public IMatrix Execute(IMatrix error, ITrainingContext context, bool calculateOutput, INeuralNetworkUpdateAccumulator updateAccumulator)
{
var matrixList = error.AsIndexable().Columns.Select(v => v.ToArray()).ToList();
var newMatrixList = new List <IMatrix>();
Tuple <int, int> newIndex;
for (var i = 0; i < matrixList.Count; i++)
{
var matrix = matrixList[i];
var table = _indexPosList[i];
newMatrixList.Add(_lap.Create(_rows, _columns, (x, y) => {
if (table.TryGetValue(Tuple.Create(x, y), out newIndex))
{
var newIndex2 = newIndex.Item1 * _newRows + newIndex.Item2;
return(matrix[newIndex2]);
}
return(0f);
}));
}
using (var tensor = _lap.CreateTensor(newMatrixList)) {
var ret = tensor.ConvertToMatrix();
foreach (var item in newMatrixList)
{
item.Dispose();
}
return(ret);
}
}
public I3DTensor ConvertToTensor(IMatrix matrix)
{
var sliceList = new List <IMatrix>();
for (int i = 0, len = matrix.ColumnCount; i < len; i++)
{
using (var vector = matrix.Column(i)) {
var parts = vector.Split(_inputWidth);
//var sliceMatrix = _lap.Create(parts).Transpose();
var sliceMatrix = _lap.Create(parts);
sliceList.Add(sliceMatrix);
foreach (var part in parts)
{
part.Dispose();
}
}
}
var ret = _lap.CreateTensor(sliceList);
foreach (var slice in sliceList)
{
slice.Dispose();
}
return(ret);
}
public I3DTensor ExecuteToTensor(I3DTensor tensor)
{
using (var output = ExecuteToMatrix(tensor)) {
// convert the matrix to a tensor
var sliceList = new List <IMatrix>();
for (int i = 0, len = output.ColumnCount; i < len; i++)
{
using (var vector = output.Column(i)) {
var parts = vector.Split(tensor.ColumnCount);
var sliceMatrix = _lap.Create(parts);
sliceList.Add(sliceMatrix);
foreach (var part in parts)
{
part.Dispose();
}
}
}
var ret = _lap.CreateTensor(sliceList);
foreach (var slice in sliceList)
{
slice.Dispose();
}
return(ret);
}
}
/// <summary>
/// Converts the volume to a tensor
/// </summary>
/// <param name="lap">The linear algebra provider</param>
public I3DTensor AsTensor(ILinearAlgebraProvider lap)
{
var matrixList = Layers.Select(l => l.AsMatrix(lap)).ToList();
var ret = lap.CreateTensor(matrixList);
foreach (var item in matrixList)
{
item.Dispose();
}
return(ret);
}
