_value_clients(), executor_test_utils.create_dummy_value_clients() ], 20.0), ('intrinsic_def_federated_zip_at_clients', *executor_test_utils. create_dummy_intrinsic_def_federated_zip_at_clients(), [ executor_test_utils.create_dummy_value_clients(), executor_test_utils.create_dummy_value_clients() ], [ anonymous_tuple.AnonymousTuple([(None, 10.0), (None, 10.0)]), anonymous_tuple.AnonymousTuple([(None, 20.0), (None, 20.0)]), anonymous_tuple.AnonymousTuple([(None, 30.0), (None, 30.0)]) ]), ('intrinsic_def_federated_zip_at_server', *executor_test_utils. create_dummy_intrinsic_def_federated_zip_at_server(), [ executor_test_utils.create_dummy_value_server(), executor_test_utils.create_dummy_value_server() ], anonymous_tuple.AnonymousTuple([(None, 10.0), (None, 10.0)])), ('computation_intrinsic', *executor_test_utils.create_dummy_computation_intrinsic(), [executor_test_utils.create_dummy_computation_tensorflow_constant() ], 10.0), ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_identity(), [executor_test_utils.create_dummy_value_unplaced()], 10.0), ]) # pyformat: enable def test_returns_value_with_comp_and_arg(self, comp, comp_type, args, expected_result): if comp == intrinsic_defs.FEDERATED_WEIGHTED_MEAN: self.skipTest( 'TODO(b/134543154): A `intrinsic_defs.FEDERATED_WEIGHTED_MEAN` can ' 'not be executed directly on top of a plain TensorFlow-based ' 'executor.') executor = create_test_executor(num_clients=3) comp = self.run_sync(executor.create_value(comp, comp_type)) elements = [self.run_sync(executor.create_value(*x)) for x in args] if len(elements) > 1: arg = self.run_sync(executor.create_tuple(elements)) else: arg = elements[0] result = self.run_sync(executor.create_call(comp, arg)) self.assertIsInstance(result, federating_executor.FederatingExecutorValue) self.assertEqual(result.type_signature.compact_representation(), comp_type.result.compact_representation()) actual_result = self.run_sync(result.compute()) if (all_isinstance([actual_result, expected_result], list) or all_isinstance([actual_result, expected_result], tf.data.Dataset)): for actual_element, expected_element in zip( actual_result, expected_result): self.assertEqual(actual_element, expected_element) else: self.assertEqual(actual_result, expected_result) # pyformat: disable @parameterized.named_parameters([ ('computation_lambda', *executor_test_utils.create_dummy_computation_lambda_empty()), ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_empty()), ]) # pyformat: enable def test_returns_value_with_comp_only(self, comp, comp_type): executor = create_test_executor(num_clients=3) comp = self.run_sync(executor.create_value(comp, comp_type)) result = self.run_sync(executor.create_call(comp)) self.assertIsInstance(result, federating_executor.FederatingExecutorValue) self.assertEqual(result.type_signature.compact_representation(), comp_type.result.compact_representation()) actual_result = self.run_sync(result.compute()) expected_result = [] self.assertCountEqual(actual_result, expected_result) def test_raises_type_error_with_unembedded_comp(self): executor = create_test_executor(num_clients=3) comp, _ = executor_test_utils.create_dummy_computation_tensorflow_identity( ) arg, arg_type = executor_test_utils.create_dummy_value_unplaced() arg = self.run_sync(executor.create_value(arg, arg_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) def test_raises_type_error_with_unembedded_arg(self): executor = create_test_executor(num_clients=3) comp, comp_type = executor_test_utils.create_dummy_computation_tensorflow_identity( ) arg, _ = executor_test_utils.create_dummy_value_unplaced() comp = self.run_sync(executor.create_value(comp, comp_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) # pyformat: disable @parameterized.named_parameters([ ('computation_intrinsic', *executor_test_utils.create_dummy_computation_intrinsic()), ('computation_lambda', *executor_test_utils.create_dummy_computation_lambda_identity()), ('computation_tensorflow', *executor_test_utils.create_dummy_computation_tensorflow_identity()), ] + get_named_parameters_for_supported_intrinsics()) # pyformat: enable def test_raises_type_error_with_comp_and_bad_arg(self, comp, comp_type): executor = create_test_executor(num_clients=3) bad_arg = 'string' bad_arg_type = computation_types.TensorType(tf.string) comp = self.run_sync(executor.create_value(comp, comp_type)) arg = self.run_sync(executor.create_value(bad_arg, bad_arg_type)) with self.assertRaises(TypeError): self.run_sync(executor.create_call(comp, arg)) # pyformat: disable @parameterized.named_parameters([ ('computation_placement', *executor_test_utils.create_dummy_computation_placement()), ('computation_tuple', *executor_test_utils.create_dummy_computation_tuple()), ('federated_type_clients', *executor_test_utils.create_dummy_value_clients()), ('federated_type_clients_all_equal', *executor_test_utils.create_dummy_value_clients_all_equal()), ('federated_type_server', *executor_test_utils.create_dummy_value_server()), ('unplaced_type', *executor_test_utils.create_dummy_value_unplaced()), ]) # pyformat: enable def test_raises_value_error_with_comp(self, comp, comp_type): executor = create_test_executor(num_clients=3) comp = self.run_sync(executor.create_value(comp, comp_type)) with self.assertRaises(ValueError): self.run_sync(executor.create_call(comp)) def test_raises_value_error_with_computation_lambda_and_arg(self): executor = create_test_executor(num_clients=3) comp, comp_type = executor_test_utils.create_dummy_computation_lambda_identity( ) arg, arg_type = executor_test_utils.create_dummy_value_unplaced() comp = self.run_sync(executor.create_value(comp, comp_type)) arg = self.run_sync(executor.create_value(arg, arg_type)) with self.assertRaises(ValueError): self.run_sync(executor.create_call(comp, arg)) def test_raises_not_implemented_error_with_intrinsic_def_federated_secure_sum( self): executor = create_test_executor(num_clients=3) comp, comp_type = executor_test_utils.create_dummy_intrinsic_def_federated_secure_sum( ) arg_1, arg_1_type = executor_test_utils.create_dummy_value_clients() arg_2, arg_2_type = executor_test_utils.create_dummy_value_unplaced() comp = self.run_sync(executor.create_value(comp, comp_type)) arg_1 = self.run_sync(executor.create_value(arg_1, arg_1_type)) arg_2 = self.run_sync(executor.create_value(arg_2, arg_2_type)) args = self.run_sync(executor.create_tuple([arg_1, arg_2])) with self.assertRaises(NotImplementedError): self.run_sync(executor.create_call(comp, args)) def test_raises_not_implemented_error_with_unimplemented_intrinsic(self): executor = create_test_executor(num_clients=3) dummy_intrinsic = intrinsic_defs.IntrinsicDef( 'DUMMY_INTRINSIC', 'dummy_intrinsic', computation_types.AbstractType('T')) comp = pb.Computation(intrinsic=pb.Intrinsic(uri='dummy_intrinsic'), type=type_serialization.serialize_type(tf.int32)) comp = self.run_sync(executor.create_value(comp)) with self.assertRaises(NotImplementedError): self.run_sync(executor.create_call(comp))