提交 2c6159a1 编写于 作者: S sneaxiy

fix unittest

fix cmake
test=develop
上级 eb825246
...@@ -171,9 +171,9 @@ if(WITH_DISTRIBUTE) ...@@ -171,9 +171,9 @@ if(WITH_DISTRIBUTE)
set_source_files_properties(executor.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS}) set_source_files_properties(executor.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
else() else()
if(NOT WIN32) if(NOT WIN32)
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass ngraph_operator variable_helper) cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass ngraph_operator variable_helper garbage_collector)
else(NOT WIN32) else(NOT WIN32)
cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass variable_helper) cc_library(executor SRCS executor.cc DEPS op_registry device_context scope framework_proto glog lod_rank_table feed_fetch_method graph_to_program_pass variable_helper garbage_collector)
endif(NOT WIN32) endif(NOT WIN32)
cc_test(test_naive_executor SRCS naive_executor_test.cc DEPS naive_executor elementwise_add_op) cc_test(test_naive_executor SRCS naive_executor_test.cc DEPS naive_executor elementwise_add_op)
endif() endif()
......
# 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.
import os
os.environ['FLAGS_eager_delete_tensor_gb'] = '0.0'
os.environ['CPU_NUM'] = '2'
import six
import unittest
import paddle
import paddle.fluid.core as core
import paddle.fluid as fluid
def train(network, use_cuda, use_parallel_executor, batch_size=32, pass_num=2):
if use_cuda and not core.is_compiled_with_cuda():
print('Skip use_cuda=True because Paddle is not compiled with cuda')
return
word_dict = paddle.dataset.imdb.word_dict()
train_reader = paddle.batch(
paddle.dataset.imdb.train(word_dict), batch_size=batch_size)
data = fluid.layers.data(
name="words", shape=[1], dtype="int64", lod_level=1)
label = fluid.layers.data(name="label", shape=[1], dtype="int64")
cost = network(data, label, len(word_dict))
optimizer = fluid.optimizer.Adagrad(learning_rate=0.2)
optimizer.minimize(cost)
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
feeder = fluid.DataFeeder(feed_list=[data, label], place=place)
reader = feeder.decorate_reader(
train_reader, multi_devices=use_parallel_executor)
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
if use_parallel_executor:
train_exe = fluid.ParallelExecutor(
use_cuda=use_cuda, loss_name=cost.name)
fetch_list = [cost.name]
else:
train_exe = exe
fetch_list = [cost]
for pass_id in six.moves.xrange(pass_num):
batch_id = 0
for data in reader():
train_exe.run(feed=data,
fetch_list=fetch_list if batch_id % 4 == 0 else [])
batch_id += 1
if batch_id > 16:
break
class TestBase(unittest.TestCase):
def setUp(self):
self.net = None
def test_network(self):
if self.net is None:
return
for use_cuda in [True, False]:
for use_parallel_executor in [False, True]:
print('network: {}, use_cuda: {}, use_parallel_executor: {}'.
format(self.net.__name__, use_cuda,
use_parallel_executor))
with fluid.program_guard(fluid.Program(), fluid.Program()):
with fluid.scope_guard(core.Scope()):
train(self.net, use_cuda, use_parallel_executor)
...@@ -13,7 +13,7 @@ ...@@ -13,7 +13,7 @@
# limitations under the License. # limitations under the License.
import unittest import unittest
from test_eager_deletion_lstm_net import TestBase from test_eager_deletion_dynamic_rnn_base import TestBase
import paddle.fluid as fluid import paddle.fluid as fluid
......
...@@ -12,60 +12,9 @@ ...@@ -12,60 +12,9 @@
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
import os from test_eager_deletion_dynamic_rnn_base import TestBase
os.environ['FLAGS_eager_delete_tensor_gb'] = '0.0'
os.environ['CPU_NUM'] = '2'
import six
import unittest
import paddle
import paddle.fluid.core as core
import paddle.fluid as fluid import paddle.fluid as fluid
import unittest
def train(network, use_cuda, use_parallel_executor, batch_size=32, pass_num=2):
if use_cuda and not core.is_compiled_with_cuda():
print('Skip use_cuda=True because Paddle is not compiled with cuda')
return
word_dict = paddle.dataset.imdb.word_dict()
train_reader = paddle.batch(
paddle.dataset.imdb.train(word_dict), batch_size=batch_size)
data = fluid.layers.data(
name="words", shape=[1], dtype="int64", lod_level=1)
label = fluid.layers.data(name="label", shape=[1], dtype="int64")
cost = network(data, label, len(word_dict))
optimizer = fluid.optimizer.Adagrad(learning_rate=0.2)
optimizer.minimize(cost)
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
feeder = fluid.DataFeeder(feed_list=[data, label], place=place)
reader = feeder.decorate_reader(
train_reader, multi_devices=use_parallel_executor)
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
if use_parallel_executor:
train_exe = fluid.ParallelExecutor(
use_cuda=use_cuda, loss_name=cost.name)
fetch_list = [cost.name]
else:
train_exe = exe
fetch_list = [cost]
for pass_id in six.moves.xrange(pass_num):
batch_id = 0
for data in reader():
train_exe.run(feed=data,
fetch_list=fetch_list if batch_id % 4 == 0 else [])
batch_id += 1
if batch_id > 16:
break
def lstm_net(data, def lstm_net(data,
...@@ -92,20 +41,10 @@ def lstm_net(data, ...@@ -92,20 +41,10 @@ def lstm_net(data,
return avg_cost return avg_cost
class TestBase(unittest.TestCase): class LSTMTest(TestBase):
def setUp(self): def setUp(self):
self.net = lstm_net self.net = lstm_net
def test_network(self):
for use_cuda in [True, False]:
for use_parallel_executor in [False, True]:
print('network: {}, use_cuda: {}, use_parallel_executor: {}'.
format(self.net.__name__, use_cuda,
use_parallel_executor))
with fluid.program_guard(fluid.Program(), fluid.Program()):
with fluid.scope_guard(core.Scope()):
train(self.net, use_cuda, use_parallel_executor)
if __name__ == "__main__": if __name__ == "__main__":
unittest.main() unittest.main()
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册