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https://github.com/saymrwulf/pytorch.git
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bb7d1837bc
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/10101 Simple DCE enabled by knowledge of the actual outputs (stacked beneath this diff) Reviewed By: yinghai Differential Revision: D9107853 fbshipit-source-id: 0c38fe5fe408be2b7fc9e1fe6a5b7160c06ce79b
57 lines
1.5 KiB
C++
57 lines
1.5 KiB
C++
#include "caffe2/core/common.h"
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#include "caffe2/opt/converter.h"
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#include "caffe2/opt/passes.h"
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#include <gtest/gtest.h>
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TEST(DeadCodeElim, BasicElim) {
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caffe2::NetDef net;
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{
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caffe2::OperatorDef* def = net.add_op();
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def->set_type("Fake");
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def->add_input("X");
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def->add_output("Y");
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}
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auto nn = caffe2::convertToNNModule(net);
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auto pass = caffe2::OptimizationPassRegistry()->Create("DeadCodeElim", &nn);
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pass->run();
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auto optimized_net = caffe2::convertToCaffe2Proto(nn, net);
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EXPECT_EQ(optimized_net.op().size(), 0);
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}
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TEST(DeadCodeElim, BasicNoElim) {
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caffe2::NetDef net;
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{
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caffe2::OperatorDef* def = net.add_op();
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def->set_type("Fake");
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def->add_input("X");
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def->add_output("Y");
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}
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net.add_external_output("Y");
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auto nn = caffe2::convertToNNModule(net);
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auto pass = caffe2::OptimizationPassRegistry()->Create("DeadCodeElim", &nn);
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pass->run();
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auto optimized_net = caffe2::convertToCaffe2Proto(nn, net);
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EXPECT_EQ(optimized_net.op().size(), 1);
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}
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TEST(DeadCodeElim, PartiallyUsedNoElim) {
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caffe2::NetDef net;
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{
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caffe2::OperatorDef* def = net.add_op();
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def->set_type("Fake");
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def->add_input("X");
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def->add_output("Y");
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def->add_output("Z");
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}
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net.add_external_output("Y");
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// Z is unused, but we should keep Fake because Y is
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auto nn = caffe2::convertToNNModule(net);
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auto pass = caffe2::OptimizationPassRegistry()->Create("DeadCodeElim", &nn);
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pass->run();
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auto optimized_net = caffe2::convertToCaffe2Proto(nn, net);
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EXPECT_EQ(optimized_net.op().size(), 1);
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}
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