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Merge pull request #1783 from stweil/clean

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IntFeatureSpace: Remove unused DeSerialize method
This commit is contained in:
Egor Pugin 2018-07-18 13:31:19 +03:00 committed by GitHub
commit 252661a4d3
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3 changed files with 2 additions and 19 deletions
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13
src/classify/intfeaturespace.cpp
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@ -44,19 +44,6 @@ bool IntFeatureSpace::Serialize(FILE* fp) const {
return true;
}
// DeSerializes the feature space definition from the given file.
// If swap is true, the data is big/little-endian swapped.
// Returns false on error.
bool IntFeatureSpace::DeSerialize(bool swap, FILE* fp) {
if (fread(&x_buckets_, sizeof(x_buckets_), 1, fp) != 1)
return false;
if (fread(&y_buckets_, sizeof(y_buckets_), 1, fp) != 1)
return false;
if (fread(&theta_buckets_, sizeof(theta_buckets_), 1, fp) != 1)
return false;
return true;
}
// Returns an INT_FEATURE_STRUCT corresponding to the given index.
// This is the inverse of the Index member.
INT_FEATURE_STRUCT IntFeatureSpace::PositionFromIndex(int index) const {

5
src/classify/intfeaturespace.h
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@ -47,11 +47,6 @@ class IntFeatureSpace {
// Returns false on error.
bool Serialize(FILE* fp) const;
// DeSerializes the feature space definition from the given file.
// If swap is true, the data is big/little-endian swapped.
// Returns false on error.
bool DeSerialize(bool swap, FILE* fp);
// Returns the total size of the feature space.
int Size() const {
return static_cast<int>(x_buckets_) * y_buckets_ * theta_buckets_;

3
src/training/commontraining.cpp
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@ -201,7 +201,7 @@ void WriteShapeTable(const STRING& file_prefix, const ShapeTable& shape_table) {
}
/**
* Creates a MasterTraininer and loads the training data into it:
* Creates a MasterTrainer and loads the training data into it:
* Initializes feature_defs and IntegerFX.
* Loads the shape_table if shape_table != nullptr.
* Loads initial unicharset from -U command-line option.
@ -211,6 +211,7 @@ void WriteShapeTable(const STRING& file_prefix, const ShapeTable& shape_table) {
* - Loads samples from .tr files in remaining command-line args.
* - Deletes outliers and computes canonical samples.
* - If FLAGS_output_trainer is set, saves the trainer for future use.
* TODO: Who uses that? There is currently no code which reads it.
* Computes canonical and cloud features.
* If shape_table is not nullptr, but failed to load, make a fake flat one,
* as shape clustering was not run.