public static Tensor Concat(this Session session, IList <Tensor> xs, int axis)
{
const string ActionName = "concat";
if (axis < 0)
{
throw new ArgumentException(Properties.Resources.E_NegativeAxisIndex, nameof(axis));
}
return(session.RunOperation(
ActionName,
() =>
{
bool calculateGradient = session.CalculateGradients && xs.Any(x => x.CalculateGradient);
Tensor y = session.AllocateTensor(ActionName, Shape.Concat(xs.Select(x => x.Shape).ToArray(), axis), calculateGradient);
ArrayOperations.Concat(xs, axis, y, false);
#if !NOLEARNING
if (calculateGradient)
{
session.Push(ActionName, () => ArrayOperations.Split(y, axis, xs, true));
}
#endif
return y;
}));
}
public static Tensor[] Split(this Session session, Tensor x, int axis, int[] sizes)
{
const string ActionName = "split";
if (axis < 0)
{
throw new ArgumentException(Properties.Resources.E_NegativeAxisIndex, nameof(axis));
}
return(session.RunOperation(
ActionName,
() =>
{
bool calculateGradient = session.CalculateGradients && x.CalculateGradient;
// check sizes
int ydim = sizes.Length;
int sum = 0;
for (int i = 0; i < ydim; i++)
{
sum += sizes[i];
}
if (sum != x.Shape.Axes[axis])
{
throw new ArgumentException("The sub tensors sizes must be provided.");
}
// allocate destination
Tensor[] ys = new Tensor[ydim];
for (int i = 0; i < ydim; i++)
{
ys[i] = session.AllocateTensor(ActionName, x.Shape.Reshape(axis, sizes[i]), calculateGradient);
}
ArrayOperations.Split(x, axis, ys, false);
#if !NOLEARNING
if (calculateGradient)
{
session.Push(ActionName, () => ArrayOperations.Concat(ys, axis, x, true));
// return copy of the array; calling method can replace its content; our closure keeps the array, not its items
return ys.ToArray();
}
#endif
return ys;
}));
}
public static Tensor[] Split(this Session session, Tensor x, int axis, int numberOfSplits)
{
const string ActionName = "split";
if (axis < 0)
{
throw new ArgumentException(Properties.Resources.E_NegativeAxisIndex, nameof(axis));
}
// check number of splits
if ((x.Axes[axis] % numberOfSplits) != 0)
{
throw new ArgumentException("The number of tensors to split into must evenly divide the tensor split dimension.", nameof(numberOfSplits));
}
return(session.RunOperation(
ActionName,
() =>
{
bool calculateGradient = session.CalculateGradients && x.CalculateGradient;
// allocate destination
Tensor[] ys = session.AllocateTensors(
ActionName,
numberOfSplits,
x.Shape.Reshape(axis, x.Axes[axis] / numberOfSplits),
calculateGradient);
ArrayOperations.Split(x, axis, ys, false);
#if !NOLEARNING
if (calculateGradient)
{
session.Push(ActionName, () => ArrayOperations.Concat(ys, axis, x, true));
// return copy of the array; calling method can replace its content; our closure keeps the array, not its items
return ys.ToArray();
}
#endif
return ys;
}));
}