static public int[] Permutation4DTo8D(int[] permutations)
{
if (permutations.Length == TensorShape.MaxRank)
{
return(permutations);
}
int batchOldAxis = TensorExtensions.Convert4DTo8DAxis(permutations[0]);
int heighOldAxis = TensorExtensions.Convert4DTo8DAxis(permutations[1]);
int widthOldIndex = TensorExtensions.Convert4DTo8DAxis(permutations[2]);
int channeOldIndex = TensorExtensions.Convert4DTo8DAxis(permutations[3]);
return(new int[] { 0, 1, batchOldAxis, 3, 4, heighOldAxis, widthOldIndex, channeOldIndex });
}
int[] MergeTranspose(int[] transpose0, int[] tranpose1)
{
int[] permutations = new int[] { 0, 1, 2, 3, 4, 5, 6, 7 };
if (transpose0.Length == 4)
{
permutations[2] = TensorExtensions.Convert4DTo8DAxis(transpose0[0]);
permutations[5] = TensorExtensions.Convert4DTo8DAxis(transpose0[1]);
permutations[6] = TensorExtensions.Convert4DTo8DAxis(transpose0[2]);
permutations[7] = TensorExtensions.Convert4DTo8DAxis(transpose0[3]);
}
else
{
permutations[0] = transpose0[0];
permutations[1] = transpose0[1];
permutations[2] = transpose0[2];
permutations[3] = transpose0[3];
permutations[4] = transpose0[4];
permutations[5] = transpose0[5];
permutations[6] = transpose0[6];
permutations[7] = transpose0[7];
}
int[] combinePermutations = new int[] { 0, 1, 2, 3, 4, 5, 6, 7 };
if (tranpose1.Length == 4)
{
combinePermutations[2] = TensorExtensions.Convert4DTo8DAxis(tranpose1[0]);
combinePermutations[5] = TensorExtensions.Convert4DTo8DAxis(tranpose1[1]);
combinePermutations[6] = TensorExtensions.Convert4DTo8DAxis(tranpose1[2]);
combinePermutations[7] = TensorExtensions.Convert4DTo8DAxis(tranpose1[3]);
}
else
{
combinePermutations[0] = tranpose1[0];
combinePermutations[1] = tranpose1[1];
combinePermutations[2] = tranpose1[2];
combinePermutations[3] = tranpose1[3];
combinePermutations[4] = tranpose1[4];
combinePermutations[5] = tranpose1[5];
combinePermutations[6] = tranpose1[6];
combinePermutations[7] = tranpose1[7];
}
permutations = TensorExtensions.Permute(permutations, combinePermutations);
return(permutations);
}
void ConcatenateTransposes(ref Model model)
{
var remap = new Dictionary<string, string>();
var layerReferences = new Dictionary<string, int>();
for (int l = 0; l < model.layers.Count; ++l)
{
Layer layer = model.layers[l];
string[] layerInputs = layer.inputs;
for (int i = 0; i < layerInputs.Length; i++)
{
if (layerReferences.TryGetValue(layerInputs[i], out int count))
count++;
else
count = 0;
layerReferences[layerInputs[i]] = count;
}
if (model.outputs.Contains(layer.name))
{
if (layerReferences.TryGetValue(layer.name, out int count))
count++;
else
count = 0;
layerReferences[layer.name] = count;
}
}
for (int l = 0; l < model.layers.Count - 1; ++l)
{
var layer = model.layers[l];
var nextLayer = model.layers[l + 1];
if (remap.ContainsKey(layer.name)) // This layer will get removed
continue;
string[] layerInputs = layer.inputs;
for (int i = 0; i < layerInputs.Length; i++)
{
if (remap.TryGetValue(layerInputs[i], out string replacement))
layerInputs[i] = replacement;
}
if (layer.flags.HasFlag(Layer.Flags.Preserve))
continue;
bool reverseMerge = nextLayer.flags.HasFlag(Layer.Flags.Preserve);
// Only concatenate serial transpose layers
if (layer.type == Layer.Type.Transpose
&& nextLayer.type == Layer.Type.Transpose
&& nextLayer.inputs.Contains(layer.name)
&& layerReferences.TryGetValue(layer.name, out int references)
&& references <= 1
&& layerReferences.TryGetValue(nextLayer.name, out references)
&& references <= 1)
{
int[] permutations = new int[] { 0, 1, 2, 3, 4, 5, 6, 7 };
if (layer.pool.Length == 4)
{
permutations[2] = TensorExtensions.Convert4DTo8DAxis(layer.pool[0]);
permutations[5] = TensorExtensions.Convert4DTo8DAxis(layer.pool[1]);
permutations[6] = TensorExtensions.Convert4DTo8DAxis(layer.pool[2]);
permutations[7] = TensorExtensions.Convert4DTo8DAxis(layer.pool[3]);
}
else
{
permutations[0] = layer.pool[0];
permutations[1] = layer.pool[1];
permutations[2] = layer.pool[2];
permutations[3] = layer.pool[3];
permutations[4] = layer.pool[4];
permutations[5] = layer.pool[5];
permutations[6] = layer.pool[6];
permutations[7] = layer.pool[7];
}
int[] combinePermutations = new int[] { 0, 1, 2, 3, 4, 5, 6, 7 };
if (nextLayer.pool.Length == 4)
{
combinePermutations[2] = TensorExtensions.Convert4DTo8DAxis(nextLayer.pool[0]);
combinePermutations[5] = TensorExtensions.Convert4DTo8DAxis(nextLayer.pool[1]);
combinePermutations[6] = TensorExtensions.Convert4DTo8DAxis(nextLayer.pool[2]);
combinePermutations[7] = TensorExtensions.Convert4DTo8DAxis(nextLayer.pool[3]);
}
else
{
combinePermutations[0] = nextLayer.pool[0];
combinePermutations[1] = nextLayer.pool[1];
combinePermutations[2] = nextLayer.pool[2];
combinePermutations[3] = nextLayer.pool[3];
combinePermutations[4] = nextLayer.pool[4];
combinePermutations[5] = nextLayer.pool[5];
combinePermutations[6] = nextLayer.pool[6];
combinePermutations[7] = nextLayer.pool[7];
}
permutations = TensorExtensions.Permute(permutations, combinePermutations);
if (reverseMerge)
{
remap[layer.name] = nextLayer.name;
nextLayer.pool = permutations;
nextLayer.inputs = layer.inputs.ToArray();
}
else
{
layer.pool = permutations;
remap[nextLayer.name] = layer.name;
}
}
}
var removeLayers = remap.Keys;
model.layers.RemoveAll(l => removeLayers.Contains(l.name));
}