# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import print_function import unittest import paddle.fluid as fluid from paddle.fluid.transpiler.distribute_transpiler import DistributeTranspilerConfig from paddle.fluid.incubate.fleet.base.role_maker import UserDefinedRoleMaker from paddle.fluid.incubate.fleet.base.role_maker import UserDefinedCollectiveRoleMaker from paddle.fluid.incubate.fleet.base.role_maker import Role import paddle.fluid.incubate.fleet.base.role_maker as role_maker from paddle.fluid.incubate.fleet.parameter_server.distribute_transpiler import fleet from paddle.fluid.incubate.fleet.parameter_server import TranspilerOptimizer from paddle.fluid.incubate.fleet.collective import CollectiveOptimizer from dist_simnet_bow import train_network class DistributeTranspilerConfigTest(unittest.TestCase): def set_runtime_split_send_recv(self, config, value): config.runtime_split_send_recv = value def set_sync_mode(self, config, value): config.sync_mode = value def testConfig(self): config = DistributeTranspilerConfig() self.assertRaises(Exception, self.set_sync_mode, config, None) self.assertRaises(Exception, self.set_runtime_split_send_recv, config, None) self.assertRaises(Exception, self.set_runtime_split_send_recv, config, True) self.set_sync_mode(config, False) self.assertFalse(config.sync_mode) self.set_runtime_split_send_recv(config, True) self.assertRaises(Exception, self.set_sync_mode, config, True) class FleetTest(unittest.TestCase): def testInvalidInputs(self): self.assertRaises(Exception, fleet.split_files, "files") self.assertRaises(Exception, fleet.init, "pserver") data = fluid.layers.data(name='X', shape=[1], dtype='float32') hidden = fluid.layers.fc(input=data, size=10) loss = fluid.layers.mean(hidden) adam = fluid.optimizer.Adam() adam.minimize(loss) place = fluid.CPUPlace() exe = fluid.Executor(place) pe = fluid.ParallelExecutor(use_cuda=False, loss_name=loss.name) self.assertRaises( Exception, fleet.save_inference_model, dirname='/tmp/', feeded_var_names=['X'], target_vars=[loss], executor=pe) self.assertRaises( Exception, fleet.save_inference_model, dirname='/tmp/', feeded_var_names=['X'], target_vars=[loss], executor="executor") compiled_prog = fluid.compiler.CompiledProgram( fluid.default_main_program()) self.assertRaises( Exception, fleet.save_inference_model, dirname='/tmp/', feeded_var_names=['X'], target_vars=[loss], executor=exe, main_program=compiled_prog) self.assertRaises( Exception, fleet.save_persistables, executor=pe, dirname='/tmp/') self.assertRaises( Exception, fleet.save_persistables, executor="executor", dirname='/tmp/') self.assertRaises( Exception, fleet.save_persistables, executor=exe, dirname='/tmp/', main_program=compiled_prog) self.assertRaises(Exception, fleet._transpile, "config") def set_program(self, avg_cost, strategy): with fluid.scope_guard(fluid.Scope()): optimizer = fluid.optimizer.SGD(0.1) optimizer = fleet.distributed_optimizer(optimizer, strategy) optimizer.minimize(avg_cost) def test_init_role(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"]) # for test optimizer without init(role) # 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) self.assertRaises(Exception, self.set_program, avg_cost, strategy) def test_transpile(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"]) # for test optimizer without init(role) fleet.init(role) batch_size = 128 is_sparse = True is_distribute = False strategy = DistributeTranspilerConfig() strategy.sync_mode = False strategy.runtime_split_send_recv = True avg_cost, _, _ = train_network(batch_size, is_distribute, is_sparse) self.set_program(avg_cost, strategy) strategy.runtime_split_send_recv = False self.set_program(avg_cost, strategy) class TranspilerOptimizerTest(unittest.TestCase): def testInvalidInputs(self): self.assertRaises(Exception, TranspilerOptimizer, "Adam", None) self.assertRaises(Exception, TranspilerOptimizer, fluid.optimizer.Adam(0.001), "strategy") transpiler = TranspilerOptimizer(fluid.optimizer.Adam(0.001)) self.assertRaises(Exception, transpiler.minimize, loss=[]) data = fluid.layers.data(name='X', shape=[1], dtype='float32') hidden = fluid.layers.fc(input=data, size=10) loss = fluid.layers.mean(hidden) self.assertRaises( Exception, transpiler.minimize, loss=loss.name, startup_program=[]) class UserDefinedRoleMakerTest(unittest.TestCase): def createRoleMaker(self, current_id=0, role=Role.WORKER, worker_num=1, server_endpoints=["127.0.0.1:8080"]): role = UserDefinedRoleMaker(current_id, role, worker_num, server_endpoints) def testRoleMaker(self): self.createRoleMaker() # test all invalid server_endpoints self.assertRaises( Exception, self.createRoleMaker, server_endpoints=None) # server_endpoints must be as list self.assertRaises( Exception, self.createRoleMaker, server_endpoints=[]) # server_endpoints can't be empty self.assertRaises( Exception, self.createRoleMaker, server_endpoints=[ 3, [] ]) # element in server_endpoints must be as string self.assertRaises( Exception, self.createRoleMaker, server_endpoints=["127.0.0.1:8080", "127.0.0.1:8080"] ) # element in server_endpoints can't be duplicate # test all invalid current_id self.assertRaises( Exception, self.createRoleMaker, current_id="0") # current_id must be as int self.assertRaises( Exception, self.createRoleMaker, current_id=-1) # current_id must be greater than or equal to 0 self.assertRaises( Exception, self.createRoleMaker, current_id=1, role=Role.SERVER, server_endpoints=["127.0.0.1:8080"] ) # if role is server, current_id must be less than len(server_endpoints) # test all invalid worker_num self.assertRaises( Exception, self.createRoleMaker, worker_num="1") # worker_num must be as int self.assertRaises( Exception, self.createRoleMaker, worker_num=0) # worker_num must be greater than 0 # test all invalid role self.assertRaises( Exception, self.createRoleMaker, role=3) # role must be as Role(Role.WORKER=1, Role.SERVER=2) class UserDefinedCollectiveRoleMakerTest(unittest.TestCase): def createRoleMaker(self, current_id=0, worker_endpoints=["127.0.0.1:8080"]): role = UserDefinedCollectiveRoleMaker(current_id, worker_endpoints) def testRoleMaker(self): self.createRoleMaker() # test all invalid worker_endpoints self.assertRaises( Exception, self.createRoleMaker, worker_endpoints=None) # worker_endpoints must be as list self.assertRaises( Exception, self.createRoleMaker, worker_endpoints=[]) # worker_endpoints can't be empty self.assertRaises( Exception, self.createRoleMaker, worker_endpoints=[3, []]) # element worker_endpoints must be as string self.assertRaises( Exception, self.createRoleMaker, worker_endpoints=["127.0.0.1:8080", "127.0.0.1:8080"] ) # element in worker_endpoints can't be duplicate # test all invalid current_id self.assertRaises( Exception, self.createRoleMaker, current_id="0") # current_id must be as int self.assertRaises( Exception, self.createRoleMaker, current_id=-1) # current_id must be greater than or equal to 0 self.assertRaises( Exception, self.createRoleMaker, current_id=1, worker_endpoints=["127.0.0.1:8080"] ) # current_id must be less than len(worker_endpoints) class CollectiveOptimizerTest(unittest.TestCase): def test_ds_as_None(self): optimizer = fluid.optimizer.AdamOptimizer() dist_optimizer = CollectiveOptimizer(optimizer, strategy=None) if __name__ == '__main__': unittest.main()