[mlpack-git] master: rollback the apis to follow versioning policy (8ebabdd)

gitdub at mlpack.org gitdub at mlpack.org
Thu Jun 9 12:25:10 EDT 2016


Repository : https://github.com/mlpack/mlpack
On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/4fa39b6ab0baa1428116d0406264b5452e716d06...97402b9098d9d72889aa795923cf8fd67a4d87bf

>---------------------------------------------------------------

commit 8ebabddf829267008c22393820e07dc753d289c7
Author: Keon Kim <kwk236 at gmail.com>
Date:   Fri Jun 10 01:19:56 2016 +0900

    rollback the apis to follow versioning policy


>---------------------------------------------------------------

8ebabddf829267008c22393820e07dc753d289c7
 .../hoeffding_trees/hoeffding_tree_main.cpp        | 40 +++++++++---------
 src/mlpack/methods/lars/lars_main.cpp              | 20 ++++-----
 .../linear_regression/linear_regression_main.cpp   | 18 ++++----
 .../softmax_regression/softmax_regression_main.cpp | 48 +++++++++++-----------
 4 files changed, 63 insertions(+), 63 deletions(-)

diff --git a/src/mlpack/methods/hoeffding_trees/hoeffding_tree_main.cpp b/src/mlpack/methods/hoeffding_trees/hoeffding_tree_main.cpp
index 609bb64..ec95512 100644
--- a/src/mlpack/methods/hoeffding_trees/hoeffding_tree_main.cpp
+++ b/src/mlpack/methods/hoeffding_trees/hoeffding_tree_main.cpp
@@ -37,9 +37,9 @@ PROGRAM_INFO("Hoeffding trees",
     "A test file may be specified with the --test_file (-T) option, and if "
     "performance numbers are desired for that test set, labels may be specified"
     " with the --test_labels_file (-L) option.  Predictions for each test point"
-    " will be stored in the file specified by --output_predictions_file (-p) and "
+    " will be stored in the file specified by --predictions_file (-p) and "
     "probabilities for each predictions will be stored in the file specified by"
-    " the --output_probabilities_file (-P) option.");
+    " the --probabilities_file (-P) option.");
 
 PARAM_STRING("training_file", "Training dataset file.", "t", "");
 PARAM_STRING("labels_file", "Labels for training dataset.", "l", "");
@@ -56,9 +56,9 @@ PARAM_STRING("output_model_file", "File to save trained tree to.", "M", "");
 
 PARAM_STRING("test_file", "File of testing data.", "T", "");
 PARAM_STRING("test_labels_file", "Labels of test data.", "L", "");
-PARAM_STRING("output_predictions_file", "File to output label predictions for"
+PARAM_STRING("predictions_file", "File to output label predictions for"
     "test data into.", "p", "");
-PARAM_STRING("output_probabilities_file", "In addition to predicting labels, "
+PARAM_STRING("probabilities_file", "In addition to predicting labels, "
     "provide prediction probabilities in this file.", "P", "");
 
 PARAM_STRING("numeric_split_strategy", "The splitting strategy to use for "
@@ -90,18 +90,18 @@ int main(int argc, char** argv)
   const string labelsFile = CLI::GetParam<string>("labels_file");
   const string inputModelFile = CLI::GetParam<string>("input_model_file");
   const string testFile = CLI::GetParam<string>("test_file");
-  const string outputPredictionsFile =
-      CLI::GetParam<string>("output_predictions_file");
-  const string outputProbabilitiesFile =
-      CLI::GetParam<string>("output_probabilities_file");
+  const string predictionsFile =
+      CLI::GetParam<string>("predictions_file");
+  const string probabilitiesFile =
+      CLI::GetParam<string>("probabilities_file");
   const string numericSplitStrategy =
       CLI::GetParam<string>("numeric_split_strategy");
 
-  if ((CLI::HasParam("output_predictions_file") ||
-       CLI::HasParam("output_probabilities_file")) &&
+  if ((CLI::HasParam("predictions_file") ||
+       CLI::HasParam("probabilities_file")) &&
        !CLI::HasParam("test_file"))
-    Log::Fatal << "--test_file must be specified if --output_predictions_file or "
-        << "--output_probabilities_file is specified." << endl;
+    Log::Fatal << "--test_file must be specified if --predictions_file or "
+        << "--probabilities_file is specified." << endl;
 
   if (!CLI::HasParam("training_file") && !CLI::HasParam("input_model_file"))
     Log::Fatal << "One of --training_file or --input_model_file must be "
@@ -180,10 +180,10 @@ void PerformActions(const typename TreeType::NumericSplit& numericSplit)
   const string inputModelFile = CLI::GetParam<string>("input_model_file");
   const string outputModelFile = CLI::GetParam<string>("output_model_file");
   const string testFile = CLI::GetParam<string>("test_file");
-  const string outputPredictionsFile =
-      CLI::GetParam<string>("output_predictions_file");
-  const string outputProbabilitiesFile =
-      CLI::GetParam<string>("output_probabilities_file");
+  const string predictionsFile =
+      CLI::GetParam<string>("predictions_file");
+  const string probabilitiesFile =
+      CLI::GetParam<string>("probabilities_file");
   bool batchTraining = CLI::HasParam("batch_mode");
   const size_t passes = (size_t) CLI::GetParam<int>("passes");
   if (passes > 1)
@@ -317,11 +317,11 @@ void PerformActions(const typename TreeType::NumericSplit& numericSplit)
           100.0 << ")." << endl;
     }
 
-    if (CLI::HasParam("output_predictions_file"))
-      data::Save(outputPredictionsFile, predictions);
+    if (CLI::HasParam("predictions_file"))
+      data::Save(predictionsFile, predictions);
 
-    if (CLI::HasParam("output_probabilities_file"))
-      data::Save(outputProbabilitiesFile, probabilities);
+    if (CLI::HasParam("probabilities_file"))
+      data::Save(probabilitiesFile, probabilities);
   }
 
   // Check the accuracy on the training set.
diff --git a/src/mlpack/methods/lars/lars_main.cpp b/src/mlpack/methods/lars/lars_main.cpp
index d053772..d9f0ae8 100644
--- a/src/mlpack/methods/lars/lars_main.cpp
+++ b/src/mlpack/methods/lars/lars_main.cpp
@@ -40,7 +40,7 @@ PROGRAM_INFO("LARS", "An implementation of LARS: Least Angle Regression "
     " can be saved with the --output_model_file, or, if training is not desired"
     " at all, a model can be loaded with --input_model_file.  Any output "
     "predictions from a test file can be saved into the file specified by the "
-    "--output_predictions_file option.");
+    "--output_predictions option.");
 
 PARAM_STRING("input_file", "File containing covariates (X).", "i", "");
 PARAM_STRING("responses_file", "File containing y (responses/observations).",
@@ -51,7 +51,7 @@ PARAM_STRING("output_model_file", "File to save model to.", "M", "");
 
 PARAM_STRING("test_file", "File containing points to regress on (test points).",
     "t", "");
-PARAM_STRING("output_predictions_file", "If --test_file is specified, this "
+PARAM_STRING("output_predictions", "If --test_file is specified, this "
     "file is where the predicted responses will be saved.", "o", "");
 
 PARAM_DOUBLE("lambda1", "Regularization parameter for l1-norm penalty.", "l",
@@ -93,17 +93,17 @@ int main(int argc, char* argv[])
     Log::Fatal << "Both --input_file (-i) and --input_model_file (-m) are "
         << "specified, but only one may be specified!" << endl;
 
-  if (!CLI::HasParam("output_predictions_file") &&
+  if (!CLI::HasParam("output_predictions") &&
       !CLI::HasParam("output_model_file"))
-    Log::Warn << "--output_predictions_file (-o) and --output_model_file (-M) "
+    Log::Warn << "--output_predictions (-o) and --output_model_file (-M) "
         << "are not specified; no results will be saved!" << endl;
 
-  if (CLI::HasParam("output_predictions_file") && !CLI::HasParam("test_file"))
-    Log::Warn << "--output_predictions_file (-o) specified, but --test_file "
+  if (CLI::HasParam("output_predictions") && !CLI::HasParam("test_file"))
+    Log::Warn << "--output_predictions (-o) specified, but --test_file "
         << "(-t) is not; no results will be saved." << endl;
 
-  if (CLI::HasParam("test_file") && !CLI::HasParam("output_predictions_file"))
-    Log::Warn << "--test_file (-t) specified, but --output_predictions_file "
+  if (CLI::HasParam("test_file") && !CLI::HasParam("output_predictions"))
+    Log::Warn << "--test_file (-t) specified, but --output_predictions "
         << "(-o) is not; no results will be saved." << endl;
 
   // Initialize the object.
@@ -163,10 +163,10 @@ int main(int argc, char* argv[])
     lars.Predict(testPoints.t(), predictions, false);
 
     // Save test predictions.  One per line, so, don't transpose on save.
-    if (CLI::HasParam("output_predictions_file"))
+    if (CLI::HasParam("output_predictions"))
     {
       const string outputPredictionsFile =
-        CLI::GetParam<string>("output_predictions_file");
+        CLI::GetParam<string>("output_predictions");
       data::Save(outputPredictionsFile, predictions, true, false);
     }
   }
diff --git a/src/mlpack/methods/linear_regression/linear_regression_main.cpp b/src/mlpack/methods/linear_regression/linear_regression_main.cpp
index d96ee17..1871acf 100644
--- a/src/mlpack/methods/linear_regression/linear_regression_main.cpp
+++ b/src/mlpack/methods/linear_regression/linear_regression_main.cpp
@@ -22,13 +22,13 @@ PROGRAM_INFO("Simple Linear Regression and Prediction",
     " another matrix X' (--test_file):\n\n"
     "   y' = X' * b\n\n"
     "and these predicted responses, y', are saved to a file "
-    "(--output_predictions_file).  This type of regression is related to "
+    "(--output_predictions).  This type of regression is related to "
     "least-angle regression, which mlpack implements with the 'lars' "
     "executable.");
 
 PARAM_STRING("training_file", "File containing training set X (regressors).",
     "t", "");
-PARAM_STRING("training_responses_file", "Optional file containing y "
+PARAM_STRING("training_responses", "Optional file containing y "
     "(responses). If not given, the responses are assumed to be the last row "
     "of the input file.", "r", "");
 
@@ -37,7 +37,7 @@ PARAM_STRING("input_model_file", "File containing existing model (parameters).",
 PARAM_STRING("output_model_file", "File to save trained model to.", "M", "");
 
 PARAM_STRING("test_file", "File containing X' (test regressors).", "T", "");
-PARAM_STRING("output_predictions_file", "If --test_file is specified, this "
+PARAM_STRING("output_predictions", "If --test_file is specified, this "
     "file is where the predicted responses will be saved.", "p", "");
 
 PARAM_DOUBLE("lambda", "Tikhonov regularization for ridge regression.  If 0, "
@@ -56,9 +56,9 @@ int main(int argc, char* argv[])
   const string inputModelFile = CLI::GetParam<string>("input_model_file");
   const string outputModelFile = CLI::GetParam<string>("output_model_file");
   const string outputPredictionsFile =
-    CLI::GetParam<string>("output_predictions_file");
+    CLI::GetParam<string>("output_predictions");
   const string trainingResponsesFile =
-    CLI::GetParam<string>("training_responses_file");
+    CLI::GetParam<string>("training_responses");
   const string testFile = CLI::GetParam<string>("test_file");
   const string trainFile = CLI::GetParam<string>("training_file");
   const double lambda = CLI::GetParam<double>("lambda");
@@ -92,8 +92,8 @@ int main(int argc, char* argv[])
         << "both." << endl;
   }
 
-  if (CLI::HasParam("test_file") && !CLI::HasParam("output_predictions_file"))
-    Log::Warn << "--test_file (-t) specified, but --output_predictions_file "
+  if (CLI::HasParam("test_file") && !CLI::HasParam("output_predictions"))
+    Log::Warn << "--test_file (-t) specified, but --output_predictions "
         << "(-o) is not; no results will be saved." << endl;
 
   // If they specified a model file, we also need a test file or we
@@ -117,7 +117,7 @@ int main(int argc, char* argv[])
     Timer::Stop("load_regressors");
 
     // Are the responses in a separate file?
-    if (!CLI::HasParam("training_responses_file"))
+    if (CLI::HasParam("training_responses"))
     {
       // The initial predictors for y, Nx1.
       responses = trans(regressors.row(regressors.n_rows - 1));
@@ -182,7 +182,7 @@ int main(int argc, char* argv[])
     Timer::Stop("prediction");
 
     // Save predictions.
-    if (CLI::HasParam("output_predictions_file"))
+    if (CLI::HasParam("output_predictions"))
       data::Save(outputPredictionsFile, predictions, true, false);
   }
 }
diff --git a/src/mlpack/methods/softmax_regression/softmax_regression_main.cpp b/src/mlpack/methods/softmax_regression/softmax_regression_main.cpp
index d3865b3..7f211a6 100644
--- a/src/mlpack/methods/softmax_regression/softmax_regression_main.cpp
+++ b/src/mlpack/methods/softmax_regression/softmax_regression_main.cpp
@@ -29,8 +29,8 @@ PROGRAM_INFO("Softmax Regression", "This program performs softmax regression, "
     "\n\n"
     "The program is also able to evaluate a model on test data.  A test dataset"
     " can be specified with the --test_data (-T) option.  Class predictions "
-    "will be saved in the file specified with the --output_predictions_file (-p) "
-    "option.  If labels are specified for the test data, with the --test_labels_file"
+    "will be saved in the file specified with the --predictions_file (-p) "
+    "option.  If labels are specified for the test data, with the --test_labels"
     " (-L) option, then the program will print the accuracy of the predictions "
     "on the given test set and its corresponding labels.");
 
@@ -41,16 +41,16 @@ PARAM_STRING("labels_file", "A file containing labels (0 or 1) for the points "
     "in the training set (y). The labels must order as a row", "l", "");
 
 // Model loading/saving.
-PARAM_STRING("input_model_file_file", "File containing existing model (parameters).",
+PARAM_STRING("input_model_file", "File containing existing model (parameters).",
     "m", "");
-PARAM_STRING("output_model_file_file", "File to save trained softmax regression "
+PARAM_STRING("output_model_file", "File to save trained softmax regression "
     "model to.", "M", "");
 
 // Testing.
 PARAM_STRING("test_data", "File containing test dataset.", "T", "");
-PARAM_STRING("output_predictions_file", "File to save predictions for test dataset "
+PARAM_STRING("predictions_file", "File to save predictions for test dataset "
     "into.", "p", "");
-PARAM_STRING("test_labels_file", "File containing test labels.", "L", "");
+PARAM_STRING("test_labels", "File containing test labels.", "L", "");
 
 // Softmax configuration options.
 PARAM_INT("max_iterations", "Maximum number of iterations before termination.",
@@ -73,7 +73,7 @@ size_t CalculateNumberOfClasses(const size_t numClasses,
 // Test the accuracy of the model.
 template<typename Model>
 void TestPredictAcc(const string& testFile,
-                    const string& outputPredictionsFile,
+                    const string& predictionsFile,
                     const string& testLabels,
                     const size_t numClasses,
                     const Model& model);
@@ -97,10 +97,10 @@ int main(int argc, char** argv)
   const std::string inputModelFile =
       CLI::GetParam<std::string>("input_model_file");
   const string outputModelFile = CLI::GetParam<string>("output_model_file");
-  const string testLabelsFile = CLI::GetParam<string>("test_labels_file");
+  const string testLabelsFile = CLI::GetParam<string>("test_labels");
   const int maxIterations = CLI::GetParam<int>("max_iterations");
-  const string outputPredictionsFile =
-      CLI::GetParam<string>("output_predictions_file");
+  const string predictionsFile =
+      CLI::GetParam<string>("predictions_file");
 
   // One of inputFile and modelFile must be specified.
   if (!CLI::HasParam("input_model_file") && !CLI::HasParam("training_file"))
@@ -117,10 +117,10 @@ int main(int argc, char** argv)
 
   // Make sure we have an output file of some sort.
   if (!CLI::HasParam("output_model_file") &&
-      !CLI::HasParam("test_labels_file") &&
-      !CLI::HasParam("output_predictions_file"))
-    Log::Warn << "None of --output_model_file, --test_labels_file, or "
-      << "--output_predictions_file are set; no results from this program "
+      !CLI::HasParam("test_labels") &&
+      !CLI::HasParam("predictions_file"))
+    Log::Warn << "None of --output_model_file, --test_labels, or "
+      << "--predictions_file are set; no results from this program "
       << " will be saved." << endl;
 
 
@@ -131,8 +131,8 @@ int main(int argc, char** argv)
                                             maxIterations);
 
   TestPredictAcc(CLI::GetParam<string>("test_data"),
-                 CLI::GetParam<string>("output_predictions_file"),
-                 CLI::GetParam<string>("test_labels_file"),
+                 CLI::GetParam<string>("predictions_file"),
+                 CLI::GetParam<string>("test_labels"),
                  sm->NumClasses(), *sm);
 
   if (CLI::HasParam("output_model_file"))
@@ -157,7 +157,7 @@ size_t CalculateNumberOfClasses(const size_t numClasses,
 
 template<typename Model>
 void TestPredictAcc(const string& testFile,
-                    const string& outputPredictionsFile,
+                    const string& predictionsFile,
                     const string& testLabelsFile,
                     size_t numClasses,
                     const Model& model)
@@ -165,19 +165,19 @@ void TestPredictAcc(const string& testFile,
   using namespace mlpack;
 
   // If there is no test set, there is nothing to test on.
-  if (testFile.empty() && outputPredictionsFile.empty() && testLabelsFile.empty())
+  if (testFile.empty() && predictionsFile.empty() && testLabelsFile.empty())
     return;
 
   if (!testLabelsFile.empty() && testFile.empty())
   {
-    Log::Warn << "--test_labels_file specified, but --test_file is not specified."
+    Log::Warn << "--test_labels specified, but --test_file is not specified."
         << "  The parameter will be ignored." << endl;
     return;
   }
 
-  if (!outputPredictionsFile.empty() && testFile.empty())
+  if (!predictionsFile.empty() && testFile.empty())
   {
-    Log::Warn << "--output_predictions_file specified, but --test_file is not "
+    Log::Warn << "--predictions_file specified, but --test_file is not "
         << "specified.  The parameter will be ignored." << endl;
     return;
   }
@@ -190,8 +190,8 @@ void TestPredictAcc(const string& testFile,
   model.Predict(testData, predictLabels);
 
   // Save predictions, if desired.
-  if (!outputPredictionsFile.empty())
-    data::Save(outputPredictionsFile, predictLabels);
+  if (!predictionsFile.empty())
+    data::Save(predictionsFile, predictLabels);
 
   // Calculate accuracy, if desired.
   if (!testLabelsFile.empty())
@@ -204,7 +204,7 @@ void TestPredictAcc(const string& testFile,
     if (testData.n_cols != testLabels.n_elem)
     {
       Log::Fatal << "Test data in --test_data has " << testData.n_cols
-          << " points, but labels in --test_labels_file have "
+          << " points, but labels in --test_labels have "
           << testLabels.n_elem << " labels!" << endl;
     }
 




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