Files
pytorch/torch/csrc/jit/mobile/flatbuffer_loader.cpp
Richard Barnes fca0f34b83 Switch c10::string_view to std::string_view (#139635)
Shortens `string_view_starts_with` to `starts_with`. Adds some missing headers. Isolates `c10_string_view` to use with `get_fully_qualified_name`.

Test Plan: Sandcastle

Reviewed By: ezyang

Differential Revision: D64833558

Pull Request resolved: https://github.com/pytorch/pytorch/pull/139635
Approved by: https://github.com/Skylion007, https://github.com/ezyang
2024-11-27 01:41:18 +00:00

946 lines
32 KiB
C++

#ifdef FLATBUFFERS_VERSION_MAJOR
#error "flatbuffer_loader.h must not include any flatbuffers headers"
#endif // FLATBUFFERS_VERSION_MAJOR
#include <array>
#include <istream>
#include <memory>
#include <string>
#include <tuple>
#include <unordered_map>
#include <unordered_set>
#include <utility>
#include <vector>
#include <ATen/ATen.h>
#include <ATen/core/dynamic_type.h>
#include <ATen/core/ivalue.h>
#include <ATen/core/qualified_name.h>
#include <c10/core/CPUAllocator.h>
#include <c10/core/impl/alloc_cpu.h>
#include <c10/util/Exception.h>
#include <c10/util/ScopeExit.h>
#include <caffe2/serialize/inline_container.h>
#include <torch/csrc/jit/mobile/file_format.h>
#include <torch/csrc/jit/mobile/flatbuffer_loader.h>
#include <torch/csrc/jit/mobile/function.h>
#include <torch/csrc/jit/mobile/import.h>
#include <torch/csrc/jit/mobile/interpreter.h>
#include <torch/csrc/jit/mobile/module.h>
#include <torch/csrc/jit/mobile/observer.h>
#include <torch/csrc/jit/mobile/type_parser.h>
#include <torch/csrc/jit/runtime/instruction.h>
#include <torch/csrc/jit/serialization/export_bytecode.h>
#include <torch/csrc/jit/serialization/import_export_constants.h>
#include <torch/csrc/jit/serialization/import_read.h>
#include <torch/custom_class.h>
#include <optional>
#ifndef DISABLE_UPGRADER
#include <torch/csrc/jit/mobile/parse_bytecode.h>
#include <torch/csrc/jit/mobile/upgrader_mobile.h>
#endif
#ifdef _WIN32
#include <malloc.h>
#else
#include <cstdlib>
#endif
#if defined(FB_XPLAT_BUILD) || defined(FBCODE_CAFFE2)
#include <torch/csrc/jit/serialization/mobile_bytecode_generated_fbsource.h> // NOLINT
namespace flatbuffers = flatbuffers_fbsource;
#define FLATBUFFERS_MAX_ALIGNMENT FLATBUFFERS_FBSOURCE_MAX_ALIGNMENT
#else
#include <torch/csrc/jit/serialization/mobile_bytecode_generated.h> // NOLINT
#endif
namespace torch::jit {
// Our own alignment requirement does not need to be exactly the same as what
// flatbuffers supports, but what flatbuffers supports needs to satisfy our
// requirement.
static_assert(
kFlatbufferDataAlignmentBytes <= FLATBUFFERS_MAX_ALIGNMENT,
"Sizes must be compatible");
static_assert(
(kFlatbufferDataAlignmentBytes & ~(kFlatbufferDataAlignmentBytes - 1)) ==
kFlatbufferDataAlignmentBytes,
"Must be a power of 2");
namespace {
static constexpr std::string_view kCustomClassPrefix =
"__torch__.torch.classes";
static constexpr std::string_view kTorchPrefix = "__torch__";
static constexpr std::string_view kJitPrefix = "torch.jit";
class FlatbufferLoader final {
public:
FlatbufferLoader();
typedef IValue (
*IValueParser)(FlatbufferLoader&, const mobile::serialization::IValue&);
void registerIValueParser(
mobile::serialization::IValueUnion ivalue_type,
IValueParser parser);
mobile::Module parseModule(mobile::serialization::Module* module, char* end);
void extractJitSourceAndConstants(
ExtraFilesMap* jit_sources,
std::vector<IValue>* constants);
using TypeResolver = TypePtr (*)(
const std::string& type_str,
const std::shared_ptr<CompilationUnit>& cu);
void internal_registerTypeResolver(TypeResolver type_resolver);
IValue& getIValue(uint32_t pos) {
TORCH_CHECK(pos < all_ivalues_.size());
return all_ivalues_[pos];
}
mobile::Function* getFunction(uint32_t pos) {
return all_functions_[pos];
}
ClassTypePtr getType(uint32_t pos) {
TORCH_CHECK(pos < all_types_.size());
return all_types_[pos];
}
c10::Storage getStorage(uint32_t index);
TypePtr getOrCreateTypeAnnotations(const flatbuffers::String* offset);
ClassTypePtr getOrCreateClassTypeForObject(
const mobile::serialization::Object* object);
const mobile::serialization::Module* getCurrentFlatbufferInput() {
return module_;
}
void setShouldCopyTensorMemory(bool should_copy_tensor_memory) {
should_copy_tensor_memory_ = should_copy_tensor_memory;
}
std::shared_ptr<mobile::CompilationUnit> mcu_;
std::shared_ptr<CompilationUnit> cu_;
private:
IValue parseIValue(const mobile::serialization::IValue* ivalue);
std::unique_ptr<mobile::Function> parseFunction(
const mobile::serialization::Function* method);
void parseAndPopulate(
uint32_t i,
const mobile::serialization::IValue* ivalue);
std::unordered_map<uint32_t, mobile::Function*> all_functions_;
std::vector<ClassTypePtr> all_types_;
std::unordered_set<uint32_t> initialized_types_;
std::unordered_map<const flatbuffers::String*, TypePtr> type_annotations_;
std::vector<bool> storage_loaded_;
std::vector<c10::Storage> storages_;
std::vector<IValue> all_ivalues_;
std::array<
IValueParser,
static_cast<uint8_t>(mobile::serialization::IValueUnion::MAX) + 1>
ivalue_parsers_;
TypeResolver type_resolver_ = nullptr;
mobile::serialization::Module* module_ = nullptr;
bool module_parsed_ = false;
bool should_copy_tensor_memory_ = false;
// 0 -> mobile_ivalue_size_ elements are from the mobile module.
uint32_t mobile_ivalue_size_ = 0;
};
IValue parseList(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseTensor(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseTuple(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseDict(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseObject(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseIntList(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseDoubleList(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseBoolList(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseBasic(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
IValue parseEnum(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue);
TypePtr resolveType(
const std::string& type_string,
const std::shared_ptr<CompilationUnit>& cu) {
TypePtr type;
std::string_view type_str(type_string);
if (c10::starts_with(type_str, kCustomClassPrefix)) {
type = getCustomClass(type_string);
TORCH_CHECK(
type, "The implementation of class ", type_string, " cannot be found.");
} else if (
c10::starts_with(type_str, kTorchPrefix) ||
c10::starts_with(type_str, kJitPrefix)) {
c10::QualifiedName qn(type_string);
if (cu->get_class(qn) == nullptr) {
auto classtype = ClassType::create(qn, cu, true);
cu->register_type(classtype);
type = classtype;
} else {
type = cu->get_class(qn);
}
} else {
type = c10::parseType(type_string);
}
return type;
}
FlatbufferLoader::FlatbufferLoader()
: mcu_(std::make_shared<mobile::CompilationUnit>()),
cu_(std::make_shared<CompilationUnit>()),
ivalue_parsers_{nullptr} {
registerIValueParser(mobile::serialization::IValueUnion::NONE, &parseBasic);
registerIValueParser(mobile::serialization::IValueUnion::Int, &parseBasic);
registerIValueParser(mobile::serialization::IValueUnion::Bool, &parseBasic);
registerIValueParser(mobile::serialization::IValueUnion::Double, &parseBasic);
registerIValueParser(
mobile::serialization::IValueUnion::ComplexDouble, &parseBasic);
registerIValueParser(
mobile::serialization::IValueUnion::TensorMetadata, &parseTensor);
registerIValueParser(mobile::serialization::IValueUnion::String, &parseBasic);
registerIValueParser(mobile::serialization::IValueUnion::List, &parseList);
registerIValueParser(
mobile::serialization::IValueUnion::IntList, &parseIntList);
registerIValueParser(
mobile::serialization::IValueUnion::DoubleList, &parseDoubleList);
registerIValueParser(
mobile::serialization::IValueUnion::BoolList, &parseBoolList);
registerIValueParser(mobile::serialization::IValueUnion::Tuple, &parseTuple);
registerIValueParser(mobile::serialization::IValueUnion::Dict, &parseDict);
registerIValueParser(
mobile::serialization::IValueUnion::Object, &parseObject);
registerIValueParser(mobile::serialization::IValueUnion::Device, &parseBasic);
registerIValueParser(
mobile::serialization::IValueUnion::EnumValue, &parseEnum);
internal_registerTypeResolver(&resolveType);
}
void FlatbufferLoader::registerIValueParser(
mobile::serialization::IValueUnion ivalue_type,
IValueParser parser) {
ivalue_parsers_[static_cast<uint8_t>(ivalue_type)] = parser;
}
void FlatbufferLoader::internal_registerTypeResolver(
TypeResolver type_resolver) {
type_resolver_ = type_resolver;
}
void parseExtraFilesFromVector(
const flatbuffers::Vector<flatbuffers::Offset<
torch::jit::mobile::serialization::ExtraFile>>* files,
ExtraFilesMap* extra_files) {
for (uint32_t i = 0; i < files->size(); ++i) {
const auto* extra_file = files->Get(i);
(*extra_files)[extra_file->name()->str()] = extra_file->content()->str();
}
}
void parseExtraFiles(
mobile::serialization::Module* module,
ExtraFilesMap& extra_files) {
auto extra_files_offsets = module->extra_files();
parseExtraFilesFromVector(extra_files_offsets, &extra_files);
}
void FlatbufferLoader::parseAndPopulate(
uint32_t i,
const mobile::serialization::IValue* ivalue) {
if (const auto* func = ivalue->val_as_Function()) {
auto func_ptr = parseFunction(func);
all_functions_[i] = func_ptr.get();
mcu_->register_function(std::move(func_ptr));
} else {
all_ivalues_[i] = parseIValue(ivalue);
}
}
mobile::Module FlatbufferLoader::parseModule(
mobile::serialization::Module* module,
char* end) {
module_ = module;
all_ivalues_.clear();
all_types_.clear();
storages_.clear();
storage_loaded_.clear();
module_parsed_ = false;
const auto* ivalues = module->ivalues();
TORCH_CHECK(
ivalues && module->object_types(),
"Parsing flatbuffer module: Corrupted ivalues/object_types field");
TORCH_CHECK(
reinterpret_cast<const char*>(ivalues) < end, "Corrupted ivalues field");
TORCH_CHECK(
module->storage_data_size() >= 0,
"Parsing flatbuffer module: illegal storage_data_size: ",
module->storage_data_size(),
", expected to be non negative");
all_ivalues_.resize(ivalues->size());
all_types_.resize(module->object_types()->size());
storages_.resize(module->storage_data_size());
storage_loaded_.resize(module->storage_data_size(), false);
mobile_ivalue_size_ = module_->mobile_ivalue_size();
if (mobile_ivalue_size_ == 0 || mobile_ivalue_size_ > ivalues->size()) {
mobile_ivalue_size_ = ivalues->size();
}
for (uint32_t i = 0; i < mobile_ivalue_size_; i++) {
const auto* ival = ivalues->Get(i);
TORCH_CHECK(
reinterpret_cast<const char*>(ival) < end, "Corrupted ivalue item")
parseAndPopulate(i, ival);
}
IValue& module_ivalue = getIValue(module->state_obj());
// register functions
for (const auto& f : all_functions_) {
uint32_t class_index =
ivalues->Get(f.first)->val_as_Function()->class_type();
ClassTypePtr class_type = all_types_[class_index];
class_type->addMethod(f.second);
}
module_parsed_ = true;
auto m = mobile::Module(module_ivalue.toObject(), mcu_);
m.set_min_operator_version(module->operator_version());
m.set_bytecode_version(module->bytecode_version());
return m;
}
void appendUpgraderFunctions(mobile::Function* function) {
#ifndef DISABLE_UPGRADER
for (auto& byteCodeFunctionWithOperator : getUpgraderBytecodeList()) {
function->append_function(byteCodeFunctionWithOperator.function);
}
#endif
}
std::unique_ptr<mobile::Function> FlatbufferLoader::parseFunction(
const mobile::serialization::Function* method) {
auto function = std::make_unique<mobile::Function>(
c10::QualifiedName(method->qn()->str()));
// TODO(qihan) add debug handle
// const auto* debug_handle = method->debug_info()->debug_handle();
for (const auto* inst : *method->instructions()) {
function->append_instruction(
static_cast<OpCode>(inst->op()), inst->x(), inst->n());
}
for (uint32_t i : *method->constants()) {
function->append_constant(getIValue(i));
}
appendUpgraderFunctions(function.get());
// 2. Decides if upgrader is needed
const uint32_t operator_version = module_->operator_version();
bool use_upgrader =
(operator_version < caffe2::serialize::kProducedFileFormatVersion);
for (const auto* op : *method->operators()) {
std::optional<int> num_args = std::nullopt;
if (op->num_args_serialized() > -1) {
num_args = op->num_args_serialized();
}
function->append_operator(
op->name()->str(), op->overload_name()->str(), num_args);
}
function->initialize_operators(true);
for (const auto i : *method->type_annotations()) {
function->append_type(getOrCreateTypeAnnotations(i));
}
// 3. If upgrader is needed, change change the OP instrunction to CALL
// instruction (In next PR, use_upgrader will be parsed to parseInstruction
// function and do the actual change)
if (use_upgrader) {
#ifndef DISABLE_UPGRADER
applyUpgrader(function.get(), operator_version);
#endif
}
function->set_register_size(method->register_size());
if (method->schema()) {
try {
auto parseArgList = [this](const auto* args_fb) {
std::vector<c10::Argument> args;
for (const auto* arg_tb : *args_fb) {
IValue default_value = getIValue(arg_tb->default_value());
TypePtr type_ptr = getOrCreateTypeAnnotations(arg_tb->type());
auto arg = c10::Argument(
arg_tb->name()->str(),
std::move(type_ptr),
std::nullopt /*N*/,
std::move(default_value));
args.emplace_back(std::move(arg));
}
return args;
};
c10::FunctionSchema schema(
method->qn()->str(),
"" /*overload_name*/,
parseArgList(method->schema()->arguments()),
parseArgList(method->schema()->returns()),
false /*is_varargs*/,
false /*is_varret*/);
function->setSchema(std::move(schema));
} catch (const c10::Error& e) {
}
}
return function;
}
IValue parseEnum(
FlatbufferLoader& loader,
const mobile::serialization::IValue& ivalue) {
const auto* enum_val = ivalue.val_as_EnumValue();
auto enum_type = loader.getOrCreateTypeAnnotations(enum_val->type_name())
->cast<c10::EnumType>();
AT_ASSERT(
enum_type,
"Enum with type: " + enum_val->type_name()->str() + " not found.");
IValue val = loader.getIValue(enum_val->value());
for (const auto& p : enum_type->enumNamesValues()) {
if (p.second == val) {
auto enum_holder = c10::make_intrusive<at::ivalue::EnumHolder>(
enum_type, p.first, p.second);
return IValue(std::move(enum_holder));
}
}
AT_ASSERT(
false, "Enum with type: " + enum_val->type_name()->str() + " not found.");
}
IValue parseBasic(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue) {
switch (ivalue.val_type()) {
case mobile::serialization::IValueUnion::NONE:
return {};
case mobile::serialization::IValueUnion::Int:
return ivalue.val_as_Int()->int_val();
case mobile::serialization::IValueUnion::Bool:
return ivalue.val_as_Bool()->bool_val();
case mobile::serialization::IValueUnion::Double:
return ivalue.val_as_Double()->double_val();
case mobile::serialization::IValueUnion::ComplexDouble: {
const auto* comp = ivalue.val_as_ComplexDouble();
return c10::complex<double>(comp->real(), comp->imag());
}
case mobile::serialization::IValueUnion::String:
return ivalue.val_as_String()->data()->str();
case mobile::serialization::IValueUnion::Device: {
return c10::Device(ivalue.val_as_Device()->str()->str());
}
default:
return {};
}
}
at::Tensor parseTensorFromMetadata(
FlatbufferLoader* loader,
const mobile::serialization::TensorMetadata* tensor_md) {
auto type = static_cast<at::ScalarType>(tensor_md->scalar_type());
auto options = at::device(at::kCPU).dtype(type);
at::Tensor tensor;
if (tensor_md->quantized_schema() != nullptr) {
// is quantized
const auto* schema = tensor_md->quantized_schema();
auto qscheme_type = static_cast<at::QScheme>(schema->qscheme());
switch (qscheme_type) {
case at::kPerTensorAffine: {
tensor = at::_empty_affine_quantized(
{0}, options, schema->scale(), schema->zero_point());
} break;
case at::kPerChannelAffineFloatQParams:
case at::kPerChannelAffine: {
at::Tensor scales = parseTensorFromMetadata(loader, schema->scales());
at::Tensor zero_points =
parseTensorFromMetadata(loader, schema->zero_points());
tensor = at::_empty_per_channel_affine_quantized(
{0}, scales, zero_points, schema->axis(), options);
} break;
default:
TORCH_CHECK(
false,
"Unsupported tensor quantization type in serialization ",
toString(qscheme_type));
break;
}
} else {
tensor = at::empty({0}, options);
}
at::TensorImpl* impl = tensor.unsafeGetTensorImpl();
c10::Storage storage;
storage = loader->getStorage(tensor_md->storage_location_index());
impl->set_storage_keep_dtype(storage);
impl->set_storage_offset(tensor_md->storage_offset());
std::vector<int64_t> size{
tensor_md->sizes()->begin(), tensor_md->sizes()->end()};
std::vector<int64_t> stride{
tensor_md->strides()->begin(), tensor_md->strides()->end()};
impl->set_sizes_and_strides(size, stride);
#ifndef MIN_EDGE_RUNTIME
tensor = autograd::make_variable(tensor, tensor_md->requires_grad());
#endif
return tensor;
}
IValue parseTensor(
FlatbufferLoader& loader,
const mobile::serialization::IValue& ivalue) {
const mobile::serialization::TensorMetadata* tensor_md =
ivalue.val_as_TensorMetadata();
return parseTensorFromMetadata(&loader, tensor_md);
}
IValue parseList(
FlatbufferLoader& loader,
const mobile::serialization::IValue& ivalue) {
const mobile::serialization::List* list = ivalue.val_as_List();
auto res = c10::impl::GenericList(AnyType::get());
for (auto i : *list->items()) {
res.emplace_back(loader.getIValue(i));
}
auto type = loader.getOrCreateTypeAnnotations(list->annotation_str());
res.unsafeSetElementType(type->containedType(0));
return res;
}
template <typename T, typename U>
std::vector<T> parseListNative(const U* list) {
TORCH_INTERNAL_ASSERT_DEBUG_ONLY(list != nullptr);
return {list->items()->begin(), list->items()->end()};
}
IValue parseIntList(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue) {
const auto& list = ivalue.val_as_IntList();
return parseListNative<int64_t>(list);
}
IValue parseDoubleList(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue) {
const auto& list = ivalue.val_as_DoubleList();
return parseListNative<double>(list);
}
IValue parseBoolList(
FlatbufferLoader&,
const mobile::serialization::IValue& ivalue) {
const auto& list = ivalue.val_as_BoolList();
std::vector<uint8_t> res = parseListNative<uint8_t>(list);
c10::List<bool> boollist;
for (auto x : res) {
boollist.push_back(x);
}
return boollist;
}
IValue parseTuple(
FlatbufferLoader& loader,
const mobile::serialization::IValue& ivalue) {
const auto& tuple = ivalue.val_as_Tuple();
const auto items = tuple->items();
std::vector<IValue> res;
res.reserve(items->size());
for (auto i : *items) {
res.emplace_back(loader.getIValue(i));
}
return c10::ivalue::Tuple::create(std::move(res));
}
IValue parseDict(
FlatbufferLoader& loader,
const mobile::serialization::IValue& ivalue) {
const auto* dict = ivalue.val_as_Dict();
auto result = c10::impl::GenericDict(AnyType::get(), AnyType::get());
const auto* keys = dict->keys();
const auto* values = dict->values();
for (size_t i = 0; i < keys->size(); ++i) {
uint32_t key = keys->Get(i);
uint32_t val = values->Get(i);
result.insert_or_assign(loader.getIValue(key), loader.getIValue(val));
}
auto type = loader.getOrCreateTypeAnnotations(dict->annotation_str());
result.unsafeSetKeyType(type->containedType(0));
result.unsafeSetValueType(type->containedType(1));
return result;
}
ClassTypePtr FlatbufferLoader::getOrCreateClassTypeForObject(
const mobile::serialization::Object* object) {
auto cls = getType(object->type_index());
const mobile::serialization::ObjectType* obj_type =
module_->object_types()->Get(object->type_index());
if (cls == nullptr) {
std::string_view qn_str(
obj_type->type_name()->c_str(), obj_type->type_name()->size());
if (c10::starts_with(qn_str, kTorchPrefix) ||
c10::starts_with(qn_str, kJitPrefix)) {
c10::QualifiedName qn(obj_type->type_name()->str());
cls = cu_->get_class(qn);
if (cls == nullptr) {
cls = ClassType::create(qn, cu_, true);
cu_->register_type(cls);
}
} else {
cls = c10::parseType(std::string(qn_str))->cast<ClassType>();
}
TORCH_CHECK(object->type_index() < all_ivalues_.size());
all_types_[object->type_index()] = cls;
if (obj_type->type() == mobile::serialization::TypeType::CLASS_WITH_FIELD) {
for (uint32_t i = 0; i < object->attrs()->size(); i++) {
IValue val = getIValue(object->attrs()->Get(i));
// Need to use concrete object's field's type to set type of field.
cls->addAttribute(
obj_type->attr_names()->Get(i)->str(),
val.type<c10::DynamicType>());
}
}
initialized_types_.insert(object->type_index());
}
return cls;
}
IValue parseObject(
FlatbufferLoader& loader,
const mobile::serialization::IValue& ivalue) {
const mobile::serialization::Object* object = ivalue.val_as_Object();
TORCH_INTERNAL_ASSERT_DEBUG_ONLY(object != nullptr);
const auto* cur_input = loader.getCurrentFlatbufferInput();
const mobile::serialization::ObjectType* obj_type =
cur_input->object_types()->Get(object->type_index());
auto cls = loader.getOrCreateClassTypeForObject(object);
Stack stack;
switch (obj_type->type()) {
case mobile::serialization::TypeType::CLASS_WITH_FIELD: {
auto obj = c10::ivalue::Object::create(
at::StrongTypePtr(loader.cu_, cls), object->attrs()->size());
for (uint32_t i = 0; i < object->attrs()->size(); i++) {
IValue val = loader.getIValue(object->attrs()->Get(i));
obj->setSlot(i, std::move(val));
}
return obj;
}
case mobile::serialization::TypeType::CLASS_WITH_SETSTATE: {
IValue input = loader.getIValue(object->state());
mobile::Function* setstate = loader.getFunction(object->setstate_func());
auto obj =
c10::ivalue::Object::create(at::StrongTypePtr(loader.cu_, cls), 0);
stack.emplace_back(obj);
stack.emplace_back(std::move(input));
setstate->run(stack);
return obj;
}
case mobile::serialization::TypeType::CUSTOM_CLASS: {
auto custom_class_type =
torch::jit::getCustomClass(cls->name()->qualifiedName());
IValue input = loader.getIValue(object->state());
auto obj = c10::ivalue::Object::create(
c10::StrongTypePtr(nullptr, custom_class_type), 1);
stack.emplace_back(obj);
stack.emplace_back(std::move(input));
custom_class_type->getMethod("__setstate__").run(stack);
return obj;
}
default:
AT_ASSERT(false, "need to be object");
}
}
IValue FlatbufferLoader::parseIValue(
const mobile::serialization::IValue* ivalue) {
return ivalue_parsers_[static_cast<uint32_t>(ivalue->val_type())](
*this, *ivalue);
}
void deleteNothing2(void*);
void deleteNothing2(void*) {}
c10::Storage FlatbufferLoader::getStorage(uint32_t index) {
TORCH_CHECK(index < storage_loaded_.size());
TORCH_CHECK(index < storages_.size());
if (!storage_loaded_[index]) {
auto* storage = module_->storage_data()->GetMutableObject(index);
size_t size = storage->data()->size();
at::DataPtr data;
if (should_copy_tensor_memory_) {
auto* allocator = at::GetCPUAllocator();
data = allocator->allocate(size);
memcpy(data.get(), storage->data()->data(), size);
} else {
void* ptr = static_cast<void*>(storage->mutable_data()->data());
data = at::DataPtr(ptr, ptr, deleteNothing2, DeviceType::CPU);
}
storages_[index] =
c10::Storage(c10::Storage::use_byte_size_t(), size, std::move(data));
storage_loaded_[index] = true;
}
return storages_[index];
}
TypePtr FlatbufferLoader::getOrCreateTypeAnnotations(
const flatbuffers::String* offset) {
auto iter = type_annotations_.find(offset);
if (iter != type_annotations_.end()) {
return iter->second;
}
TypePtr type = type_resolver_(offset->str(), cu_);
type_annotations_[offset] = type;
return type;
}
void FlatbufferLoader::extractJitSourceAndConstants(
ExtraFilesMap* jit_sources,
std::vector<IValue>* constants) {
AT_ASSERT(
module_parsed_,
"Need to first parse a flatbuffer file before extracting jit_sources");
const auto* ivalues = module_->ivalues();
for (uint32_t i = mobile_ivalue_size_; i < ivalues->size(); i++) {
const auto* ival = ivalues->Get(i);
parseAndPopulate(i, ival);
}
// register functions
for (const auto& f : all_functions_) {
if (f.first >= mobile_ivalue_size_) {
uint32_t class_index =
ivalues->Get(f.first)->val_as_Function()->class_type();
ClassTypePtr class_type = all_types_[class_index];
class_type->addMethod(f.second);
}
}
const auto* jit_constants = module_->jit_constants();
for (const auto i : c10::irange(jit_constants->size())) {
constants->emplace_back(getIValue(jit_constants->Get(i)));
}
parseExtraFilesFromVector(module_->jit_sources(), jit_sources);
}
} // namespace
mobile::Module parse_and_initialize_mobile_module(
void* data,
size_t size,
std::optional<at::Device>,
ExtraFilesMap* extra_files,
bool should_copy_tensor_memory) {
// TODO(T128189662): If not copying, enforce that data is aligned to
// kFlatbufferDataAlignmentBytes, and add unit tests.
// Validate Flatbuffer module before parsing.
flatbuffers::Verifier verifier(reinterpret_cast<uint8_t*>(data), size);
TORCH_CHECK(
mobile::serialization::VerifyModuleBuffer(verifier),
"Malformed Flatbuffer module");
FlatbufferLoader loader;
loader.setShouldCopyTensorMemory(should_copy_tensor_memory);
// Flatbuffer doesn't seem to have a way to provide the buffer size when
// interacting with the buffer.
auto* flatbuffer_module = mobile::serialization::GetMutableModule(data);
auto* end = static_cast<char*>(data) + size;
mobile::Module m = loader.parseModule(flatbuffer_module, end);
if (extra_files != nullptr) {
parseExtraFiles(flatbuffer_module, *extra_files);
}
return m;
}
mobile::Module parse_and_initialize_mobile_module(
std::shared_ptr<char> data,
size_t size,
std::optional<at::Device> device,
ExtraFilesMap* extra_files) {
mobile::Module m = parse_and_initialize_mobile_module(
data.get(),
size,
device,
extra_files,
/*should_copy_tensor_memory=*/false);
m.set_delete_memory(std::move(data));
return m;
}
mobile::Module parse_and_initialize_mobile_module_for_jit(
void* data,
size_t size,
ExtraFilesMap& jit_sources,
std::vector<IValue>& jit_constants,
std::optional<at::Device>,
ExtraFilesMap* extra_files) {
TORCH_CHECK(
mobile::serialization::ModuleBufferHasIdentifier(data), "Format error");
// TODO(T128189662): Enforce that data is aligned to
// kFlatbufferDataAlignmentBytes, and add unit tests.
// Validate Flatbuffer module before parsing.
flatbuffers::Verifier verifier(reinterpret_cast<uint8_t*>(data), size);
TORCH_CHECK(
mobile::serialization::VerifyModuleBuffer(verifier),
"Malformed Flatbuffer module");
FlatbufferLoader loader;
auto* flatbuffer_module = mobile::serialization::GetMutableModule(data);
auto* end = static_cast<char*>(data) + size;
mobile::Module m = loader.parseModule(flatbuffer_module, end);
if (extra_files != nullptr) {
parseExtraFiles(flatbuffer_module, *extra_files);
}
loader.extractJitSourceAndConstants(&jit_sources, &jit_constants);
return m;
}
mobile::Module load_mobile_module_from_file(
const std::string& filename,
std::optional<c10::Device> device,
ExtraFilesMap* extra_files) {
auto [data, size] = get_file_content(filename.c_str());
return parse_and_initialize_mobile_module(
std::move(data), size, device, extra_files);
}
uint64_t get_bytecode_version(std::istream& in) {
auto [data, size] = get_stream_content(in);
return get_bytecode_version_from_bytes(data.get());
}
uint64_t get_bytecode_version(const std::string& filename) {
auto [data, size] = get_file_content(filename.c_str());
return get_bytecode_version_from_bytes(data.get());
}
uint64_t get_bytecode_version_from_bytes(char* flatbuffer_content) {
TORCH_CHECK(
mobile::serialization::ModuleBufferHasIdentifier(flatbuffer_content),
"Format error");
auto* flatbuffer_module =
mobile::serialization::GetMutableModule(flatbuffer_content);
return flatbuffer_module->bytecode_version();
}
mobile::ModuleInfo get_module_info_from_flatbuffer(char* flatbuffer_content) {
auto* ff_module = mobile::serialization::GetMutableModule(flatbuffer_content);
mobile::ModuleInfo minfo;
minfo.operator_version = ff_module->operator_version();
minfo.bytecode_version = ff_module->bytecode_version();
uint32_t mobile_ivalue_size = ff_module->mobile_ivalue_size();
if (mobile_ivalue_size == 0) {
mobile_ivalue_size = ff_module->ivalues()->size();
}
std::vector<std::string> type_name_list;
for (uint32_t i = 0; i < mobile_ivalue_size; i++) {
const auto* ival = ff_module->ivalues()->Get(i);
if (const auto* func = ival->val_as_Function()) {
minfo.function_names.insert(func->qn()->str());
for (const auto* op : *func->operators()) {
at::OperatorName opname(op->name()->str(), op->overload_name()->str());
minfo.opname_to_num_args[mobile::operator_str(opname)] =
op->num_args_serialized();
}
for (const auto* type_ann : *func->type_annotations()) {
type_name_list.push_back(type_ann->str());
}
}
}
c10::TypeParser parser(type_name_list);
parser.parseList();
minfo.type_names = parser.getContainedTypes();
return minfo;
}
mobile::Module load_mobile_module_from_stream_with_copy(
std::istream& in,
std::optional<at::Device> device,
ExtraFilesMap* extra_files) {
auto [data, size] = get_stream_content(in);
return parse_and_initialize_mobile_module(
std::move(data), size, device, extra_files);
}
mobile::Module parse_flatbuffer_no_object(
std::shared_ptr<char> data,
size_t size,
std::optional<at::Device> device) {
(void)device;
(void)size;
// Validate Flatbuffer module before parsing.
flatbuffers::Verifier verifier(reinterpret_cast<uint8_t*>(data.get()), size);
TORCH_CHECK(
mobile::serialization::VerifyModuleBuffer(verifier),
"Malformed Flatbuffer module");
auto* flatbuffer_module = mobile::serialization::GetMutableModule(data.get());
FlatbufferLoader loader;
// replace parserObject with to handle only class with field case
// function.
loader.registerIValueParser(
mobile::serialization::IValueUnion::Object,
+[](FlatbufferLoader& loader,
const mobile::serialization::IValue& ivalue) {
const mobile::serialization::Object* object = ivalue.val_as_Object();
auto cls = loader.getOrCreateClassTypeForObject(object);
auto obj = c10::ivalue::Object::create(
at::StrongTypePtr(loader.cu_, cls), object->attrs()->size());
for (uint32_t i = 0; i < object->attrs()->size(); i++) {
IValue val = loader.getIValue(object->attrs()->Get(i));
obj->setSlot(i, std::move(val));
}
return static_cast<c10::IValue>(obj);
});
auto* end = data.get() + size;
mobile::Module m = loader.parseModule(flatbuffer_module, end);
m.set_delete_memory(std::move(data));
return m;
}
bool register_flatbuffer_loader() {
return true;
}
} // namespace torch::jit