PLearn 0.1
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Go to the source code of this file.
Classes | |
class | PLearn::SparseIncrementalAffineTransformVariable |
Affine transformation of a vector variable, with weights that are sparse and incrementally added Should work for both column and row vectors: result vector will be of same kind (row or col) First row of transformation matrix contains bias b, following rows contain linear-transformation T Will compute b + x.T. More... | |
class | PLearn::DiffTemplate< ObjectType, SparseIncrementalAffineTransformVariable > |
class | PLearn::TypeTraits< SparseIncrementalAffineTransformVariable > |
Namespaces | |
namespace | PLearn |
< for swap | |
Functions | |
Object * | PLearn::toObjectPtr (const SparseIncrementalAffineTransformVariable &o) |
PStream & | PLearn::operator>> (PStream &in, SparseIncrementalAffineTransformVariable &o) |
PStream & | PLearn::operator>> (PStream &in, SparseIncrementalAffineTransformVariable *&o) |
PStream & | PLearn::operator<< (PStream &out, const SparseIncrementalAffineTransformVariable &o) |
PStream & | PLearn::operator>> (PStream &in, PP< SparseIncrementalAffineTransformVariable > &o) |
template<class ObjectType > | |
int | PLearn::diff (const string &refer, const string &other, const Option< ObjectType, SparseIncrementalAffineTransformVariable > *opt, PLearnDiff *diffs) |
Var | PLearn::sparse_incremental_affine_transform (Var vec, Var transformation, real the_running_average_prop=0.01, real the_start_grad_prop=1) |
first row of transformation is the bias. |