public ONNXTensor Permute(int[] permutations)
{
// transpose both data & shape
var transposedData = Permute(m_Data, permutations);
var transposedShape = ONNXLayout.Permute(m_Shape, permutations);
return(new ONNXTensor(transposedData, transposedShape));
}
internal static Tensor Permute(Tensor inTensor, int[] permutations) // TODO: unify Permute() arguments
{
var padPermutationsToBarracudaRank = 4 - permutations.Length;
if (padPermutationsToBarracudaRank > 0)
{
permutations = permutations.Concat(Enumerable.Range(permutations.Length, padPermutationsToBarracudaRank)).ToArray();
}
Debug.Assert(permutations.Length == 4);
// See: https://stackoverflow.com/a/32034565
Profiler.BeginSample("ONNXTensor.Permute");
var outTensor = new Tensor(ONNXLayout.Permute(inTensor.shape.ToArray(), permutations));
Debug.Assert(outTensor.length == inTensor.length);
// {0, 2, 3, 1} => {0, 3, 1, 2}
// {2, 3, 1, 0} => {3, 2, 0, 1}
// => {find_index(0), find_index(1), find_index(2), find_index(3)}
var reversePermute = new int[permutations.Length];
for (var i = 0; i < permutations.Length; ++i)
{
reversePermute[i] = Array.IndexOf(permutations, i);
}
// outTensor strides
var outStrideC = outTensor.channels;
var outStrideWC = outStrideC * outTensor.width;
var outStrideHWC = outStrideWC * outTensor.height;
var outStride = new int[reversePermute.Length];
for (var i = 0; i < reversePermute.Length; ++i)
{
outStride[i] = new[] { 0, outStrideHWC, outStrideWC, outStrideC, 1 }
}