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