public static Tensor Forward(Tensor A, AxisZero dim, int copies, int copies2 = 0)
{
Matrix m = null;
if (dim == AxisZero.horizontal)
{
m = Matrix.Zeros(A.Data.X, copies);
Matrix.MatrixLoop((i, j) =>
{
m[i, j] = A.Data[i, 0];
}, A.Data.X, copies);
}
else if (dim == AxisZero.vertical)
{
m = Matrix.Zeros(copies, A.Data.Y);
Matrix.MatrixLoop((i, j) =>
{
m[i, j] = A.Data[0, j];
}, copies, A.Data.Y);
}
else if (dim == AxisZero.none)
{
m = Matrix.Zeros(copies, copies2);
Matrix.MatrixLoop((i, j) =>
{
m[i, j] = A.Data[0, 0];
}, copies, copies2);
}
if (A.AutoGrad)
{
var Creators = new List <Tensor>()
{
A
};
var Argument = new List <object>()
{
dim
};
return(new Tensor(m,
autoGrad: true,
creators: Creators,
arguments: Argument,
backwardCallback: Backward
));
}
return(new Tensor(m));
}
//Sumatory
public static Matrix Sumatory(Matrix m, AxisZero dimension = AxisZero.none)
{
double[,] output;
if (dimension == AxisZero.none)
{
output = new double[1, 1];
}
else if (dimension == AxisZero.horizontal)
{
output = new double[m.X, 1];
}
else if (dimension == AxisZero.vertical)
{
output = new double[1, m.Y];
}
else
{
throw new ArgumentException("The dimension must be -1, 0 or 1");
}
if (dimension == AxisZero.none)
{
MatrixLoop((i, j) =>
{
output[0, 0] += m.GetValue(i, j);
}, m.X, m.Y);
}
else if (dimension == AxisZero.horizontal)
{
MatrixLoop((i, j) =>
{
output[i, 0] += m.GetValue(i, j);
}, m.X, m.Y);
}
else if (dimension == AxisZero.vertical)
{
MatrixLoop((i, j) =>
{
output[0, j] += m.GetValue(i, j);
}, m.X, m.Y);
}
return(output);
}
public static Tensor Forward(Tensor A, AxisZero dim)
{
if (A.AutoGrad)
{
var Argument = new List <object>()
{
dim, new int[] { A.Data.X, A.Data.Y }
};
var Creators = new List <Tensor>()
{
A
};
return(new Tensor(A.Data.Sumatory(dim),
autoGrad: true,
creators: Creators,
arguments: Argument,
backwardCallback: Backward));
}
return(new Tensor(A.Data.Sumatory(dim)));
}
public Matrix Sumatory(AxisZero dimension = AxisZero.none)
{
return(Sumatory(this, dimension));
}
public static Tensor Sum(this Tensor A, AxisZero dim)
{
return(Summation.Forward(A, dim));
}
public static Tensor Exp(this Tensor A, AxisZero dim, int copies, int copies2 = 0)
{
return(Expand.Forward(A, dim, copies, copies2));
}
