Commit 2a8d38c5 authored by Qiwei Ye's avatar Qiwei Ye
Browse files

Merge branches 'master' and 'master' of https://github.com/Microsoft/LightGBM

parents 351b3d7e ed958eb2
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......@@ -77,7 +77,7 @@ Linkers::~Linkers() {
}
void Linkers::ParseMachineList(const char * filename) {
TextReader<size_t> machine_list_reader(filename);
TextReader<size_t> machine_list_reader(filename, false);
machine_list_reader.ReadAllLines();
if (machine_list_reader.Lines().size() <= 0) {
Log::Fatal("Machine list file:%s doesn't exist", filename);
......
......@@ -9,7 +9,7 @@
namespace LightGBM {
// static member defination
// static member definition
int Network::num_machines_;
int Network::rank_;
Linkers* Network::linkers_;
......@@ -141,7 +141,7 @@ void Network::ReduceScatter(char* input, int input_size, int* block_start, int*
// send local data to neighbor first
linkers_->Send(recursive_halving_map_.neighbor, input, input_size);
} else if (recursive_halving_map_.type == RecursiveHalvingNodeType::GroupLeader) {
// recieve neighbor data first
// receive neighbor data first
int need_recv_cnt = input_size;
linkers_->Recv(recursive_halving_map_.neighbor, output, need_recv_cnt);
// reduce
......
......@@ -155,7 +155,7 @@ public:
pAdapter = pAdapter->Next;
}
} else {
Log::Error("GetAdaptersinfo error: code %d ", dwRetVal);
Log::Fatal("GetAdaptersinfo error: code %d ", dwRetVal);
}
if (pAdapterInfo)
FREE(pAdapterInfo);
......
......@@ -8,13 +8,13 @@
namespace LightGBM {
/*!
* \brief Objective funtion for binary classification
* \brief Objective function for binary classification
*/
class BinaryLogloss: public ObjectiveFunction {
public:
explicit BinaryLogloss(const ObjectiveConfig& config) {
is_unbalance_ = config.is_unbalance;
sigmoid_ = static_cast<score_t>(config.sigmoid);
sigmoid_ = static_cast<float>(config.sigmoid);
if (sigmoid_ <= 0.0) {
Log::Fatal("Sigmoid parameter %f :should greater than zero", sigmoid_);
}
......@@ -47,8 +47,8 @@ public:
label_weights_[1] = 1.0f;
// if using unbalance, change the labels weight
if (is_unbalance_) {
label_weights_[1] = 1.0f / cnt_positive;
label_weights_[0] = 1.0f / cnt_negative;
label_weights_[1] = 1.0f;
label_weights_[0] = static_cast<float>(cnt_positive) / cnt_negative;
}
}
......@@ -80,7 +80,7 @@ public:
}
}
double GetSigmoid() const override {
float GetSigmoid() const override {
return sigmoid_;
}
......@@ -92,11 +92,11 @@ private:
/*! \brief True if using unbalance training */
bool is_unbalance_;
/*! \brief Sigmoid parameter */
score_t sigmoid_;
float sigmoid_;
/*! \brief Values for positive and negative labels */
int label_val_[2];
/*! \brief Weights for positive and negative labels */
score_t label_weights_[2];
float label_weights_[2];
/*! \brief Weights for data */
const float* weights_;
};
......
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......@@ -77,9 +77,9 @@ private:
int* block_start_;
/*! \brief Block size for reduce scatter */
int* block_len_;
/*! \brief Write positions for feature histgrams */
/*! \brief Write positions for feature histograms */
int* buffer_write_start_pos_;
/*! \brief Read positions for local feature histgrams */
/*! \brief Read positions for local feature histograms */
int* buffer_read_start_pos_;
/*! \brief Size for reduce scatter */
int reduce_scatter_size_;
......
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