fix unittest

fix cmake
test=develop

paddle/fluid/framework/CMakeLists.txt

@@ -171,9 +171,9 @@ if(WITH_DISTRIBUTE)
   set_source_files_properties(executor.cc PROPERTIES COMPILE_FLAGS ${DISTRIBUTE_COMPILE_FLAGS})
 else()
   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)
-    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)
   cc_test(test_naive_executor SRCS naive_executor_test.cc DEPS naive_executor elementwise_add_op)
 endif()

python/paddle/fluid/tests/unittests/test_eager_deletion_dynamic_rnn_base.py

@@ -0,0 +1,86 @@
+# 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)

python/paddle/fluid/tests/unittests/test_eager_deletion_gru_net.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import unittest
-from test_eager_deletion_lstm_net import TestBase
+from test_eager_deletion_dynamic_rnn_base import TestBase
 import paddle.fluid as fluid
 
 

python/paddle/fluid/tests/unittests/test_eager_deletion_lstm_net.py

@@ -12,60 +12,9 @@
 # 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
+from test_eager_deletion_dynamic_rnn_base import TestBase
 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
+import unittest
 
 
 def lstm_net(data,
@@ -92,20 +41,10 @@ def lstm_net(data,
     return avg_cost
 
 
-class TestBase(unittest.TestCase):
+class LSTMTest(TestBase):
     def setUp(self):
         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__":
     unittest.main()