Simplify the testOnePeriod method.

.travis.yml

@@ -50,7 +50,7 @@ before_install:
     fi
   - if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then sudo paddle/scripts/travis/before_install.linux.sh; fi
   - if [[ "$TRAVIS_OS_NAME" == "osx" ]]; then paddle/scripts/travis/before_install.osx.sh; fi
-  - pip install wheel protobuf sphinx breathe recommonmark virtualenv numpy
+  - pip install wheel protobuf sphinx breathe recommonmark virtualenv numpy sphinx_rtd_theme
 script:
   - paddle/scripts/travis/main.sh
 notifications:

paddle/api/test/run_tests.sh

@@ -20,11 +20,7 @@ popd > /dev/null
 
 cd $SCRIPTPATH
 
-if [ ! -f ../../dist/*.whl ] ; then  # Swig not compiled.
-  exit 0
-fi
-
-rm .test_env -rf
+rm -rf .test_env
 virtualenv .test_env
 source .test_env/bin/activate
 

paddle/trainer/Tester.cpp

@@ -17,22 +17,22 @@ limitations under the License. */
 #include <fenv.h>
 #include <stdio.h>
 
-#include <iostream>
 #include <iomanip>
-#include <sstream>
+#include <iostream>
 #include <limits>
+#include <sstream>
 
 #include <google/protobuf/text_format.h>
 
+#include "paddle/utils/GlobalConstants.h"
 #include "paddle/utils/PythonUtil.h"
 #include "paddle/utils/Stat.h"
 #include "paddle/utils/Util.h"
-#include "paddle/utils/GlobalConstants.h"
 
+#include "TesterConfig.h"
+#include "paddle/gserver/gradientmachines/GradientMachineMode.h"
 #include "paddle/gserver/gradientmachines/NeuralNetwork.h"
 #include "paddle/gserver/layers/ValidationLayer.h"
-#include "paddle/gserver/gradientmachines/GradientMachineMode.h"
-#include "TesterConfig.h"
 
 namespace paddle {
 
@@ -66,6 +66,9 @@ Tester::Tester(const std::shared_ptr<TrainerConfigHelper>& config,
 }
 
 void Tester::startTestPeriod() {
+  if (testDataProvider_) {
+    testDataProvider_->reset();
+  }
   testEvaluator_->start();
   testContext_.cost = 0;
   testContext_.numSamples = 0;
@@ -87,27 +90,18 @@ void Tester::testOneDataBatch(const DataBatch& dataBatch,
 void Tester::testOnePeriod() {
   DataBatch dataBatch;
   int64_t batchSize = config_->getOptConfig().batch_size();
-
-  int batches = std::numeric_limits<int>::max();
-
   std::vector<Argument> outArgs;
-
   startTestPeriod();
-  for (int i = 0; i < batches; ++i) {
-    int num = testDataProvider_->getNextBatch(batchSize, &dataBatch);
-    if (num == 0) {
-      testDataProvider_->reset();
-      if (intconfig_->prevBatchState) {
-        gradientMachine_->resetState();
-      }
-      break;
-    }
+  while (testDataProvider_->getNextBatch(batchSize, &dataBatch) != 0) {
     testOneDataBatch(dataBatch, &outArgs);
   }
   finishTestPeriod();
 }
 
 void Tester::finishTestPeriod() {
+  if (intconfig_->prevBatchState) {
+    gradientMachine_->resetState();
+  }
   testEvaluator_->finish();
   CHECK_GT(testContext_.numSamples, 0)
       << "There is no samples in your test batch. Possibly "

paddle/trainer/Trainer.cpp

@@ -17,36 +17,38 @@ limitations under the License. */
 #include <fenv.h>
 #include <stdio.h>
 
-#include <iostream>
 #include <iomanip>
-#include <sstream>
+#include <iostream>
 #include <limits>
+#include <sstream>
 
 #include <google/protobuf/text_format.h>
 
+#include "paddle/utils/Excepts.h"
+#include "paddle/utils/GlobalConstants.h"
 #include "paddle/utils/PythonUtil.h"
 #include "paddle/utils/Stat.h"
 #include "paddle/utils/Util.h"
-#include "paddle/utils/Excepts.h"
-#include "paddle/utils/GlobalConstants.h"
 
-#include "paddle/gserver/gradientmachines/NeuralNetwork.h"
-#include "paddle/gserver/gradientmachines/GradientMachineMode.h"
-#include "paddle/gserver/layers/ValidationLayer.h"
+#include "RemoteParameterUpdater.h"
 #include "TesterConfig.h"
 #include "ThreadParameterUpdater.h"
-#include "RemoteParameterUpdater.h"
 #include "TrainerConfigHelper.h"
+#include "paddle/gserver/gradientmachines/GradientMachineMode.h"
+#include "paddle/gserver/gradientmachines/NeuralNetwork.h"
+#include "paddle/gserver/layers/ValidationLayer.h"
 
 P_DEFINE_string(config, "", "Trainer config file");
 
-P_DEFINE_int32(test_period, 0,
+P_DEFINE_int32(test_period,
+               0,
                "if equal 0, do test on all test data at the end of "
                "each pass. While if equal non-zero, do test on all test "
                "data every test_period batches");
-P_DEFINE_bool(test_all_data_in_one_period, false,
-               "This option was deprecated, since we will always do "
-               "test on all test set ");
+P_DEFINE_bool(test_all_data_in_one_period,
+              false,
+              "This option was deprecated, since we will always do "
+              "test on all test set ");
 
 P_DEFINE_bool(local, true, "Train in local mode or not");
 
@@ -392,10 +394,6 @@ void Trainer::startTrain() {
     dataProvider_->reset();
   }
 
-  if (this->testDataProvider_) {
-    this->testDataProvider_->reset();
-  }
-
   trainerInternal_.getGradientMachine()->start(*config_, dataProvider_);
 }
 
@@ -630,16 +628,14 @@ void Trainer::test() { tester_->test(); }
 std::unique_ptr<TesterConfig> Trainer::createTesterConfig() {
   TesterConfig* conf = new TesterConfig;
   if (FLAGS_test_period) {
-    LOG(WARNING)
-      << "The meaning of --test_period is changed: "
-      << "if equal 0, do test on all test data at the end of "
-      << "each pass. While if equal non-zero, do test on all test "
-      << "data every test_period batches ";
+    LOG(WARNING) << "The meaning of --test_period is changed: "
+                 << "if equal 0, do test on all test data at the end of "
+                 << "each pass. While if equal non-zero, do test on all test "
+                 << "data every test_period batches ";
   }
   if (FLAGS_test_all_data_in_one_period) {
-    LOG(WARNING)
-      << "--test_all_data_in_one_period was deprecated, since "
-      << "we will always do test on all test set ";
+    LOG(WARNING) << "--test_all_data_in_one_period was deprecated, since "
+                 << "we will always do test on all test set ";
   }
   conf->testPeriod = FLAGS_test_period;
   conf->prevBatchState = FLAGS_prev_batch_state;