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new compiler flag for storage order #16

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new compiler flag for storage order #16

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22091d3
Matrix and Vector globally defined
Mar 31, 2020
bb13b3f
remove typedef Matrix and Vector declarations
Mar 31, 2020
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1 change: 0 additions & 1 deletion include/Activation/Identity.h
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Expand Up @@ -20,7 +20,6 @@ namespace MiniDNN
class Identity
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;

public:
// a = activation(z) = z
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1 change: 0 additions & 1 deletion include/Activation/Mish.h
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Expand Up @@ -18,7 +18,6 @@ namespace MiniDNN
class Mish
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;

public:
// Mish(x) = x * tanh(softplus(x))
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1 change: 0 additions & 1 deletion include/Activation/ReLU.h
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Expand Up @@ -16,7 +16,6 @@ namespace MiniDNN
class ReLU
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;

public:
// a = activation(z) = max(z, 0)
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1 change: 0 additions & 1 deletion include/Activation/Sigmoid.h
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Expand Up @@ -16,7 +16,6 @@ namespace MiniDNN
class Sigmoid
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;

public:
// a = activation(z) = 1 / (1 + exp(-z))
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1 change: 0 additions & 1 deletion include/Activation/Softmax.h
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Expand Up @@ -13,7 +13,6 @@ namespace MiniDNN
class Softmax
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::Array<Scalar, 1, Eigen::Dynamic> RowArray;

public:
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1 change: 0 additions & 1 deletion include/Activation/Tanh.h
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Expand Up @@ -16,7 +16,6 @@ namespace MiniDNN
class Tanh
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;

public:
// a = activation(z) = tanh(z)
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1 change: 0 additions & 1 deletion include/Callback.h
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Expand Up @@ -29,7 +29,6 @@ class Network;
class Callback
{
protected:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::RowVectorXi IntegerVector;

public:
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9 changes: 8 additions & 1 deletion include/Config.h
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Expand Up @@ -4,14 +4,21 @@
namespace MiniDNN
{


// Floating-point number type
#ifndef MDNN_SCALAR
typedef double Scalar;
#else
typedef MDNN_SCALAR Scalar;
#endif

#if(MDNN_ROWMAJOR == 1)
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor> Matrix;
#else
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
#endif

typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;


} // namespace MiniDNN

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2 changes: 0 additions & 2 deletions include/Layer.h
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Expand Up @@ -26,8 +26,6 @@ namespace MiniDNN
class Layer
{
protected:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef std::map<std::string, int> MetaInfo;

const int m_in_size; // Size of input units
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2 changes: 0 additions & 2 deletions include/Layer/Convolutional.h
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Expand Up @@ -27,8 +27,6 @@ template <typename Activation>
class Convolutional: public Layer
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef Matrix::ConstAlignedMapType ConstAlignedMapMat;
typedef Vector::ConstAlignedMapType ConstAlignedMapVec;
typedef Vector::AlignedMapType AlignedMapVec;
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2 changes: 0 additions & 2 deletions include/Layer/FullyConnected.h
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Expand Up @@ -23,8 +23,6 @@ template <typename Activation>
class FullyConnected: public Layer
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef Vector::ConstAlignedMapType ConstAlignedMapVec;
typedef Vector::AlignedMapType AlignedMapVec;
typedef std::map<std::string, int> MetaInfo;
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1 change: 0 additions & 1 deletion include/Layer/MaxPooling.h
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Expand Up @@ -25,7 +25,6 @@ template <typename Activation>
class MaxPooling: public Layer
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::MatrixXi IntMatrix;
typedef std::map<std::string, int> MetaInfo;

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10 changes: 9 additions & 1 deletion include/Network.h
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Expand Up @@ -32,7 +32,6 @@ namespace MiniDNN
class Network
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::RowVectorXi IntegerVector;
typedef std::map<std::string, int> MetaInfo;

Expand Down Expand Up @@ -437,10 +436,19 @@ class Network
// We want to force XType and YType to be column-majored
typedef typename Eigen::MatrixBase<DerivedX>::PlainObject PlainObjectX;
typedef typename Eigen::MatrixBase<DerivedY>::PlainObject PlainObjectY;

#if (MDNN_ROWMAJOR == 1 )
typedef Eigen::Matrix<typename PlainObjectX::Scalar, PlainObjectX::RowsAtCompileTime, PlainObjectX::ColsAtCompileTime, Eigen::RowMajor>
XType;
typedef Eigen::Matrix<typename PlainObjectY::Scalar, PlainObjectY::RowsAtCompileTime, PlainObjectY::ColsAtCompileTime, Eigen::RowMajor>
YType;
#else
typedef Eigen::Matrix<typename PlainObjectX::Scalar, PlainObjectX::RowsAtCompileTime, PlainObjectX::ColsAtCompileTime>
XType;
typedef Eigen::Matrix<typename PlainObjectY::Scalar, PlainObjectY::RowsAtCompileTime, PlainObjectY::ColsAtCompileTime>
YType;
#endif

const int nlayer = num_layers();

if (nlayer <= 0)
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1 change: 0 additions & 1 deletion include/Optimizer.h
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Expand Up @@ -20,7 +20,6 @@ namespace MiniDNN
class Optimizer
{
protected:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef Vector::ConstAlignedMapType ConstAlignedMapVec;
typedef Vector::AlignedMapType AlignedMapVec;

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1 change: 0 additions & 1 deletion include/Optimizer/AdaGrad.h
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Expand Up @@ -18,7 +18,6 @@ namespace MiniDNN
class AdaGrad: public Optimizer
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef Eigen::Array<Scalar, Eigen::Dynamic, 1> Array;
typedef Vector::ConstAlignedMapType ConstAlignedMapVec;
typedef Vector::AlignedMapType AlignedMapVec;
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1 change: 0 additions & 1 deletion include/Optimizer/Adam.h
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Expand Up @@ -18,7 +18,6 @@ namespace MiniDNN
class Adam: public Optimizer
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef Eigen::Array<Scalar, Eigen::Dynamic, 1> Array;
typedef Vector::ConstAlignedMapType ConstAlignedMapVec;
typedef Vector::AlignedMapType AlignedMapVec;
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1 change: 0 additions & 1 deletion include/Optimizer/RMSProp.h
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Expand Up @@ -18,7 +18,6 @@ namespace MiniDNN
class RMSProp: public Optimizer
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef Eigen::Array<Scalar, Eigen::Dynamic, 1> Array;
typedef Vector::ConstAlignedMapType ConstAlignedMapVec;
typedef Vector::AlignedMapType AlignedMapVec;
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1 change: 0 additions & 1 deletion include/Optimizer/SGD.h
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Expand Up @@ -17,7 +17,6 @@ namespace MiniDNN
class SGD: public Optimizer
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef Vector::ConstAlignedMapType ConstAlignedMapVec;
typedef Vector::AlignedMapType AlignedMapVec;

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2 changes: 0 additions & 2 deletions include/Output.h
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Expand Up @@ -23,8 +23,6 @@ namespace MiniDNN
class Output
{
protected:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;
typedef Eigen::RowVectorXi IntegerVector;

public:
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2 changes: 0 additions & 2 deletions include/Output/RegressionMSE.h
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Expand Up @@ -17,8 +17,6 @@ namespace MiniDNN
class RegressionMSE: public Output
{
private:
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, 1> Vector;

Matrix m_din; // Derivative of the input of this layer.
// Note that input of this layer is also the output of previous layer
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10 changes: 4 additions & 6 deletions include/Utils/Convolution.h
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Expand Up @@ -131,8 +131,8 @@ inline void moving_product(
const int step,
const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>&
mat1,
Eigen::Map< const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> >& mat2,
Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>& res
Eigen::Map< const Matrix >& mat2,
Matrix& res
)
{
const int row1 = mat1.rows();
Expand All @@ -156,7 +156,6 @@ inline void convolve_valid(
const Scalar* filter_data,
Scalar* dest)
{
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
RMatrix;
typedef Eigen::Map<const Matrix> ConstMapMat;
Expand Down Expand Up @@ -243,8 +242,8 @@ inline void moving_product(
const int padding, const int step,
const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>&
mat1,
const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>& mat2,
Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>& res
const Matrix& mat2,
Matrix & res
)
{
const int row1 = mat1.rows();
Expand Down Expand Up @@ -294,7 +293,6 @@ inline void convolve_full(
const Scalar* src, const int n_obs, const Scalar* filter_data,
Scalar* dest)
{
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> Matrix;
typedef Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
RMatrix;
typedef Eigen::Map<const Matrix> ConstMapMat;
Expand Down