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#include <torch/csrc/jit/mobile/module.h>
#include <torch/csrc/jit/mobile/interpreter.h>
#include <torch/csrc/jit/mobile/observer.h>
#include <torch/csrc/jit/runtime/jit_exception.h>
#include <exception>
#include <ATen/record_function.h>
namespace torch {
namespace jit {
std::ostream& operator<<(std::ostream& out, Instruction inst);
namespace mobile {
void CompilationUnit::register_function(std::unique_ptr<Function> fn) {
methods_.emplace_back(std::move(fn));
}
Function* CompilationUnit::find_function(const c10::QualifiedName& qn) {
for (auto& fn : methods_) {
if (fn->qualname() == qn) {
return fn.get();
}
}
return nullptr;
}
Method Module::get_method(const std::string& name) const {
if (auto method = find_method(name)) {
return *method;
}
AT_ERROR("Method '", name, "' is not defined.");
}
c10::optional<Method> Module::find_method(const std::string& basename) const {
for (auto& fn : cu_->methods()) {
if (fn->name() == basename) {
return c10::make_optional<Method>(Method(this, fn.get()));
}
}
return c10::nullopt;
}
namespace {
void set_train_recurse(
const c10::intrusive_ptr<c10::ivalue::Object>& obj,
bool on) {
if (auto slot = obj->type()->findAttributeSlot("training")) {
obj->setSlot(*slot, on);
} else {
TORCH_INTERNAL_ASSERT(false, "'training' attribute not found");
}
for (const auto& slot : obj->slots()) {
if (slot.isObject()) {
set_train_recurse(slot.toObject(), on);
}
}
}
void slot_params_recurse(
const c10::intrusive_ptr<c10::ivalue::Object>& obj,
std::vector<at::Tensor>* params) {
for (const auto& slot : obj->slots()) {
if (slot.isTensor()) {
params->emplace_back(slot.toTensor());
} else if (slot.isObject()) {
slot_params_recurse(slot.toObject(), params);
}
}
}
void slot_named_params_recurse(
const c10::intrusive_ptr<c10::ivalue::Object>& obj,
std::map<std::string, at::Tensor>* params,
const std::string& parent_name) {
auto slots = obj->slots();
size_t nslots = slots.size();
for (size_t i = 0; i < nslots; ++i) {
auto slot = slots[i];
std::string name =
parent_name.size() == 0 ? parent_name : parent_name + ".";
name += obj->type()->getAttributeName(i);
if (slot.isTensor()) {
(*params)[name] = slot.toTensor();
} else if (slot.isObject()) {
slot_named_params_recurse(slot.toObject(), params, name);
}
}
}
} // namespace
const std::vector<at::Tensor> Module::parameters() const {
std::vector<at::Tensor> params;
slot_params_recurse(object_, ¶ms);
return params;
}
const std::map<std::string, at::Tensor> Module::named_parameters() const {
std::map<std::string, at::Tensor> params;
const std::string name = "";
slot_named_params_recurse(object_, ¶ms, name);
return params;
}
std::string Module::get_forward_method_debug_info(size_t pc) const {
return find_method("forward")->get_module_debug_info(pc);
}
void Module::train(bool on) {
set_train_recurse(object_, on);
}
bool Module::is_training() const {
if (auto slot = object_->type()->findAttributeSlot("training")) {
return object_->getSlot(*slot).toBool();
}
return true;
}
Method::Method(const Module* owner, Function* function)
: owner_(owner), function_(function) {}
void Method::run(Stack& stack) {
auto observer = torch::observerConfig().getModuleObserver();
/* if the metadata dict doesn't contain "model_name", copy the metadata and
set the value of "model_name" as name() */
std::unordered_map<std::string, std::string> copied_metadata =
owner_->metadata();
if (owner_->metadata().find("model_name") == owner_->metadata().end()) {
copied_metadata["model_name"] = owner_->name();
}
if (observer) {
observer->onEnterRunMethod(copied_metadata, function_->name());
}
auto debug_info = std::make_shared<MobileDebugInfo>();
std::string name = copied_metadata["model_name"];
debug_info->setModelName(name);
debug_info->setMethodName(function_->name());
at::DebugInfoGuard guard(at::DebugInfoKind::MOBILE_RUNTIME_INFO, debug_info);
try {
stack.insert(stack.begin(), owner_->_ivalue());
function_->run(stack);
if (observer) {
observer->onExitRunMethod();
}
} catch (c10::Error& error) {
if (observer) {
observer->onFailRunMethod(error.what());
}
TORCH_RETHROW(error);
} catch (...) {
auto currentException = std::current_exception();
try {
if (!currentException) {
TORCH_CHECK(false, "Unknown exception");
} else {
try {
std::rethrow_exception(currentException);
} catch (const std::exception& e) {
TORCH_CHECK(false, e.what());
}
}
} catch (c10::Error& error) {
if (observer) {
observer->onFailRunMethod(error.what());
}
TORCH_RETHROW(error);
}
}
}
c10::IValue Method::operator()(std::vector<IValue> stack) {
run(stack);
TORCH_INTERNAL_ASSERT(!stack.empty());
return stack.front();
}
} // namespace mobile
} // namespace jit
} // namespace torch
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