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ConvNet
1.0
A GPU-based C++ implementation of Convolutional Neural Nets
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Implmenets LBFGS optimization. More...
#include <optimizer.h>
Public Member Functions | |
| LBFGSOptimizer (const config::Optimizer &optimizer_config) | |
| virtual void | AllocateMemory (const int rows, const int cols) |
| virtual void | Optimize (Matrix &gradient, Matrix ¶meter) |
| virtual void | LoadParameters (hid_t file, const string &prefix) |
| virtual void | SaveParameters (hid_t file, const string &prefix) |
| virtual bool | IsAllocated () |
Public Member Functions inherited from Optimizer | |
| Optimizer (const config::Optimizer &optimizer_config) | |
| virtual void | ReduceLearningRate (float factor) |
Protected Attributes | |
| Matrix | q_ |
| Matrix | last_q_ |
| Matrix | last_w_ |
| const int | m_ |
| vector< float > | rho_ |
| vector< float > | alpha_ |
| vector< float > | beta_ |
| vector< Matrix > | s_ |
| vector< Matrix > | y_ |
| int | start_ |
Protected Attributes inherited from Optimizer | |
| const config::Optimizer::Decay | epsilon_decay_type_ |
| float | epsilon_ |
| float | minimum_epsilon_ |
| const int | epsilon_decay_timescale_ |
| const int | start_optimization_after_ |
| const float | l2_decay_ |
| const float | weight_norm_limit_ |
| const float | weight_norm_constraint_ |
| int | step_ |
Additional Inherited Members | |
Static Public Member Functions inherited from Optimizer | |
| static Optimizer * | ChooseOptimizer (const config::Optimizer &config) |
Protected Member Functions inherited from Optimizer | |
| float | GetDecayedEpsilon () const |
| void | ApplyConstraints (Matrix ¶meter) |
Implmenets LBFGS optimization.
This class is under construction.
1.8.7