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#include <gtest/gtest.h>
#include "caffe2/opt/converter.h"
#include "caffe2/opt/distributed.h"
caffe2::NetDef fakeNet() {
caffe2::NetDef net;
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("X");
def->add_output("Y");
}
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("Y");
def->add_output("Z");
}
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("Z");
def->add_input("X");
def->add_output("W");
}
net.add_external_input("X");
net.add_external_output("Y");
net.add_external_output("W");
return net;
}
caffe2::NetDef fakeNetWithDuplicateKeyInExInputAndOutput() {
caffe2::NetDef net;
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("X");
def->add_output("Y");
}
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("Y");
def->add_output("X");
}
{
caffe2::OperatorDef* def = net.add_op();
def->set_type("Fake");
def->add_input("Y");
def->add_output("W");
}
net.add_external_input("X");
net.add_external_output("X");
net.add_external_output("Y");
net.add_external_output("W");
return net;
}
// Common usage
using namespace nom::repr;
TEST(Converter, DeclareExport) {
auto net = fakeNet();
caffe2::injectDataEdgeIndicators(&net);
auto nn = caffe2::convertToNNModule(net);
// This is in nom::repr
auto inputs = nn::filter<Declare>(nn);
auto outputs = nn::filter<Export>(nn);
auto count = 0;
for (const auto& declareNode : inputs) {
count++;
// This call fails an assertion if it isn't true
auto delcare_op = nn::get<Declare>(declareNode);
// String version of name can be extracted like this
EXPECT_EQ(delcare_op->getName(), "Declare");
// What used to be external_input (note that getOutputs returns a vector)
auto inputNode = nn::getOutputs(declareNode).at(0);
// Key idea is that we are working with nodes that hold things,
// so nn::get<T> is very commonly used
auto input = nn::get<Tensor>(inputNode);
// We only had one external input in the original net,
// so this should be true
EXPECT_EQ(input->getName(), "X");
}
// Only 1 external input
EXPECT_EQ(count, 1);
// Reset for external output
count = 0;
for (const auto& exportNode : outputs) {
count++;
}
// 2 external outputs
EXPECT_EQ(count, 2);
}
TEST(Distributed, InsertDeviceOptions) {
auto net = fakeNet();
caffe2::injectDataEdgeIndicators(&net);
auto nn = caffe2::convertToNNModule(net);
caffe2::DeviceOption d;
d.set_device_type(1337);
caffe2::addBlobDeviceOptions({{"X", d}, {"Y", d}, {"W", d}}, &nn);
for (auto& ns : {nn::filter<Declare>(nn), nn::filter<Export>(nn)}) {
for (auto& node : ns) {
auto op = nn::get<NeuralNetOperator>(node);
auto annot = dyn_cast<caffe2::Caffe2Annotation>(op->getAnnotation());
// NOLINTNEXTLINE(performance-unnecessary-copy-initialization)
auto d = annot->getDeviceOption();
EXPECT_EQ(d.device_type(), 1337);
}
}
}
TEST(Distributed, InsertDeviceOptionsFailureCase) {
auto net = fakeNet();
caffe2::injectDataEdgeIndicators(&net);
auto nn = caffe2::convertToNNModule(net);
caffe2::DeviceOption d;
d.set_device_type(1337);
// We can only use correct blob names, expect failure otherwise
// NOLINTNEXTLINE(hicpp-avoid-goto,cppcoreguidelines-avoid-goto)
EXPECT_THROW(
{
caffe2::addBlobDeviceOptions(
{{"X", d}, {"Y", d}, {"W", d}, {"FAKE", d}}, &nn);
},
std::exception);
}
TEST(Distributed, InsertDeviceOptionsDuplicateKeyAcrossExternalInputAndOutput) {
auto net = fakeNetWithDuplicateKeyInExInputAndOutput();
caffe2::injectDataEdgeIndicators(&net);
auto nn = caffe2::convertToNNModule(net);
caffe2::DeviceOption d;
d.set_device_type(1337);
caffe2::addBlobDeviceOptions({{"X", d}, {"Y", d}, {"W", d}}, &nn);
for (auto& ns : {nn::filter<Declare>(nn), nn::filter<Export>(nn)}) {
for (auto& node : ns) {
auto op = nn::get<NeuralNetOperator>(node);
auto annot = dyn_cast<caffe2::Caffe2Annotation>(op->getAnnotation());
// NOLINTNEXTLINE(performance-unnecessary-copy-initialization)
auto d_annot = annot->getDeviceOption();
EXPECT_EQ(d_annot.device_type(), 1337);
}
}
}
TEST(Distributed, InsertDeviceOptionsDuplicateKeyInExternalInput) {
auto net = fakeNetWithDuplicateKeyInExInputAndOutput();
net.add_external_input("X");
caffe2::injectDataEdgeIndicators(&net);
auto nn = caffe2::convertToNNModule(net);
caffe2::DeviceOption d;
d.set_device_type(1337);
EXPECT_THROW(
{
caffe2::addBlobDeviceOptions(
{{"X", d}, {"Y", d}, {"W", d}}, &nn);
},
std::exception);
}
TEST(Distributed, InsertDeviceOptionsDuplicateKeyInExternalOutput) {
auto net = fakeNetWithDuplicateKeyInExInputAndOutput();
net.add_external_output("X");
caffe2::injectDataEdgeIndicators(&net);
auto nn = caffe2::convertToNNModule(net);
caffe2::DeviceOption d;
d.set_device_type(1337);
EXPECT_THROW(
{
caffe2::addBlobDeviceOptions(
{{"X", d}, {"Y", d}, {"W", d}}, &nn);
},
std::exception);
}
TEST(Converter, InjectDataEdgeIndicators) {
auto net = fakeNet();
auto nn = caffe2::convertToNNModule(net);
caffe2::injectDataEdgeIndicators(&nn);
auto new_net = caffe2::convertToCaffe2Proto(nn);
EXPECT_EQ(new_net.op_size(), 3 + 1 + 2); // Inserted 1 Declare and 2 Export
auto declare_count = 0;
auto export_count = 0;
for (const auto& op : new_net.op()) {
declare_count += op.type() == "Declare";
export_count += op.type() == "Export";
}
EXPECT_EQ(declare_count, 1);
EXPECT_EQ(export_count, 2);
// Remove them from the network
EXPECT_EQ(new_net.external_input_size(), 0);
EXPECT_EQ(new_net.external_output_size(), 0);
auto new_nn = caffe2::convertToNNModule(new_net);
caffe2::removeDataEdgeIndicators(&new_nn);
new_net = caffe2::convertToCaffe2Proto(new_nn);
for (const auto& op : new_net.op()) {
EXPECT_NE(op.type(), "Declare");
EXPECT_NE(op.type(), "Export");
}
EXPECT_EQ(new_net.external_input_size(), 1);
EXPECT_EQ(new_net.external_output_size(), 2);
}
// Main usage
TEST(Converter, OverloadedConvertToNNModule) {
auto net = fakeNet();
caffe2::DeviceOption d;
d.set_device_type(1337);
auto nn = caffe2::convertToNNModule(net, {{"X", d}, {"Y", d}, {"W", d}});
for (auto& ns : {nn::filter<Declare>(nn), nn::filter<Export>(nn)}) {
for (auto& node : ns) {
auto op = nn::get<NeuralNetOperator>(node);
auto annot = dyn_cast<caffe2::Caffe2Annotation>(op->getAnnotation());
// NOLINTNEXTLINE(performance-unnecessary-copy-initialization)
auto d = annot->getDeviceOption();
EXPECT_EQ(d.device_type(), 1337);
}
}
}
TEST(Converter, OverloadedConvertToNNModuleFailure) {
auto net = fakeNet();
caffe2::DeviceOption d;
d.set_device_type(1337);
// We can only use correct blob names, expect failure otherwise
// NOLINTNEXTLINE(hicpp-avoid-goto,cppcoreguidelines-avoid-goto)
EXPECT_THROW(
{
auto nn = caffe2::convertToNNModule(
net, {{"X", d}, {"Y", d}, {"W", d}, {"FAKE", d}});
},
std::exception);
}
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