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#pragma once
#include <ATen/core/jit_type.h>
#include <torch/csrc/jit/mobile/debug_info.h>
#include <torch/csrc/jit/mobile/function.h>
#include <torch/csrc/jit/mobile/method.h>
#include <torch/csrc/jit/mobile/quantization.h>
namespace torch {
namespace jit {
namespace mobile {
using Stack = std::vector<c10::IValue>;
// A CompilationUnit object is the one that gets executed by the lite
// interpreter.
//
// A CompilationUnit object contains a list of Method Objects. These are methods
// that appear in the original PyTorch Model. These method correspond to Python
// member functions of the Model class.
//
// Methods in turn contain a Function, and a back-pointer to the Module that
// owns this Method instance.
//
// A Function contains a Code Object (code_) which is defined in interpreter.h
//
// A Code object contains the following:
//
// std::vector<Instruction> instructions_;
// std::vector<c10::OperatorName> op_names_;
// std::vector<std::function<void(Stack&)>> operators_;
// std::vector<c10::IValue> constants_;
// std::vector<c10::TypePtr> types_;
// size_t register_size_; // Aggregated output size.
//
class CompilationUnit {
public:
void register_function(std::unique_ptr<Function> fn);
std::vector<std::unique_ptr<Function>>& methods() {
return methods_;
}
const std::vector<std::unique_ptr<Function>>& methods() const {
return methods_;
}
Function* find_function(const c10::QualifiedName& qn);
const Function* find_function(const c10::QualifiedName& qn) const;
void unsafeRemoveFunction(const int64_t index) {
methods_.erase(methods_.begin() + index);
}
private:
std::vector<std::unique_ptr<Function>> methods_;
};
// A Torch Mobile Module is a representation of the model (trained in case
// of inference). A Mobile Module contains
//
// 1. data (object_)
// 2. metadata (optional) about the model (metadata_ from the metadata.pkl
// file added after training)
// 3. Compilation Unit (cu_)
//
class TORCH_API Module {
public:
Module(
// NOLINTNEXTLINE(modernize-pass-by-value)
c10::intrusive_ptr<c10::ivalue::Object> object,
std::shared_ptr<CompilationUnit> cu)
: object_(object), cu_(std::move(cu)) {}
Module() = default;
Method get_method(const std::string& method_name) const;
template <typename... Types>
c10::IValue run_method(const std::string& method_name, Types&&... args) {
return get_method(method_name)({IValue(std::forward<Types>(args))...});
}
c10::IValue forward(std::vector<c10::IValue> inputs) {
return get_method("forward")(std::move(inputs));
}
c10::optional<Method> find_method(const std::string& basename) const;
const std::string name() const {
return object_->name();
}
const std::vector<at::IValue>& slots() const {
return object_->slots();
}
const c10::intrusive_ptr<c10::ivalue::Object> _ivalue() const {
return object_;
}
const std::vector<at::Tensor> parameters() const;
const std::map<std::string, at::Tensor> named_parameters() const;
std::string get_forward_method_debug_info(int64_t debug_handle) const;
std::string getModuleHierarchy(const int64_t debug_handle) const;
std::string getCallStack(const int64_t debug_handle) const;
/// Enables "training" mode.
void train(bool on = true);
/// Calls train(false) to enable "eval" mode.
void eval() {
train(/*on=*/false);
}
/// True if the module is in training mode.
bool is_training() const;
const std::unordered_map<std::string, std::string> getMetadata() const {
return metadata_;
}
void setMetadata(
const std::unordered_map<std::string, std::string>& metadata) {
metadata_ = metadata;
}
const std::vector<Method> get_methods() const;
c10::IValue attr(const std::string& name, c10::IValue or_else) const {
if (auto r = object_->type()->findAttributeSlot(name)) {
return object_->getSlot(*r);
}
if (auto r = object_->type()->findConstantSlot(name)) {
return object_->type()->getConstant(*r);
}
return or_else;
}
void setDebugTable(MobileDebugTable&& debug_table) {
debug_table_ = std::move(debug_table);
}
const MobileDebugTable& getDebugTable() const {
return debug_table_;
}
void setHasDebugHandles(bool has_debug_handles) {
has_debug_handles_ = has_debug_handles;
}
bool hasDebugHandles() const {
return has_debug_handles_;
}
const CompilationUnit& compilation_unit() const {
return *cu_.get();
}
void set_delete_memory(std::shared_ptr<char> delete_mem) {
mem_to_delete_ = delete_mem;
}
void set_min_operator_version(int64_t version) {
min_operator_version_ = version;
}
int64_t min_operator_version() const {
return min_operator_version_;
}
void set_bytecode_version(int64_t version) {
bytecode_version_ = version;
}
int64_t bytecode_version() const {
return bytecode_version_;
}
private:
friend class quantization::PTQQuanizationHelper;
bool compareMethodSchemas(
const std::string& name_1,
const std::string& name_2);
void unsafeRemoveMethod(const std::string& basename);
void unsafeCopyMethod(
const std::string& new_method_name,
const Function& to_be_copied);
c10::intrusive_ptr<c10::ivalue::Object> object_;
std::unordered_map<std::string, std::string> metadata_;
std::shared_ptr<CompilationUnit> cu_;
MobileDebugTable debug_table_;
bool has_debug_handles_ = false;
int64_t min_operator_version_ = 4;
int64_t bytecode_version_ = 4;
// Extra handle for the module to delete when itself is deleted
std::shared_ptr<char> mem_to_delete_;
};
struct TORCH_API ModuleInfo {
uint64_t bytecode_version;
uint64_t operator_version;
std::unordered_map<std::string, int> opname_to_num_args;
std::unordered_set<std::string> function_names;
std::unordered_set<std::string> type_names;
};
TORCH_API ModuleInfo get_module_info(const mobile::Module& module);
} // namespace mobile
} // namespace jit
} // namespace torch
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