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https://github.com/saymrwulf/pytorch.git
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a9b0a921d5
Summary: As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH` All changes but the ones to `.clang-tidy` are generated using following script: ``` for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`; do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008 Reviewed By: driazati, r-barnes Differential Revision: D29838584 Pulled By: malfet fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
43 lines
1 KiB
C++
43 lines
1 KiB
C++
#include "caffe2/core/logging.h"
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#include "caffe2/opt/converter.h"
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#include "caffe2/opt/passes.h"
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namespace caffe2 {
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namespace opt {
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using namespace nom;
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using namespace nom::repr;
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void deadCodeElim(NNModule* nn) {
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// Iteratively remove unconsumed non-external outputs.
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bool changed = false;
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do {
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changed = false;
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for (const auto& node : nn->dataFlow.getMutableNodes()) {
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NOM_REQUIRE_OR_CONT(nn::is<repr::NeuralNetOperator>(node));
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bool isUsed = false;
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for (const auto& output : nn::getOutputs(node)) {
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if (nn::hasConsumer(output) || nn->outputs.count(output)) {
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isUsed = true;
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break;
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}
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}
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NOM_REQUIRE_OR_CONT(!isUsed);
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// No outputs are used, delete them and the node itself.
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for (const auto& output : nn::getOutputs(node)) {
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nn->dataFlow.deleteNode(output);
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}
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nn->dataFlow.deleteNode(node);
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changed = true;
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break;
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}
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} while (changed);
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}
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REGISTER_OPT_PASS_FROM_FUNC(DeadCodeElim, deadCodeElim);
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} // namespace opt
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} // namespace caffe2
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