Removed unused GradientMachine::create

paddle/gserver/gradientmachines/GradientMachine.cpp

@@ -60,55 +60,6 @@ GradientMachine* GradientMachine::create(
   return nullptr;
 }
 
-GradientMachine* GradientMachine::create(const std::string& modelFile,
-                                         DataConfig* dataConfig) {
-  std::ifstream is(modelFile);
-  CHECK(is) << "Fail to open " << modelFile;
-  return create(is, dataConfig);
-}
-
-GradientMachine* GradientMachine::create(std::istream& is,
-                                         DataConfig* dataConfig) {
-  TrainerConfig trainerConfig;
-  GradientMachine* ret = create(is, &trainerConfig);
-  if (dataConfig && trainerConfig.has_data_config()) {
-    *dataConfig = trainerConfig.data_config();
-  }
-  return ret;
-}
-
-GradientMachine* GradientMachine::create(const std::string& modelFile,
-                                         TrainerConfig* trainerConfig) {
-  std::ifstream is(modelFile);
-  CHECK(is) << "Fail to open " << modelFile;
-  return create(is, trainerConfig);
-}
-
-GradientMachine* GradientMachine::create(std::istream& is,
-                                         TrainerConfig* trainerConfig) {
-  TrainerConfig trainerConfigTemp;
-  int64_t size;
-  CHECK(is.read((char*)&size, sizeof(size))) << "Fail to read ";
-  std::string buf;
-  buf.resize(size);
-  CHECK(is.read(&buf[0], size)) << "Fail to read ";
-  CHECK(trainerConfigTemp.ParseFromString(buf)) << "Fail to parse config";
-  std::unique_ptr<GradientMachine> machine(
-      create(trainerConfigTemp.model_config()));
-  std::vector<ParameterPtr>& parameters = machine->getParameters();
-  for (auto& para : parameters) {
-    para->load(is);
-  }
-
-  machine->onLoadParameter();
-
-  if (trainerConfig) {
-    *trainerConfig = trainerConfigTemp;
-  }
-
-  return machine.release();
-}
-
 void GradientMachine::saveParameters(const std::string& dir) const {
   LOG(INFO) << "Saving parameters to " << dir;
 

paddle/gserver/gradientmachines/GradientMachine.h

@@ -89,39 +89,6 @@ public:
           std::vector<ParameterType>{
               PARAMETER_VALUE, PARAMETER_GRADIENT, PARAMETER_MOMENTUM});
 
-  /**
-   * Create a gradient machine from the merged model file.
-   * The merged model file can be generated using tools/merge_model
-   * If dataConfig is not null, it will be filled with the DataConfig
-   * from the TrainerConfig
-   */
-  static GradientMachine* create(const std::string& modelFile,
-                                 DataConfig* dataConfig);
-
-  /**
-   * Create a gradient machine from a stream which contains the merged
-   * model file. The merged model file can be generated using tools/merge_model
-   * If dataConfig is not null, it will be filled with the DataConfig
-   * from the TrainerConfig
-   */
-  static GradientMachine* create(std::istream& is, DataConfig* dataConfig);
-
-  /**
-   * Create a gradient machine from the merged model file.
-   * The merged model file can be generated using tools/merge_model
-   * If trainerConfig is not null, it will be filled with the TrainerConfig
-   */
-  static GradientMachine* create(const std::string& modelFile,
-                                 TrainerConfig* trainerConfig);
-
-  /**
-   * Create a gradient machine from a stream which contains the merged
-   * model file. The merged model file can be generated using tools/merge_model
-   * If trainerConfig is not null, it will be filled with the TrainerConfig
-   */
-  static GradientMachine* create(std::istream& is,
-                                 TrainerConfig* trainerConfig);
-
   virtual ~GradientMachine() {}
 
   /**

paddle/trainer/tests/CMakeLists.txt

-################# test_Prediction ######################
-add_unittest_without_exec(test_Prediction
-    test_Prediction.cpp)
-add_test(NAME test_Prediction
-  COMMAND ${PROJ_ROOT}/paddle/.set_python_path.sh -d ${PROJ_ROOT}/python
-        ${CMAKE_CURRENT_BINARY_DIR}/test_Prediction --merger=${CMAKE_CURRENT_BINARY_DIR}/../paddle_merge_model
-    WORKING_DIRECTORY ${PROJ_ROOT}/paddle/)
-
 ################# test_Compare ############################
 add_unittest_without_exec(test_Compare
     test_Compare.cpp)

paddle/trainer/tests/test_Prediction.cpp

-/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
-
-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. */
-
-#include <paddle/utils/PythonUtil.h>
-
-#include "paddle/trainer/Trainer.h"
-
-#include <gtest/gtest.h>
-
-DECLARE_string(config);
-DECLARE_string(config_args);
-DEFINE_string(merger,
-              "./paddle_merge_model",
-              "path to paddle_merge_model binary");
-
-using namespace paddle;  // NOLINT
-using namespace std;     // NOLINT
-
-static const string& configFile = "trainer/tests/sample_trainer_config.conf";
-static const string& mergedModelFile = "./test_model_file";
-static const string& modelDir = "./test_model_dir";
-
-void checkBuffer(real* vec1, real* vec2, size_t len) {
-  for (size_t i = 0; i < len; i++) {
-    EXPECT_EQ(vec1[i], vec2[i]) << "vec1:" << vec1[i] << " vec2:" << vec2[i];
-  }
-}
-
-void checkParameters(vector<ParameterPtr> A, vector<ParameterPtr> B) {
-  CHECK_EQ(B.size(), A.size()) << "parameter size not equal";
-  for (size_t i = 0; i < A.size(); i++) {
-    auto vec1 = A[i]->getBuf(PARAMETER_VALUE);
-    auto vec2 = B[i]->getBuf(PARAMETER_VALUE);
-    CHECK_EQ(vec1->useGpu_, vec2->useGpu_) << "use gpu not equal";
-    CHECK_EQ(vec1->getSize(), vec2->getSize()) << "size not equal";
-
-    if (vec1->useGpu_ == false) {
-      checkBuffer(vec1->getData(), vec2->getData(), vec1->getSize());
-    } else {
-      VectorPtr cpuVec1 = Vector::create(vec1->getSize(), false);
-      VectorPtr cpuVec2 = Vector::create(vec2->getSize(), false);
-      cpuVec1->copyFrom(*vec1, HPPL_STREAM_DEFAULT);
-      cpuVec2->copyFrom(*vec2, HPPL_STREAM_DEFAULT);
-      hl_stream_synchronize(HPPL_STREAM_DEFAULT);
-      checkBuffer(cpuVec1->getData(), cpuVec2->getData(), cpuVec1->getSize());
-    }
-  }
-}
-
-TEST(GradientMachine, create) {
-#ifdef PADDLE_ONLY_CPU
-  FLAGS_use_gpu = false;
-#endif
-  mkDir(modelDir.c_str());
-  FLAGS_config = configFile;
-  FLAGS_config_args = "with_cost=False";
-  auto config = TrainerConfigHelper::createFromFlagConfig();
-
-  // save model to directory
-  unique_ptr<GradientMachine> gradientMachine1(
-      GradientMachine::create(*config));
-  gradientMachine1->saveParameters(modelDir);
-  Trainer trainer;
-  trainer.init(config);
-  ParameterUtil* paramUtil = trainer.getParameterUtilPtr();
-  if (paramUtil != NULL) {
-    paramUtil->saveConfigWithPath(modelDir);
-  }
-
-  // create a different GradientMachine
-  unique_ptr<GradientMachine> gradientMachine2(
-      GradientMachine::create(*config));
-  gradientMachine2->randParameters();
-
-  // merge config and model to one file
-  string cmd = FLAGS_merger + " --model_dir=" + modelDir +
-               " --config_args=with_cost=False" + " --model_file=" +
-               mergedModelFile;
-  LOG(INFO) << cmd;
-  int ret = system(cmd.c_str());
-  EXPECT_EQ(0, ret);
-  if (ret) {
-    return;
-  }
-
-  // create GradientMachine from the merged model
-  DataConfig dataConfig;
-  unique_ptr<GradientMachine> gradientMachine3(
-      GradientMachine::create(mergedModelFile, &dataConfig));
-  CHECK(gradientMachine3);
-  EXPECT_EQ(dataConfig.type(), "simple");
-  EXPECT_EQ(dataConfig.feat_dim(), 3);
-
-  // compare the parameters of GradientMachine and GradientMachine3
-  std::vector<ParameterPtr> paraMachine1 = gradientMachine1->getParameters();
-  std::vector<ParameterPtr> paraMachine3 = gradientMachine3->getParameters();
-  checkParameters(paraMachine1, paraMachine3);
-
-  // Test that the GradientMachine created from the merged model
-  // is same as the orginnal one.
-  vector<Argument> inArgs(1);
-  vector<Argument> outArgs;
-
-  int inputDim = 3;
-  int numSamples = 2;
-  CpuMatrix cpuInput(numSamples, inputDim);
-  for (int i = 0; i < numSamples; ++i) {
-    for (int j = 0; j < inputDim; ++j) {
-      cpuInput.getData()[i * inputDim + j] =
-          rand() / (real)RAND_MAX;  // NOLINT TODO(yuyang): use rand_r
-    }
-  }
-  MatrixPtr input = Matrix::create(numSamples,
-                                   inputDim,
-                                   /* trans */ false,
-                                   FLAGS_use_gpu);
-  input->copyFrom(cpuInput);
-  inArgs[0].value = input;
-  gradientMachine1->forward(inArgs, &outArgs, PASS_TEST);
-  EXPECT_EQ((size_t)1, outArgs.size());
-
-  vector<Argument> outArgs2;
-  gradientMachine2->forward(inArgs, &outArgs2, PASS_TEST);
-  CpuMatrix out1(outArgs[0].value->getHeight(), outArgs[0].value->getWidth());
-  CpuMatrix out2(outArgs2[0].value->getHeight(), outArgs2[0].value->getWidth());
-  out1.copyFrom(*outArgs[0].value);
-  out2.copyFrom(*outArgs2[0].value);
-  for (size_t i = 0; i < out1.getHeight() * out1.getWidth(); i++) {
-    EXPECT_NE(out1.getData()[i], out2.getData()[i]);
-  }
-
-  gradientMachine3->forward(inArgs, &outArgs2, PASS_TEST);
-  out2.copyFrom(*outArgs2[0].value);
-  checkBuffer(
-      out1.getData(), out2.getData(), out2.getHeight() * out2.getWidth());
-
-  cmd = " rm -rf " + modelDir + "/*";
-  LOG(INFO) << "cmd " << cmd;
-  ret = system(cmd.c_str());
-  EXPECT_EQ(0, ret);
-  if (ret) {
-    return;
-  }
-
-  cmd = " rm -rf " + mergedModelFile;
-  LOG(INFO) << "cmd " << cmd;
-  ret = system(cmd.c_str());
-  EXPECT_EQ(0, ret);
-  if (ret) {
-    return;
-  }
-
-  // clean up
-  rmDir(modelDir.c_str());
-  remove(mergedModelFile.c_str());
-}
-
-int main(int argc, char** argv) {
-  initMain(argc, argv);
-  initPython(argc, argv);
-  testing::InitGoogleTest(&argc, argv);
-  return RUN_ALL_TESTS();
-}