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authorJoe Zhao <ztuowen@gmail.com>2014-04-14 08:14:45 +0800
committerJoe Zhao <ztuowen@gmail.com>2014-04-14 08:14:45 +0800
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+#ifndef _NETWORK_COMPONENT_I_H
+#define _NETWORK_COMPONENT_I_H
+
+
+#include "Vector.h"
+#include "Matrix.h"
+
+#include <iostream>
+#include <stdexcept>
+
+
+namespace TNet {
+
+
+ /**
+ * Basic element of the network,
+ * it is a box with defined inputs and outputs,
+ * and functions to refresh outputs
+ *
+ * it is able to compute tranformation function (forward pass)
+ * and jacobian function (backward pass),
+ * which is to be implemented in descendents
+ */
+ class Component
+ {
+ public:
+ /// Types of the net components
+ typedef enum {
+ UPDATABLE_COMPONENT = 0x0100,
+ BIASED_LINEARITY,
+ SHARED_LINEARITY,
+
+ ACT_FUN = 0x0200,
+ SOFTMAX,
+ SIGMOID,
+ BLOCK_SOFTMAX,
+
+ OTHER = 0x0400,
+ EXPAND,
+ COPY,
+ TRANSPOSE,
+ BLOCK_LINEARITY,
+ WINDOW,
+ BIAS,
+ LOG,
+
+ BLOCK_ARRAY,
+ } ComponentType;
+
+
+ //////////////////////////////////////////////////////////////
+ // Constructor & Destructor
+ public:
+ Component(size_t nInputs, size_t nOutputs, Component *pPred);
+ virtual ~Component();
+
+ //////////////////////////////////////////////////////////////
+ // Interface specification (public)
+ public:
+ /// Get Type Identification of the component
+ virtual ComponentType GetType() const = 0;
+ /// Get Type Label of the component
+ virtual const char* GetName() const = 0;
+ ///
+ virtual bool IsUpdatable() const
+ { return false; }
+ /// Clone the component
+ virtual Component* Clone() const = 0;
+
+ /// Get size of input vectors
+ size_t GetNInputs() const;
+ /// Get size of output vectors
+ size_t GetNOutputs() const;
+
+ /// IO Data getters
+ const Matrix<BaseFloat>& GetInput() const;
+ const Matrix<BaseFloat>& GetOutput() const;
+ const Matrix<BaseFloat>& GetErrorInput() const;
+ const Matrix<BaseFloat>& GetErrorOutput() const;
+
+ /// Set input vector (bind with the preceding NetworkComponent)
+ void SetInput(const Matrix<BaseFloat>& rInput);
+ /// Set error input vector (bind with the following NetworkComponent)
+ void SetErrorInput(const Matrix<BaseFloat>& rErrorInput);
+
+ /// Perform forward pass propagateion Input->Output
+ void Propagate();
+ /// Perform backward pass propagateion ErrorInput->ErrorOutput
+ void Backpropagate();
+
+ /// Reads the component parameters from stream
+ virtual void ReadFromStream(std::istream& rIn) { }
+ /// Writes the components parameters to stream
+ virtual void WriteToStream(std::ostream& rOut) { }
+
+
+ ///////////////////////////////////////////////////////////////
+ // Nonpublic member functions used to update data outputs
+ protected:
+ /// Forward pass transformation (to be implemented by descendents...)
+ virtual void PropagateFnc(const Matrix<BaseFloat>& X, Matrix<BaseFloat>& Y) = 0;
+ /// Backward pass transformation (to be implemented by descendents...)
+ virtual void BackpropagateFnc(const Matrix<BaseFloat>& X, Matrix<BaseFloat>& Y) = 0;
+
+
+ ///////////////////////////////////////////////////////////////
+ // data members
+ protected:
+
+ size_t mNInputs; ///< Size of input vectors
+ size_t mNOutputs; ///< Size of output vectors
+
+ const Matrix<BaseFloat>* mpInput; ///< inputs are NOT OWNED by component
+ const Matrix<BaseFloat>* mpErrorInput;///< inputs are NOT OWNED by component
+
+ Matrix<BaseFloat> mOutput; ///< outputs are OWNED by component
+ Matrix<BaseFloat> mErrorOutput; ///< outputs are OWNED by component
+
+ };
+
+
+ /**
+ * Class UpdatableComponent is a box which has some
+ * parameters adjustable by learning
+ *
+ * you can set the learning rate, lock the params,
+ * and learn from each data observation
+ */
+ class UpdatableComponent : public Component
+ {
+ //////////////////////////////////////////////////////////////
+ // Constructor & Destructor
+ public:
+ UpdatableComponent(size_t nInputs, size_t nOutputs, Component *pPred);
+ virtual ~UpdatableComponent();
+
+
+ //////////////////////////////////////////////////////////////
+ // Interface specification (public)
+ public:
+ ///
+ virtual bool IsUpdatable() const
+ { return true; }
+
+ /// calculate gradient
+ virtual void Gradient() = 0;
+ /// accumulate gradient from other components
+ virtual void AccuGradient(const UpdatableComponent& src, int thr, int thrN) = 0;
+ /// update weights, reset the accumulator
+ virtual void Update(int thr, int thrN) = 0;
+
+ /// Sets the learning rate of gradient descent
+ void LearnRate(BaseFloat rate);
+ /// Gets the learning rate of gradient descent
+ BaseFloat LearnRate() const;
+
+ void Momentum(BaseFloat mmt);
+ BaseFloat Momentum() const ;
+
+ void Weightcost(BaseFloat cost);
+ BaseFloat Weightcost() const;
+
+ void Bunchsize(size_t size);
+ size_t Bunchsize() const;
+
+ protected:
+ BaseFloat mLearningRate;
+ BaseFloat mMomentum;
+ BaseFloat mWeightcost;
+ size_t mBunchsize;
+ };
+
+
+
+
+ //////////////////////////////////////////////////////////////////////////
+ // INLINE FUNCTIONS
+ // Component::
+ inline
+ Component::
+ Component(size_t nInputs, size_t nOutputs, Component *pPred)
+ : mNInputs(nInputs), mNOutputs(nOutputs),
+ mpInput(NULL), mpErrorInput(NULL),
+ mOutput(), mErrorOutput()
+ {
+ /* DOUBLE LINK the Components */
+ if (pPred != NULL) {
+ SetInput(pPred->GetOutput());
+ pPred->SetErrorInput(GetErrorOutput());
+ }
+ }
+
+
+ inline
+ Component::
+ ~Component()
+ {
+ ;
+ }
+
+ inline void
+ Component::
+ Propagate()
+ {
+ //initialize output buffer
+ if(mOutput.Rows() != GetInput().Rows() || mOutput.Cols() != GetNOutputs()) {
+ mOutput.Init(GetInput().Rows(),GetNOutputs());
+ }
+ //do the dimensionality test
+ if(GetNInputs() != GetInput().Cols()) {
+ KALDI_ERR << "Non-matching INPUT dim!!! Network dim: " << GetNInputs()
+ << " Data dim: " << GetInput().Cols();
+ }
+ //run transform
+ PropagateFnc(GetInput(),mOutput);
+
+ }
+
+
+ inline void
+ Component::
+ Backpropagate()
+ {
+ //re-initialize the output buffer
+ if(mErrorOutput.Rows() != GetErrorInput().Rows() || mErrorOutput.Cols() != GetNInputs()) {
+ mErrorOutput.Init(GetErrorInput().Rows(),GetNInputs());
+ }
+
+ //do the dimensionality test
+ assert(GetErrorInput().Cols() == mNOutputs);
+ assert(mErrorOutput.Cols() == mNInputs);
+ assert(mErrorOutput.Rows() == GetErrorInput().Rows());
+
+ //transform
+ BackpropagateFnc(GetErrorInput(),mErrorOutput);
+
+ }
+
+
+ inline void
+ Component::
+ SetInput(const Matrix<BaseFloat>& rInput)
+ {
+ mpInput = &rInput;
+ }
+
+
+ inline void
+ Component::
+ SetErrorInput(const Matrix<BaseFloat>& rErrorInput)
+ {
+ mpErrorInput = &rErrorInput;
+ }
+
+
+ inline const Matrix<BaseFloat>&
+ Component::
+ GetInput() const
+ {
+ if (NULL == mpInput) Error("mpInput is NULL");
+ return *mpInput;
+ }
+
+ inline const Matrix<BaseFloat>&
+ Component::
+ GetOutput() const
+ {
+ return mOutput;
+ }
+
+ inline const Matrix<BaseFloat>&
+ Component::
+ GetErrorInput() const
+ {
+ if (NULL == mpErrorInput) Error("mpErrorInput is NULL");
+ return *mpErrorInput;
+ }
+
+ inline const Matrix<BaseFloat>&
+ Component::
+ GetErrorOutput() const
+ {
+ return mErrorOutput;
+ }
+
+ inline size_t
+ Component::
+ GetNInputs() const
+ {
+ return mNInputs;
+ }
+
+ inline size_t
+ Component::
+ GetNOutputs() const
+ {
+ return mNOutputs;
+ }
+
+
+
+ //////////////////////////////////////////////////////////////////////////
+ // INLINE FUNCTIONS
+ // UpdatableComponent::
+
+ inline
+ UpdatableComponent::
+ UpdatableComponent(size_t nInputs, size_t nOutputs, Component *pPred)
+ : Component(nInputs, nOutputs, pPred),
+ mLearningRate(0.0), mMomentum(0.0), mWeightcost(0.0), mBunchsize(0)
+ {
+ ;
+ }
+
+
+ inline
+ UpdatableComponent::
+ ~UpdatableComponent()
+ {
+ ;
+ }
+
+
+ inline void
+ UpdatableComponent::
+ LearnRate(BaseFloat rate)
+ {
+ mLearningRate = rate;
+ }
+
+ inline BaseFloat
+ UpdatableComponent::
+ LearnRate() const
+ {
+ return mLearningRate;
+ }
+
+
+ inline void
+ UpdatableComponent::
+ Momentum(BaseFloat mmt)
+ {
+ mMomentum = mmt;
+ }
+
+ inline BaseFloat
+ UpdatableComponent::
+ Momentum() const
+ {
+ return mMomentum;
+ }
+
+
+ inline void
+ UpdatableComponent::
+ Weightcost(BaseFloat cost)
+ {
+ mWeightcost = cost;
+ }
+
+ inline BaseFloat
+ UpdatableComponent::
+ Weightcost() const
+ {
+ return mWeightcost;
+ }
+
+
+ inline void
+ UpdatableComponent::
+ Bunchsize(size_t size)
+ {
+ mBunchsize = size;
+ }
+
+ inline size_t
+ UpdatableComponent::
+ Bunchsize() const
+ {
+ return mBunchsize;
+ }
+
+
+} // namespace TNet
+
+
+#endif