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Fix for permutation cpu reference impl #253

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Jul 26, 2024
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Fix for permutation cpu reference impl #253

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81 changes: 19 additions & 62 deletions library/src/permutation/permutation_cpu_reference_impl.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -115,74 +115,31 @@ namespace hiptensor
auto elementCount = hiptensor::elementsFromLengths(
std::vector<index_t>(std::begin(arg.mLengths), std::end(arg.mLengths)));

#if HIPTENSOR_DATA_LAYOUT_COL_MAJOR
// Sort the output strides to calculate output tensor lengths
std::vector<int> outStrides(std::begin(arg.mOutStrides[0]),
std::end(arg.mOutStrides[0]));
std::sort(outStrides.begin(), outStrides.end());
assert(outStrides.front() == 1);

// Map the lengths in output to its indices( using list to cover redundant lengths )
std::unordered_map<int32_t, std::list<int32_t>> bLengthToIndex;
int prevLength = 1, i;
for(i = 1; i < modeSize; i++)
{
bLengthToIndex[outStrides[i] / prevLength].push_back(i - 1);
prevLength = outStrides[i];
}
bLengthToIndex[elementCount / prevLength].push_back(i - 1);
#else
// Sort the output strides to calculate output tensor lengths
std::vector<int> outStrides(std::begin(arg.mOutStrides[0]),
std::end(arg.mOutStrides[0]));
std::sort(outStrides.rbegin(), outStrides.rend());
assert(outStrides.back() == 1);

// Map the lengths in output to its indices( using list to cover redundant lengths )
std::unordered_map<int32_t, std::list<int32_t>> bLengthToIndex;
int prevLength = 1, i;
for(i = modeSize - 2; i >= 0; i--)
{
bLengthToIndex[outStrides[i] / prevLength].push_back(i + 1);
prevLength = outStrides[i];
}
bLengthToIndex[elementCount / prevLength].push_back(i + 1);
#endif

// From computed output lengths and argument's input lengths,
// create a mode map between input and output
std::map<int, int> modeATomodeBmap;
for(int i = 0; i < modeSize; i++)
{
modeATomodeBmap[i] = bLengthToIndex[arg.mLengths[i]].front();
bLengthToIndex[arg.mLengths[i]].pop_front();
}

// Find the write offset and index in output for every input element
auto bIndices = std::vector<int32_t>(modeSize, 0);
auto indices = std::vector<int32_t>(modeSize, 0);
for(int elementIndex = 0; elementIndex < elementCount; elementIndex++)
{
auto index = elementIndex;
#if HIPTENSOR_DATA_LAYOUT_COL_MAJOR
for(int modeIndex = 0; modeIndex < modeSize; modeIndex++)
{
bIndices[modeATomodeBmap[modeIndex]] = index % arg.mLengths[modeIndex];
index /= arg.mLengths[modeIndex];
}
auto bOffset = std::inner_product(
bIndices.begin(), bIndices.end(), std::begin(outStrides), 0);
#else // HIPTENSOR_DATA_LAYOUT_COL_MAJOR
for(int modeIndex = modeSize - 1; modeIndex >= 0; modeIndex--)
{
bIndices[modeATomodeBmap[modeIndex]] = index % arg.mLengths[modeIndex];
index /= arg.mLengths[modeIndex];
}
auto nextIndex = [&indices, &arg]() -> bool {
int N = indices.size();
for (int i = N - 1; i >= 0; --i) {
if (indices[i] < arg.mLengths[i] - 1) {
++indices[i];
return true;
} else {
indices[i] = 0;
}
}
return false;
};

auto bOffset = std::inner_product(
bIndices.rbegin(), bIndices.rend(), std::rbegin(outStrides), 0);
#endif // HIPTENSOR_DATA_LAYOUT_COL_MAJOR
indices.rbegin(), indices.rend(), std::rbegin(arg.mOutStrides[0]), 0);
auto aOffset = std::inner_product(
indices.rbegin(), indices.rend(), std::rbegin(arg.mInStrides[0]), 0);
nextIndex();

// Perform sequence of unary, scale operations on input
arg.mElementOp(arg.mOutput[bOffset], arg.mInput[elementIndex]);
arg.mElementOp(arg.mOutput[bOffset], arg.mInput[aOffset]);
}
return 0;
}
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