def test_pserver(self): role = role_maker.UserDefinedRoleMaker( current_id=0, role=role_maker.Role.SERVER, worker_num=2, server_endpoints=["127.0.0.1:36011", "127.0.0.1:36012"]) fleet.init(role) batch_size = 128 is_sparse = True is_distribute = False strategy = DistributeTranspilerConfig() strategy.sync_mode = False strategy.geo_sgd_mode = True strategy.geo_sgd_need_push_nums = 5 avg_cost, _, _, _ = train_network(batch_size, is_distribute, is_sparse) fluid.clip.set_gradient_clip( clip=fluid.clip.GradientClipByGlobalNorm(2.0)) optimizer = fluid.optimizer.SGD(0.1) optimizer = fleet.distributed_optimizer(optimizer, strategy) optimizer.minimize(avg_cost) pserver_startup_program = fleet.startup_program pserver_mian_program = fleet.main_program
def test_pserver(self): role = role_maker.UserDefinedRoleMaker( current_id=0, role=role_maker.Role.SERVER, worker_num=2, server_endpoints=["127.0.0.1:36011", "127.0.0.1:36012"]) fleet.init(role) batch_size = 128 is_sparse = True is_distribute = False strategy = paddle.distributed.fleet.DistributedStrategy() strategy.a_sync = True strategy.a_sync_configs = {"k_steps": 100, "launch_barrier": False} avg_cost, _, _, _ = train_network(batch_size, is_distribute, is_sparse) optimizer = fluid.optimizer.SGD(0.1) optimizer = fleet.distributed_optimizer(optimizer, strategy) optimizer.minimize(avg_cost)
def test_pserver(self): role = role_maker.UserDefinedRoleMaker( current_id=0, role=role_maker.Role.SERVER, worker_num=2, server_endpoints=["127.0.0.1:36011", "127.0.0.1:36012"]) fleet.init(role) batch_size = 128 is_sparse = True is_distribute = False strategy = StrategyFactory.create_geo_strategy(5) avg_cost, _, _, _ = train_network(batch_size, is_distribute, is_sparse) optimizer = fluid.optimizer.SGD(0.1) optimizer = fleet.distributed_optimizer(optimizer, strategy) optimizer.minimize(avg_cost) pserver_startup_program = fleet.startup_program pserver_mian_program = fleet.main_program