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1 change: 1 addition & 0 deletions .github/workflows/codeql.yml
Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@ name: "CodeQL Advanced"

on:
workflow_dispatch:
pull_request:
push:
branches:
- develop
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4 changes: 2 additions & 2 deletions .gitmodules
Original file line number Diff line number Diff line change
Expand Up @@ -3,13 +3,13 @@
url = https://github.com/google/flatbuffers.git
[submodule "thirdparty/elf"]
path = thirdparty/elf
url = https://github.com/openvinotoolkit/npu_plugin_elf.git
url = https://github.com/DariaMityagina/vpux_plugin_elf.git
[submodule "thirdparty/llvm-project"]
path = thirdparty/llvm-project
url = https://github.com/intel/npu-plugin-llvm.git
[submodule "thirdparty/vpucostmodel"]
path = thirdparty/vpucostmodel
url = https://github.com/intel/npu-nn-cost-model.git
url = https://github.com/DariaMityagina/npu-nn-cost-model.git
[submodule "thirdparty/yaml-cpp"]
path = thirdparty/yaml-cpp
url = https://github.com/jbeder/yaml-cpp
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3 changes: 2 additions & 1 deletion src/vpux_compiler/src/bitc/src/Encoder.cpp
Original file line number Diff line number Diff line change
Expand Up @@ -756,7 +756,8 @@ void Encoder::Impl::encode(const BitCompactorConfig& config, const std::vector<u
const auto last_block_elements{input_bytes - (input_blocks << 6)};
uint32_t last_block{static_cast<uint32_t>(last_block_elements > 0u)};

std::vector<AlgorithmParam> block_params(input_blocks * ALGORITHMS);
std::size_t total_blocks = static_cast<std::size_t>(input_blocks) * static_cast<std::size_t>(ALGORITHMS);
std::vector<AlgorithmParam> block_params(total_blocks);
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Multiplication result converted to larger type

std::vector<BitStream> block_stream(input_blocks + last_block);

if (config.mode_fp16_enable) {
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Original file line number Diff line number Diff line change
Expand Up @@ -160,7 +160,7 @@ SmallVector<int64_t> inferOutputShapeWithScalesMode(ShapeRef inputShape, ArrayRe
auto scalesIter = scalesVal.begin();
for (const auto& axis : axesVal) {
outputShape[axis] =
static_cast<int64_t>(floor(static_cast<StorageType>(*scalesIter++) * inputShape[Dim(axis)]));
static_cast<int64_t>(floor(static_cast<double>(static_cast<StorageType>(*scalesIter++) * inputShape[Dim(axis)])));
log.trace("Infer Scales mode at axis {0}: {1} -> {2}", axis, inputShape[Dim(axis)], outputShape[axis]);
}
return outputShape;
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Original file line number Diff line number Diff line change
Expand Up @@ -518,7 +518,7 @@ class CompressionRateCounter {
convertBytesToReadableSize(compressedF16constantsAfterCompression_),
(double)compressedF16constantsAfterCompression_ / compressedF16constantsBeforeCompression_ * 100);
}
if (compressedConstantsCounter_ - compressedF16constantsCounter_ > 0) {
if (compressedConstantsCounter_ > compressedF16constantsCounter_) {
log.nest().info(
"Int8 - count: {0}, size: {1}, compressed size: {2}, ({3}%)",
compressedConstantsCounter_ - compressedF16constantsCounter_,
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Original file line number Diff line number Diff line change
Expand Up @@ -157,7 +157,7 @@ void PatchPopulateWeightTableWithShavePass::patchShaveForPopulateWeightTable(VPU
const auto offsetsAttr = subView.getStaticOffsets();
auto offsets = parseIntArrayAttr<int32_t>(offsetsAttr);
_log.trace("offset {0}", offsets);
swKernelRunOffsets.push_back(offsets[0] * weightAddressOffset);
swKernelRunOffsets.push_back(static_cast<int64_t>(offsets[0]) * static_cast<int64_t>(weightAddressOffset));
} else {
swKernelRunOffsets.push_back(0);
}
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2 changes: 1 addition & 1 deletion thirdparty/elf
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