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#pragma once
#include <ATen/core/ivalue.h>
#include <c10/macros/Export.h>
#include <torch/csrc/jit/mobile/compatibility/runtime_compatibility.h>
#include <istream>
#include <memory>
#include <unordered_map>
#include <vector>
namespace caffe2::serialize {
class PyTorchStreamReader;
class ReadAdapterInterface;
} // namespace caffe2::serialize
namespace torch::jit {
// The family of methods below to get bytecode version from a model
// Throws if not passed in a well formed model
TORCH_API uint64_t _get_model_bytecode_version(std::istream& in);
TORCH_API uint64_t _get_model_bytecode_version(const std::string& filename);
TORCH_API uint64_t _get_model_bytecode_version(
const std::shared_ptr<caffe2::serialize::ReadAdapterInterface>& rai);
uint64_t _get_model_bytecode_version(
const std::vector<c10::IValue>& bytecode_ivalues);
// The family of methods below to get the operator version from a model
// Throws if not passed in a well formed model
TORCH_API uint64_t _get_model_operator_version(std::istream& in);
TORCH_API uint64_t _get_model_operator_version(const std::string& filename);
TORCH_API uint64_t _get_model_operator_version(
std::shared_ptr<caffe2::serialize::ReadAdapterInterface> rai);
// Utility Functions
std::vector<c10::IValue> get_bytecode_ivalues(
caffe2::serialize::PyTorchStreamReader& reader);
c10::IValue readArchive(
const std::string& archive_name,
caffe2::serialize::PyTorchStreamReader& stream_reader);
bool check_zip_file(
const std::shared_ptr<caffe2::serialize::ReadAdapterInterface>& rai);
// The family of methods below to get the root ops and information from a model
TORCH_API std::unordered_map<std::string, OperatorInfo> _get_model_ops_and_info(
std::istream& in);
TORCH_API std::unordered_map<std::string, OperatorInfo> _get_model_ops_and_info(
const std::string& filename);
TORCH_API std::unordered_map<std::string, OperatorInfo> _get_model_ops_and_info(
std::shared_ptr<caffe2::serialize::ReadAdapterInterface> rai);
// The family of methods below to get contained types from a model
// Throws if not passed in a well formed model
TORCH_API std::unordered_set<std::string> _get_mobile_model_contained_types(
std::istream& in);
TORCH_API std::unordered_set<std::string> _get_mobile_model_contained_types(
const std::string& filename);
TORCH_API std::unordered_set<std::string> _get_mobile_model_contained_types(
std::shared_ptr<caffe2::serialize::ReadAdapterInterface> rai);
std::unordered_set<std::string> _get_mobile_model_contained_types(
const std::vector<c10::IValue>& bytecode_ivalues);
// The family of methods below return the compatibility information of a model
struct ModelCompatibilityInfo {
uint64_t bytecode_version;
std::unordered_map<std::string, OperatorInfo> operator_info;
std::unordered_set<std::string> type_table;
uint64_t operator_version;
// Factory Methods
static TORCH_API ModelCompatibilityInfo get(std::istream& in);
static TORCH_API ModelCompatibilityInfo get(const std::string& filename);
static TORCH_API ModelCompatibilityInfo
get(std::shared_ptr<caffe2::serialize::ReadAdapterInterface> rai);
};
enum ModelCompatibilityStatus {
OK = 1,
ERROR = 2,
};
struct ModelCompatCheckResult {
ModelCompatibilityStatus status;
std::vector<std::string> errors{};
};
// Takes in information about a runtime and a model and returns if the two are
// compatible with one another.
TORCH_API ModelCompatCheckResult is_compatible(
RuntimeCompatibilityInfo runtime_info,
const ModelCompatibilityInfo& model_info);
} // namespace torch::jit
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