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modify the test config for test_CompareTwoNets.cpp
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-346
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7 files changed

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-346
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‎paddle/gserver/tests/CMakeLists.txt

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@@ -111,3 +111,12 @@ if(NOT ON_TRAVIS)
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${CMAKE_CURRENT_BINARY_DIR}/test_CompareSparse
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WORKING_DIRECTORY ${PADDLE_SOURCE_DIR}/paddle/)
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endif()
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################ test_CompareTwoNets ######################
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add_unittest_without_exec(test_CompareTwoNets
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test_CompareTwoNets.cpp)
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add_test(NAME test_CompareTwoNets
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COMMAND ${PADDLE_SOURCE_DIR}/paddle/.set_python_path.sh -d
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${PADDLE_SOURCE_DIR}/python:${PADDLE_SOURCE_DIR}/paddle/gserver/tests
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${CMAKE_CURRENT_BINARY_DIR}/test_CompareTwoNets
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WORKING_DIRECTORY ${PADDLE_SOURCE_DIR}/paddle/)

‎paddle/gserver/tests/sequence_recurrent.py

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#!/usr/bin/env python
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# Copyright (c) 2016 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 paddle.trainer_config_helpers import *
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######################## data source ################################
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dict_path = 'gserver/tests/Sequence/tour_dict_phrase.dict'
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dict_file = dict()
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for line_count, line in enumerate(open(dict_path, "r")):
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dict_file[line.strip()] = line_count
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define_py_data_sources2(
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train_list='gserver/tests/Sequence/train.list',
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test_list=None,
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module='sequenceGen',
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obj='process',
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args={"dict_file": dict_file})
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settings(batch_size=5)
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######################## network configure ################################
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dict_dim = len(open(dict_path, 'r').readlines())
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word_dim = 128
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hidden_dim = 128
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label_dim = 3
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# This config is designed to be equivalent with sequence_recurrent_group.py
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data = data_layer(name="word", size=dict_dim)
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emb = embedding_layer(
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input=data, size=word_dim, param_attr=ParamAttr(name="emb"))
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recurrent = recurrent_layer(input=emb, bias_attr=False, act=SoftmaxActivation())
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recurrent_last = last_seq(input=recurrent)
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with mixed_layer(
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size=label_dim, act=SoftmaxActivation(), bias_attr=True) as output:
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output += full_matrix_projection(input=recurrent_last)
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outputs(
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classification_cost(
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input=output, label=data_layer(
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name="label", size=1)))

‎paddle/gserver/tests/sequence_recurrent_group.py

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#!/usr/bin/env python
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# Copyright (c) 2016 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 paddle.trainer_config_helpers import *
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######################## data source ################################
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dict_path = 'gserver/tests/Sequence/tour_dict_phrase.dict'
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dict_file = dict()
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for line_count, line in enumerate(open(dict_path, "r")):
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dict_file[line.strip()] = line_count
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define_py_data_sources2(
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train_list='gserver/tests/Sequence/train.list',
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test_list=None,
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module='sequenceGen',
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obj='process',
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args={"dict_file": dict_file})
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settings(batch_size=5)
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######################## network configure ################################
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dict_dim = len(open(dict_path, 'r').readlines())
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word_dim = 128
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hidden_dim = 128
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label_dim = 3
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# This config is designed to be equivalent with sequence_recurrent.py
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data = data_layer(name="word", size=dict_dim)
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emb = embedding_layer(
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input=data, size=word_dim, param_attr=ParamAttr(name="emb"))
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def step(y):
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mem = memory(name="rnn_state", size=hidden_dim)
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with mixed_layer(
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name="rnn_state",
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size=hidden_dim,
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bias_attr=False,
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act=SoftmaxActivation()) as out:
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out += identity_projection(input=y)
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out += full_matrix_projection(
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input=mem, param_attr=ParamAttr(name="___recurrent_layer_0__"))
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return out
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recurrent = recurrent_group(name="rnn", step=step, input=emb)
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recurrent_last = last_seq(input=recurrent)
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with mixed_layer(
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size=label_dim, act=SoftmaxActivation(), bias_attr=True) as output:
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output += full_matrix_projection(input=recurrent_last)
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outputs(
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classification_cost(
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input=output, label=data_layer(
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name="label", size=1)))

‎paddle/trainer/tests/test_CompareTwoNets.cpp renamed to ‎paddle/gserver/tests/test_CompareTwoNets.cpp

Lines changed: 7 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -30,8 +30,6 @@ DECLARE_bool(use_gpu);
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DECLARE_string(config);
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DECLARE_string(nics);
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DEFINE_string(config_file_a, "", "config of one network to compare");
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DEFINE_string(config_file_b, "", "config of another network to compare");
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DEFINE_bool(need_high_accuracy,
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false,
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"whether need to run in double accuracy");
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DECLARE_bool(thread_local_rand_use_global_seed);
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DECLARE_int32(seed);
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static const string& config_file_a = "gserver/tests/sequence_recurrent.py";
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static const string& config_file_b =
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"gserver/tests/sequence_recurrent_group.py";
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struct ComData {
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vector<Argument> outArgs;
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vector<ParameterPtr> parameters;
@@ -66,6 +68,7 @@ void calcGradient(ComData& data, const string configFile) {
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DataBatch dataBatch;
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int32_t batchSize = trainer.getConfig().opt_config().batch_size();
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trainer.getDataProvider()->reset();
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trainer.getDataProvider()->setSkipShuffle();
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trainer.getDataProvider()->getNextBatch(batchSize, &dataBatch);
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@@ -167,11 +170,11 @@ void compareGradient(ComData& comDataA, ComData& comDataB) {
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TEST(Trainer, create) {
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ComData dataA;
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calcGradient(dataA, FLAGS_config_file_a);
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calcGradient(dataA, config_file_a);
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LOG(INFO) << "\n\nforwardBackward of Network A is finished\n\n";
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ComData dataB;
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calcGradient(dataB, FLAGS_config_file_b);
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calcGradient(dataB, config_file_b);
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LOG(INFO) << "\n\nforwardBackward of the Network B is finished\n\n";
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compareGradient(dataA, dataB);

‎paddle/trainer/tests/CMakeLists.txt

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@@ -28,14 +28,6 @@ if(WITH_PYTHON)
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${PADDLE_SOURCE_DIR}/paddle/.set_port.sh -p port ${CMAKE_CURRENT_BINARY_DIR}/test_TrainerOnePass
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WORKING_DIRECTORY ${PADDLE_SOURCE_DIR}/paddle/)
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endif()
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################ test_CompareTwoNets ######################
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add_unittest_without_exec(test_CompareTwoNets
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test_CompareTwoNets.cpp)
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add_test(NAME test_CompareTwoNets
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COMMAND ${PADDLE_SOURCE_DIR}/paddle/.set_python_path.sh -d ${PADDLE_SOURCE_DIR}/python/
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${CMAKE_CURRENT_BINARY_DIR}/test_CompareTwoNets
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--config_file_a=trainer/tests/sample_trainer_config_qb_rnn.conf --config_file_b=trainer/tests/sample_trainer_config_rnn.conf
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WORKING_DIRECTORY ${PADDLE_SOURCE_DIR}/paddle/)
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############### test_CompareTwoOpts ###################
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add_unittest_without_exec(test_CompareTwoOpts

‎paddle/trainer/tests/sample_trainer_config_qb_rnn.conf

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