//TODO this is not actually used at the moment. It probably should be.
// excludeDim may be -1 to not exclude any dimension
/// <summary>
/// Collapses the dims.
/// </summary>
/// <param name="tensor">The tensor.</param>
/// <param name="excludeDim">The exclude dim.</param>
/// <param name="info">The information.</param>
/// <returns>System.Int32.</returns>
/// <exception cref="ArgumentException">excludeDim must equal -1 if all dims are of size 1 - excludeDim</exception>
public static int CollapseDims(Tensor tensor, int excludeDim, out TensorInfo info)
{
info.buffer = CudaHelpers.GetBufferStart(tensor);
var firstNonOneDim = GetInnermostNon1Dim(tensor.Shape, excludeDim);
// If all dims are size 1 (ie. tensor contains 1 element)
if (firstNonOneDim == -1)
{
if (excludeDim != -1)
{
throw new ArgumentException("excludeDim must equal -1 if all dims are of size 1", "excludeDim");
}
info.sizes = new long[] { 1 };
info.strides = new long[] { 1 };
return(0);
}
// Count the number of successive dimensions that can be collapsed, from
// innermost to outermost.
int numCollapsed = 0;
// Skip the leading size 1 dims
numCollapsed += tensor.DimensionCount - 1 - firstNonOneDim;
// We perform one pass through to determine how many dimensions we
// can collapse, before calculating the actual size of the collapsed
// dimensions.
// size/strideInner are the size/strides of the previous inner
// non-collapsible dim we encounter.
var sizeInner = tensor.Shape[firstNonOneDim];
var strideInner = tensor.Strides[firstNonOneDim];
for (int i = firstNonOneDim - 1; i >= 0; --i)
{
var sizeOuter = tensor.Shape[i];
var strideOuter = tensor.Strides[i];
// Don't collapse this dimension if we want to exclude it from
// collapsing.
// Since this code is attempting to collapse a subsequent
// dimension (i) with the preceding dimension (i + 1), we can only
// perform collapsing if the preceding dimension can be collapsed
// (i.e., not excludeDim)
if ((excludeDim != i) && (excludeDim != i + 1))
{
// The next outermost dimension can be skipped if size 1
if (sizeOuter == 1)
{
++numCollapsed;
continue;
}
// If the next outermost dimension is contiguous with the
// previous non-collapsed one, collapse it
if (strideOuter == strideInner * sizeInner)
{
++numCollapsed;
// This is the run of collapsed dimensions' size
sizeInner = sizeInner * sizeOuter;
continue;
}
}
// Otherwise, this new outer dimension at `i` cannot be collapsed
// because it is excluded from collapsing, or it is not contiguous
// with the previous inner dimension.
sizeInner = sizeOuter;
strideInner = strideOuter;
}
// This will be our new size/stride and dimension.
var newSizes = new long[TSCudaContext.MaxDims];
var newStrides = new long[TSCudaContext.MaxDims];
int newDims = tensor.DimensionCount - numCollapsed;
// We return the index of the excluded dimension that is excluded
// from being collapsed here.
int returnDim = -1;
// We perform a second pass through the dimensions to actually
// calculate the size of the collapsed dimensions.
int collapsedIndex = tensor.DimensionCount - numCollapsed - 1;
newSizes[collapsedIndex] = tensor.Shape[firstNonOneDim];
newStrides[collapsedIndex] = tensor.Strides[firstNonOneDim];
if (firstNonOneDim == excludeDim)
{
returnDim = collapsedIndex;
}
for (int i = firstNonOneDim - 1; i >= 0; --i)
{
var sizeOuter = tensor.Shape[i];
var strideOuter = tensor.Strides[i];
if ((excludeDim != i) && (excludeDim != i + 1))
{
if (sizeOuter == 1)
{
// skip
continue;
}
if (strideOuter == newSizes[collapsedIndex] * newStrides[collapsedIndex])
{
// collapse
newSizes[collapsedIndex] *= sizeOuter;
continue;
}
}
// Otherwise, strides don't match, or dim `i` is excluded from
// collapsing.
--collapsedIndex;
//assert(collapsedIndex >= 0);
//assert(collapsedIndex < newDims);
newSizes[collapsedIndex] = sizeOuter;
newStrides[collapsedIndex] = strideOuter;
if (excludeDim == i)
{
returnDim = collapsedIndex;
}
}
info.sizes = newSizes.Take(newDims).ToArray();
info.strides = newStrides.Take(newDims).ToArray();
return(returnDim);
}
private static CudaDeviceVariable <float> GetDeviceVar(Tensor tensor)
{
var ptr = CudaHelpers.GetBufferStart(tensor);
return(new CudaDeviceVariable <float>(ptr, false, 0));// set size to 0 because we never end up using it
}
