pytorch/caffe2/opt/dead_code_elim_test.cc

58 lines
1.5 KiB
C++

#include "caffe2/core/common.h"
#include "caffe2/opt/converter.h"
#include "caffe2/opt/passes.h"
#include <gtest/gtest.h>
TEST(DeadCodeElim, BasicElim) {
caffe2::NetDef net;
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("X");
def->add_output("Y");
}
auto nn = caffe2::convertToNNModule(net);
auto pass = caffe2::OptimizationPassRegistry()->Create("DeadCodeElim", &nn);
pass->run();
auto optimized_net = caffe2::convertToCaffe2Proto(nn, net);
EXPECT_EQ(optimized_net.op().size(), 0);
}
TEST(DeadCodeElim, BasicNoElim) {
caffe2::NetDef net;
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("X");
def->add_output("Y");
}
net.add_external_output("Y");
auto nn = caffe2::convertToNNModule(net);
auto pass = caffe2::OptimizationPassRegistry()->Create("DeadCodeElim", &nn);
pass->run();
auto optimized_net = caffe2::convertToCaffe2Proto(nn, net);
EXPECT_EQ(optimized_net.op().size(), 1);
}
TEST(DeadCodeElim, PartiallyUsedNoElim) {
caffe2::NetDef net;
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("X");
def->add_output("Y");
def->add_output("Z");
}
net.add_external_output("Y");
// Z is unused, but we should keep Fake because Y is
auto nn = caffe2::convertToNNModule(net);
auto pass = caffe2::OptimizationPassRegistry()->Create("DeadCodeElim", &nn);
pass->run();
auto optimized_net = caffe2::convertToCaffe2Proto(nn, net);
EXPECT_EQ(optimized_net.op().size(), 1);
}