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feature importance type in saved model file #3220

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Jul 15, 2020
Merged

feature importance type in saved model file #3220

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f399900
feature importance type in saved model file
guolinke Jul 12, 2020
d77d054
fix nullptr
guolinke Jul 12, 2020
4293ed2
fixed formatting
StrikerRUS Jul 12, 2020
557e9c9
fix python/R
guolinke Jul 13, 2020
613886f
Update src/c_api.cpp
guolinke Jul 13, 2020
09f2545
Apply suggestions from code review
guolinke Jul 13, 2020
4ff47de
fix c_api test
guolinke Jul 13, 2020
a48a00f
Merge branch 'feature-importance-type-cli' of https://github.com/Micr…
guolinke Jul 13, 2020
9d2033d
fix swig
guolinke Jul 13, 2020
28cc2e0
Merge branch 'master' into feature-importance-type-cli
StrikerRUS Jul 13, 2020
4f3803d
minor docs improvements and added defines for importance types
StrikerRUS Jul 13, 2020
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9 changes: 6 additions & 3 deletions R-package/R/lgb.Booster.R
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Original file line number Diff line number Diff line change
Expand Up @@ -424,7 +424,7 @@ Booster <- R6::R6Class(
},

# Save model
save_model = function(filename, num_iteration = NULL) {
save_model = function(filename, num_iteration = NULL, feature_importance_type = 0L) {

# Check if number of iteration is non existent
if (is.null(num_iteration)) {
Expand All @@ -437,6 +437,7 @@ Booster <- R6::R6Class(
, ret = NULL
, private$handle
, as.integer(num_iteration)
, as.integer(feature_importance_type)
, lgb.c_str(filename)
)

Expand All @@ -445,7 +446,7 @@ Booster <- R6::R6Class(
},

# Save model to string
save_model_to_string = function(num_iteration = NULL) {
save_model_to_string = function(num_iteration = NULL, feature_importance_type = 0L) {

# Check if number of iteration is non existent
if (is.null(num_iteration)) {
Expand All @@ -457,12 +458,13 @@ Booster <- R6::R6Class(
"LGBM_BoosterSaveModelToString_R"
, private$handle
, as.integer(num_iteration)
, as.integer(feature_importance_type)
))

},

# Dump model in memory
dump_model = function(num_iteration = NULL) {
dump_model = function(num_iteration = NULL, feature_importance_type = 0L) {

# Check if number of iteration is non existent
if (is.null(num_iteration)) {
Expand All @@ -474,6 +476,7 @@ Booster <- R6::R6Class(
"LGBM_BoosterDumpModel_R"
, private$handle
, as.integer(num_iteration)
, as.integer(feature_importance_type)
)

},
Expand Down
15 changes: 9 additions & 6 deletions R-package/src/lightgbm_R.cpp
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Expand Up @@ -632,37 +632,40 @@ LGBM_SE LGBM_BoosterPredictForMat_R(LGBM_SE handle,

LGBM_SE LGBM_BoosterSaveModel_R(LGBM_SE handle,
LGBM_SE num_iteration,
LGBM_SE feature_importance_type,
LGBM_SE filename,
LGBM_SE call_state) {
R_API_BEGIN();
CHECK_CALL(LGBM_BoosterSaveModel(R_GET_PTR(handle), 0, R_AS_INT(num_iteration), R_CHAR_PTR(filename)));
CHECK_CALL(LGBM_BoosterSaveModel(R_GET_PTR(handle), 0, R_AS_INT(num_iteration), R_AS_INT(feature_importance_type), R_CHAR_PTR(filename)));
R_API_END();
}

LGBM_SE LGBM_BoosterSaveModelToString_R(LGBM_SE handle,
LGBM_SE num_iteration,
LGBM_SE feature_importance_type,
LGBM_SE buffer_len,
LGBM_SE actual_len,
LGBM_SE out_str,
LGBM_SE call_state) {
R_API_BEGIN();
int64_t out_len = 0;
std::vector<char> inner_char_buf(R_AS_INT(buffer_len));
CHECK_CALL(LGBM_BoosterSaveModelToString(R_GET_PTR(handle), 0, R_AS_INT(num_iteration), R_AS_INT(buffer_len), &out_len, inner_char_buf.data()));
CHECK_CALL(LGBM_BoosterSaveModelToString(R_GET_PTR(handle), 0, R_AS_INT(num_iteration), R_AS_INT(feature_importance_type), R_AS_INT(buffer_len), &out_len, inner_char_buf.data()));
EncodeChar(out_str, inner_char_buf.data(), buffer_len, actual_len, static_cast<size_t>(out_len));
R_API_END();
}

LGBM_SE LGBM_BoosterDumpModel_R(LGBM_SE handle,
LGBM_SE num_iteration,
LGBM_SE feature_importance_type,
LGBM_SE buffer_len,
LGBM_SE actual_len,
LGBM_SE out_str,
LGBM_SE call_state) {
R_API_BEGIN();
int64_t out_len = 0;
std::vector<char> inner_char_buf(R_AS_INT(buffer_len));
CHECK_CALL(LGBM_BoosterDumpModel(R_GET_PTR(handle), 0, R_AS_INT(num_iteration), R_AS_INT(buffer_len), &out_len, inner_char_buf.data()));
CHECK_CALL(LGBM_BoosterDumpModel(R_GET_PTR(handle), 0, R_AS_INT(num_iteration), R_AS_INT(feature_importance_type), R_AS_INT(buffer_len), &out_len, inner_char_buf.data()));
EncodeChar(out_str, inner_char_buf.data(), buffer_len, actual_len, static_cast<size_t>(out_len));
R_API_END();
}
Expand Down Expand Up @@ -707,9 +710,9 @@ static const R_CallMethodDef CallEntries[] = {
{"LGBM_BoosterCalcNumPredict_R" , (DL_FUNC) &LGBM_BoosterCalcNumPredict_R , 8},
{"LGBM_BoosterPredictForCSC_R" , (DL_FUNC) &LGBM_BoosterPredictForCSC_R , 14},
{"LGBM_BoosterPredictForMat_R" , (DL_FUNC) &LGBM_BoosterPredictForMat_R , 11},
{"LGBM_BoosterSaveModel_R" , (DL_FUNC) &LGBM_BoosterSaveModel_R , 4},
{"LGBM_BoosterSaveModelToString_R" , (DL_FUNC) &LGBM_BoosterSaveModelToString_R , 6},
{"LGBM_BoosterDumpModel_R" , (DL_FUNC) &LGBM_BoosterDumpModel_R , 6},
{"LGBM_BoosterSaveModel_R" , (DL_FUNC) &LGBM_BoosterSaveModel_R , 5},
{"LGBM_BoosterSaveModelToString_R" , (DL_FUNC) &LGBM_BoosterSaveModelToString_R , 7},
{"LGBM_BoosterDumpModel_R" , (DL_FUNC) &LGBM_BoosterDumpModel_R , 7},
{NULL, NULL, 0}
};

Expand Down
3 changes: 3 additions & 0 deletions R-package/src/lightgbm_R.h
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Expand Up @@ -590,6 +590,7 @@ LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterPredictForMat_R(
LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterSaveModel_R(
LGBM_SE handle,
LGBM_SE num_iteration,
LGBM_SE feature_importance_type,
LGBM_SE filename,
LGBM_SE call_state
);
Expand All @@ -604,6 +605,7 @@ LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterSaveModel_R(
LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterSaveModelToString_R(
LGBM_SE handle,
LGBM_SE num_iteration,
LGBM_SE feature_importance_type,
LGBM_SE buffer_len,
LGBM_SE actual_len,
LGBM_SE out_str,
Expand All @@ -620,6 +622,7 @@ LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterSaveModelToString_R(
LIGHTGBM_C_EXPORT LGBM_SE LGBM_BoosterDumpModel_R(
LGBM_SE handle,
LGBM_SE num_iteration,
LGBM_SE feature_importance_type,
LGBM_SE buffer_len,
LGBM_SE actual_len,
LGBM_SE out_str,
Expand Down
6 changes: 6 additions & 0 deletions docs/Parameters.rst
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Expand Up @@ -574,6 +574,12 @@ Learning Control Parameters

- **Note**: can be used only in CLI version

- ``saved_feature_importance_type`` :raw-html:`<a id="saved_feature_importance_type" title="Permalink to this parameter" href="#saved_feature_importance_type">&#x1F517;&#xFE0E;</a>`, default = ``0``, type = int

- the feature importance type in the saved model file

- ``0``: count-based feature importance; ``1``: gain-based feature importance

- ``snapshot_freq`` :raw-html:`<a id="snapshot_freq" title="Permalink to this parameter" href="#snapshot_freq">&#x1F517;&#xFE0E;</a>`, default = ``-1``, type = int, aliases: ``save_period``

- frequency of saving model file snapshot
Expand Down
10 changes: 6 additions & 4 deletions include/LightGBM/boosting.h
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Expand Up @@ -176,9 +176,10 @@ class LIGHTGBM_EXPORT Boosting {
* \brief Dump model to json format string
* \param start_iteration The model will be saved start from
* \param num_iteration Number of iterations that want to dump, -1 means dump all
* \param feature_importance_type type of feature importance, 0: count, 1: gain
* \return Json format string of model
*/
virtual std::string DumpModel(int start_iteration, int num_iteration) const = 0;
virtual std::string DumpModel(int start_iteration, int num_iteration, int feature_importance_type) const = 0;

/*!
* \brief Translate model to if-else statement
Expand All @@ -199,19 +200,20 @@ class LIGHTGBM_EXPORT Boosting {
* \brief Save model to file
* \param start_iteration The model will be saved start from
* \param num_iterations Number of model that want to save, -1 means save all
* \param is_finish Is training finished or not
* \param feature_importance_type type of feature importance, 0: count, 1:gain
* \param filename Filename that want to save to
* \return true if succeeded
*/
virtual bool SaveModelToFile(int start_iteration, int num_iterations, const char* filename) const = 0;
virtual bool SaveModelToFile(int start_iteration, int num_iterations, int feature_importance_type, const char* filename) const = 0;

/*!
* \brief Save model to string
* \param start_iteration The model will be saved start from
* \param num_iterations Number of model that want to save, -1 means save all
* \param feature_importance_type type of feature importance, 0: count, 1:gain
* \return Non-empty string if succeeded
*/
virtual std::string SaveModelToString(int start_iteration, int num_iterations) const = 0;
virtual std::string SaveModelToString(int start_iteration, int num_iterations, int feature_importance_type) const = 0;

/*!
* \brief Restore from a serialized string
Expand Down
6 changes: 6 additions & 0 deletions include/LightGBM/c_api.h
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Expand Up @@ -996,19 +996,22 @@ LIGHTGBM_C_EXPORT int LGBM_BoosterPredictForMats(BoosterHandle handle,
* \param handle Handle of booster
* \param start_iteration Start index of the iteration that should be saved
* \param num_iteration Index of the iteration that should be saved, <= 0 means save all
* \param feature_importance_type type of feature importance, 0: count, 1:gain
* \param filename The name of the file
* \return 0 when succeed, -1 when failure happens
*/
LIGHTGBM_C_EXPORT int LGBM_BoosterSaveModel(BoosterHandle handle,
int start_iteration,
int num_iteration,
int feature_importance_type,
const char* filename);

/*!
* \brief Save model to string.
* \param handle Handle of booster
* \param start_iteration Start index of the iteration that should be saved
* \param num_iteration Index of the iteration that should be saved, <= 0 means save all
* \param feature_importance_type type of feature importance, 0: count, 1:gain
* \param buffer_len String buffer length, if ``buffer_len < out_len``, you should re-allocate buffer
* \param[out] out_len Actual output length
* \param[out] out_str String of model, should pre-allocate memory
Expand All @@ -1017,6 +1020,7 @@ LIGHTGBM_C_EXPORT int LGBM_BoosterSaveModel(BoosterHandle handle,
LIGHTGBM_C_EXPORT int LGBM_BoosterSaveModelToString(BoosterHandle handle,
int start_iteration,
int num_iteration,
int feature_importance_type,
int64_t buffer_len,
int64_t* out_len,
char* out_str);
Expand All @@ -1026,6 +1030,7 @@ LIGHTGBM_C_EXPORT int LGBM_BoosterSaveModelToString(BoosterHandle handle,
* \param handle Handle of booster
* \param start_iteration Start index of the iteration that should be dumped
* \param num_iteration Index of the iteration that should be dumped, <= 0 means dump all
* \param feature_importance_type type of feature importance, 0: count, 1:gain
* \param buffer_len String buffer length, if ``buffer_len < out_len``, you should re-allocate buffer
* \param[out] out_len Actual output length
* \param[out] out_str JSON format string of model, should pre-allocate memory
Expand All @@ -1034,6 +1039,7 @@ LIGHTGBM_C_EXPORT int LGBM_BoosterSaveModelToString(BoosterHandle handle,
LIGHTGBM_C_EXPORT int LGBM_BoosterDumpModel(BoosterHandle handle,
int start_iteration,
int num_iteration,
int feature_importance_type,
int64_t buffer_len,
int64_t* out_len,
char* out_str);
Expand Down
4 changes: 4 additions & 0 deletions include/LightGBM/config.h
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Expand Up @@ -532,6 +532,10 @@ struct Config {
// desc = **Note**: can be used only in CLI version
std::string output_model = "LightGBM_model.txt";

// desc = the feature importance type in the saved model file
// desc = ``0``: count-based feature importance; ``1``: gain-based feature importance
int saved_feature_importance_type = 0;

// [no-save]
// alias = save_period
// desc = frequency of saving model file snapshot
Expand Down
17 changes: 14 additions & 3 deletions python-package/lightgbm/basic.py
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Expand Up @@ -2600,7 +2600,7 @@ def eval_valid(self, feval=None):
return [item for i in range_(1, self.__num_dataset)
for item in self.__inner_eval(self.name_valid_sets[i - 1], i, feval)]

def save_model(self, filename, num_iteration=None, start_iteration=0):
def save_model(self, filename, num_iteration=None, start_iteration=0, feature_importance_type=0):
"""Save Booster to file.

Parameters
Expand All @@ -2613,6 +2613,8 @@ def save_model(self, filename, num_iteration=None, start_iteration=0):
If <= 0, all iterations are saved.
start_iteration : int, optional (default=0)
Start index of the iteration that should be saved.
feature_importance_type : int, optional (default=0)
0: count-based; 1: gain-based

Returns
-------
Expand All @@ -2625,6 +2627,7 @@ def save_model(self, filename, num_iteration=None, start_iteration=0):
self.handle,
ctypes.c_int(start_iteration),
ctypes.c_int(num_iteration),
ctypes.c_int(feature_importance_type),
c_str(filename)))
_dump_pandas_categorical(self.pandas_categorical, filename)
return self
Expand Down Expand Up @@ -2685,7 +2688,7 @@ def model_from_string(self, model_str, verbose=True):
self.pandas_categorical = _load_pandas_categorical(model_str=model_str)
return self

def model_to_string(self, num_iteration=None, start_iteration=0):
def model_to_string(self, num_iteration=None, start_iteration=0, feature_importance_type=0):
"""Save Booster to string.

Parameters
Expand All @@ -2696,6 +2699,8 @@ def model_to_string(self, num_iteration=None, start_iteration=0):
If <= 0, all iterations are saved.
start_iteration : int, optional (default=0)
Start index of the iteration that should be saved.
feature_importance_type : int, optional (default=0)
0: count-based; 1: gain-based

Returns
-------
Expand All @@ -2712,6 +2717,7 @@ def model_to_string(self, num_iteration=None, start_iteration=0):
self.handle,
ctypes.c_int(start_iteration),
ctypes.c_int(num_iteration),
ctypes.c_int(feature_importance_type),
ctypes.c_int64(buffer_len),
ctypes.byref(tmp_out_len),
ptr_string_buffer))
Expand All @@ -2724,14 +2730,15 @@ def model_to_string(self, num_iteration=None, start_iteration=0):
self.handle,
ctypes.c_int(start_iteration),
ctypes.c_int(num_iteration),
ctypes.c_int(feature_importance_type),
ctypes.c_int64(actual_len),
ctypes.byref(tmp_out_len),
ptr_string_buffer))
ret = string_buffer.value.decode('utf-8')
ret += _dump_pandas_categorical(self.pandas_categorical)
return ret

def dump_model(self, num_iteration=None, start_iteration=0):
def dump_model(self, num_iteration=None, start_iteration=0, feature_importance_type=0):
"""Dump Booster to JSON format.

Parameters
Expand All @@ -2742,6 +2749,8 @@ def dump_model(self, num_iteration=None, start_iteration=0):
If <= 0, all iterations are dumped.
start_iteration : int, optional (default=0)
Start index of the iteration that should be dumped.
feature_importance_type : int, optional (default=0)
0: count-based; 1: gain-based

Returns
-------
Expand All @@ -2758,6 +2767,7 @@ def dump_model(self, num_iteration=None, start_iteration=0):
self.handle,
ctypes.c_int(start_iteration),
ctypes.c_int(num_iteration),
ctypes.c_int(feature_importance_type),
ctypes.c_int64(buffer_len),
ctypes.byref(tmp_out_len),
ptr_string_buffer))
Expand All @@ -2770,6 +2780,7 @@ def dump_model(self, num_iteration=None, start_iteration=0):
self.handle,
ctypes.c_int(start_iteration),
ctypes.c_int(num_iteration),
ctypes.c_int(feature_importance_type),
ctypes.c_int64(actual_len),
ctypes.byref(tmp_out_len),
ptr_string_buffer))
Expand Down
6 changes: 4 additions & 2 deletions src/application/application.cpp
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Expand Up @@ -201,7 +201,8 @@ void Application::InitTrain() {
void Application::Train() {
Log::Info("Started training...");
boosting_->Train(config_.snapshot_freq, config_.output_model);
boosting_->SaveModelToFile(0, -1, config_.output_model.c_str());
boosting_->SaveModelToFile(0, -1, config_.saved_feature_importance_type,
config_.output_model.c_str());
// convert model to if-else statement code
if (config_.convert_model_language == std::string("cpp")) {
boosting_->SaveModelToIfElse(-1, config_.convert_model.c_str());
Expand Down Expand Up @@ -233,7 +234,8 @@ void Application::Predict() {
boosting_->Init(&config_, train_data_.get(), objective_fun_.get(),
Common::ConstPtrInVectorWrapper<Metric>(train_metric_));
boosting_->RefitTree(pred_leaf);
boosting_->SaveModelToFile(0, -1, config_.output_model.c_str());
boosting_->SaveModelToFile(0, -1, config_.saved_feature_importance_type,
config_.output_model.c_str());
Log::Info("Finished RefitTree");
} else {
// create predictor
Expand Down
2 changes: 1 addition & 1 deletion src/boosting/gbdt.cpp
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Expand Up @@ -258,7 +258,7 @@ void GBDT::Train(int snapshot_freq, const std::string& model_output_path) {
if (snapshot_freq > 0
&& (iter + 1) % snapshot_freq == 0) {
std::string snapshot_out = model_output_path + ".snapshot_iter_" + std::to_string(iter + 1);
SaveModelToFile(0, -1, snapshot_out.c_str());
SaveModelToFile(0, -1, config_->saved_feature_importance_type, snapshot_out.c_str());
}
}
}
Expand Down
12 changes: 9 additions & 3 deletions src/boosting/gbdt.h
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Expand Up @@ -249,9 +249,11 @@ class GBDT : public GBDTBase {
* \brief Dump model to json format string
* \param start_iteration The model will be saved start from
* \param num_iteration Number of iterations that want to dump, -1 means dump all
* \param feature_importance_type type of feature importance, 0: count, 1:gain
* \return Json format string of model
*/
std::string DumpModel(int start_iteration, int num_iteration) const override;
std::string DumpModel(int start_iteration, int num_iteration,
int feature_importance_type) const override;

/*!
* \brief Translate model to if-else statement
Expand All @@ -272,18 +274,22 @@ class GBDT : public GBDTBase {
* \brief Save model to file
* \param start_iteration The model will be saved start from
* \param num_iterations Number of model that want to save, -1 means save all
* \param feature_importance_type type of feature importance, 0: count, 1:gain
* \param filename Filename that want to save to
* \return is_finish Is training finished or not
*/
bool SaveModelToFile(int start_iteration, int num_iterations, const char* filename) const override;
bool SaveModelToFile(int start_iteration, int num_iterations,
int feature_importance_type,
const char* filename) const override;

/*!
* \brief Save model to string
* \param start_iteration The model will be saved start from
* \param num_iterations Number of model that want to save, -1 means save all
* \param feature_importance_type type of feature importance, 0: count, 1:gain
* \return Non-empty string if succeeded
*/
std::string SaveModelToString(int start_iteration, int num_iterations) const override;
std::string SaveModelToString(int start_iteration, int num_iterations, int feature_importance_type) const override;

/*!
* \brief Restore from a serialized buffer
Expand Down
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