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264 lines
10 KiB
264 lines
10 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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import paddle.fluid as fluid
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from paddle.fluid.transpiler.distribute_transpiler import DistributeTranspilerConfig
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from paddle.fluid.incubate.fleet.base.role_maker import UserDefinedRoleMaker
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from paddle.fluid.incubate.fleet.base.role_maker import UserDefinedCollectiveRoleMaker
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from paddle.fluid.incubate.fleet.base.role_maker import Role
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import paddle.fluid.incubate.fleet.base.role_maker as role_maker
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from paddle.fluid.incubate.fleet.parameter_server.distribute_transpiler import fleet
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from paddle.fluid.incubate.fleet.parameter_server import TranspilerOptimizer
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from paddle.fluid.incubate.fleet.collective import CollectiveOptimizer
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from dist_simnet_bow import train_network
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class DistributeTranspilerConfigTest(unittest.TestCase):
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def set_runtime_split_send_recv(self, config, value):
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config.runtime_split_send_recv = value
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def set_sync_mode(self, config, value):
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config.sync_mode = value
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def testConfig(self):
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config = DistributeTranspilerConfig()
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self.assertRaises(Exception, self.set_sync_mode, config, None)
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self.assertRaises(Exception, self.set_runtime_split_send_recv, config,
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None)
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self.assertRaises(Exception, self.set_runtime_split_send_recv, config,
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True)
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self.set_sync_mode(config, False)
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self.assertFalse(config.sync_mode)
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self.set_runtime_split_send_recv(config, True)
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self.assertRaises(Exception, self.set_sync_mode, config, True)
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class FleetTest(unittest.TestCase):
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def testInvalidInputs(self):
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self.assertRaises(Exception, fleet.split_files, "files")
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self.assertRaises(Exception, fleet.init, "pserver")
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data = fluid.layers.data(name='X', shape=[1], dtype='float32')
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hidden = fluid.layers.fc(input=data, size=10)
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loss = fluid.layers.mean(hidden)
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adam = fluid.optimizer.Adam()
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adam.minimize(loss)
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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pe = fluid.ParallelExecutor(use_cuda=False, loss_name=loss.name)
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self.assertRaises(
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Exception,
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fleet.save_inference_model,
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dirname='/tmp/',
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feeded_var_names=['X'],
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target_vars=[loss],
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executor=pe)
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self.assertRaises(
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Exception,
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fleet.save_inference_model,
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dirname='/tmp/',
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feeded_var_names=['X'],
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target_vars=[loss],
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executor="executor")
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compiled_prog = fluid.compiler.CompiledProgram(
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fluid.default_main_program())
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self.assertRaises(
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Exception,
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fleet.save_inference_model,
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dirname='/tmp/',
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feeded_var_names=['X'],
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target_vars=[loss],
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executor=exe,
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main_program=compiled_prog)
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self.assertRaises(
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Exception, fleet.save_persistables, executor=pe, dirname='/tmp/')
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self.assertRaises(
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Exception,
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fleet.save_persistables,
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executor="executor",
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dirname='/tmp/')
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self.assertRaises(
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Exception,
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fleet.save_persistables,
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executor=exe,
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dirname='/tmp/',
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main_program=compiled_prog)
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self.assertRaises(Exception, fleet._transpile, "config")
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def set_program(self, avg_cost, strategy):
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with fluid.scope_guard(fluid.Scope()):
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optimizer = fluid.optimizer.SGD(0.1)
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optimizer = fleet.distributed_optimizer(optimizer, strategy)
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optimizer.minimize(avg_cost)
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def test_init_role(self):
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role = role_maker.UserDefinedRoleMaker(
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current_id=0,
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role=role_maker.Role.SERVER,
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worker_num=2,
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server_endpoints=["127.0.0.1:36011", "127.0.0.1:36012"])
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# for test optimizer without init(role)
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# fleet.init(role)
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batch_size = 128
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is_sparse = True
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is_distribute = False
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strategy = DistributeTranspilerConfig()
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strategy.sync_mode = False
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strategy.geo_sgd_mode = True
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strategy.geo_sgd_need_push_nums = 5
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avg_cost, _, _ = train_network(batch_size, is_distribute, is_sparse)
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self.assertRaises(Exception, self.set_program, avg_cost, strategy)
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def test_transpile(self):
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role = role_maker.UserDefinedRoleMaker(
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current_id=0,
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role=role_maker.Role.SERVER,
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worker_num=2,
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server_endpoints=["127.0.0.1:36011", "127.0.0.1:36012"])
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# for test optimizer without init(role)
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fleet.init(role)
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batch_size = 128
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is_sparse = True
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is_distribute = False
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strategy = DistributeTranspilerConfig()
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strategy.sync_mode = False
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strategy.runtime_split_send_recv = True
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avg_cost, _, _ = train_network(batch_size, is_distribute, is_sparse)
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self.set_program(avg_cost, strategy)
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strategy.runtime_split_send_recv = False
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self.set_program(avg_cost, strategy)
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class TranspilerOptimizerTest(unittest.TestCase):
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def testInvalidInputs(self):
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self.assertRaises(Exception, TranspilerOptimizer, "Adam", None)
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self.assertRaises(Exception, TranspilerOptimizer,
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fluid.optimizer.Adam(0.001), "strategy")
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transpiler = TranspilerOptimizer(fluid.optimizer.Adam(0.001))
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self.assertRaises(Exception, transpiler.minimize, loss=[])
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data = fluid.layers.data(name='X', shape=[1], dtype='float32')
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hidden = fluid.layers.fc(input=data, size=10)
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loss = fluid.layers.mean(hidden)
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self.assertRaises(
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Exception, transpiler.minimize, loss=loss.name, startup_program=[])
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class UserDefinedRoleMakerTest(unittest.TestCase):
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def createRoleMaker(self,
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current_id=0,
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role=Role.WORKER,
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worker_num=1,
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server_endpoints=["127.0.0.1:8080"]):
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role = UserDefinedRoleMaker(current_id, role, worker_num,
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server_endpoints)
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def testRoleMaker(self):
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self.createRoleMaker()
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# test all invalid server_endpoints
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self.assertRaises(
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Exception, self.createRoleMaker,
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server_endpoints=None) # server_endpoints must be as list
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self.assertRaises(
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Exception, self.createRoleMaker,
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server_endpoints=[]) # server_endpoints can't be empty
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self.assertRaises(
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Exception, self.createRoleMaker, server_endpoints=[
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3, []
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]) # element in server_endpoints must be as string
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self.assertRaises(
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Exception,
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self.createRoleMaker,
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server_endpoints=["127.0.0.1:8080", "127.0.0.1:8080"]
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) # element in server_endpoints can't be duplicate
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# test all invalid current_id
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self.assertRaises(
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Exception, self.createRoleMaker,
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current_id="0") # current_id must be as int
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self.assertRaises(
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Exception, self.createRoleMaker,
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current_id=-1) # current_id must be greater than or equal to 0
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self.assertRaises(
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Exception,
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self.createRoleMaker,
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current_id=1,
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role=Role.SERVER,
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server_endpoints=["127.0.0.1:8080"]
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) # if role is server, current_id must be less than len(server_endpoints)
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# test all invalid worker_num
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self.assertRaises(
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Exception, self.createRoleMaker,
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worker_num="1") # worker_num must be as int
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self.assertRaises(
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Exception, self.createRoleMaker,
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worker_num=0) # worker_num must be greater than 0
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# test all invalid role
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self.assertRaises(
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Exception, self.createRoleMaker,
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role=3) # role must be as Role(Role.WORKER=1, Role.SERVER=2)
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class UserDefinedCollectiveRoleMakerTest(unittest.TestCase):
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def createRoleMaker(self, current_id=0,
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worker_endpoints=["127.0.0.1:8080"]):
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role = UserDefinedCollectiveRoleMaker(current_id, worker_endpoints)
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def testRoleMaker(self):
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self.createRoleMaker()
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# test all invalid worker_endpoints
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self.assertRaises(
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Exception, self.createRoleMaker,
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worker_endpoints=None) # worker_endpoints must be as list
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self.assertRaises(
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Exception, self.createRoleMaker,
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worker_endpoints=[]) # worker_endpoints can't be empty
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self.assertRaises(
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Exception, self.createRoleMaker,
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worker_endpoints=[3,
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[]]) # element worker_endpoints must be as string
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self.assertRaises(
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Exception,
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self.createRoleMaker,
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worker_endpoints=["127.0.0.1:8080", "127.0.0.1:8080"]
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) # element in worker_endpoints can't be duplicate
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# test all invalid current_id
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self.assertRaises(
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Exception, self.createRoleMaker,
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current_id="0") # current_id must be as int
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self.assertRaises(
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Exception, self.createRoleMaker,
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current_id=-1) # current_id must be greater than or equal to 0
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self.assertRaises(
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Exception,
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self.createRoleMaker,
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current_id=1,
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worker_endpoints=["127.0.0.1:8080"]
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) # current_id must be less than len(worker_endpoints)
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class CollectiveOptimizerTest(unittest.TestCase):
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def test_ds_as_None(self):
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optimizer = fluid.optimizer.AdamOptimizer()
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dist_optimizer = CollectiveOptimizer(optimizer, strategy=None)
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if __name__ == '__main__':
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unittest.main()
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