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[DML EP] Fix variable shadowing in EinSum (#13520)

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### Description
Fix variable shadowing in the DML EP's implementation of EinSum



### Motivation and Context
An SDL bug was opened because of shadowing of the variable `i` in a
nested loop of the EinSum operator.
This commit is contained in:
Patrice Vignola 2022-10-31 19:27:43 -07:00 committed by GitHub
parent 74f905b237
commit 3d0db47c17
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GPG key ID: 4AEE18F83AFDEB23
1 changed files with 10 additions and 10 deletions
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20
onnxruntime/core/providers/dml/DmlExecutionProvider/src/Operators/DmlOperatorEinSum.cpp
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@ -76,11 +76,11 @@ public:
constexpr std::array<uint32_t, 4> labelIndices = {0, 2, 1, 3};
assert(m_inputTensorDescs.size() >= 2);
for (uint32_t i = 0; i < 2; ++i)
for (uint32_t inputIndex = 0; inputIndex < 2; ++inputIndex)
{
TensorDesc& tensorDesc = m_inputTensorDescs[i];
TensorDesc& tensorDesc = m_inputTensorDescs[inputIndex];
auto originalStrides = tensorDesc.GetStrides();
std::vector<uint32_t> inputSizes = kernelCreationContext.GetTensorShapeDescription().GetInputTensorShape(i);
std::vector<uint32_t> inputSizes = kernelCreationContext.GetTensorShapeDescription().GetInputTensorShape(inputIndex);
std::vector<uint32_t> inputStrides(inputSizes.size());
// If there were no strides, compute them based in descending packed order
@ -98,12 +98,12 @@ public:
std::vector<uint32_t> newStrides(inputStrides.size());
std::vector<uint32_t> newSizes(inputStrides.size());
for (size_t i = 0, dimensionCount = inputStrides.size(); i < dimensionCount; ++i)
for (size_t dim = 0, dimensionCount = inputStrides.size(); dim < dimensionCount; ++dim)
{
uint32_t labelIndex = labelIndices[i];
uint32_t labelIndex = labelIndices[dim];
assert(labelIndex < inputStrides.size());
newSizes[i] = inputSizes[labelIndex];
newStrides[i] = inputStrides[labelIndex];
newSizes[dim] = inputSizes[labelIndex];
newStrides[dim] = inputStrides[labelIndex];
}
// Override the initial input tensor with the new strides.
@ -115,10 +115,10 @@ public:
std::vector<uint32_t> newOutputSizes(outputSizes.size());
assert(outputSizes.size() == labelIndices.size());
for (size_t i = 0; i < outputSizes.size(); ++i)
for (size_t dim = 0; dim < outputSizes.size(); ++dim)
{
uint32_t labelIndex = labelIndices[i];
newOutputSizes[i] = outputSizes[labelIndex];
uint32_t labelIndex = labelIndices[dim];
newOutputSizes[dim] = outputSizes[labelIndex];
}
m_outputTensorDescs.front() = TensorDesc(m_outputTensorDescs.front().GetDmlDataType(), newOutputSizes, std::nullopt, 0);