@@ -66,7 +66,7 @@ std::vector<char> pickle(

// This has to live here instead of the C++ API to mirror torch.save since the

// mobile build excludes the C++ API

std::vector<char> pickle_save(const at::IValue& ivalue) {

// Pickle the IValue into an array of bytes

std::vector<char> pickle_data;

Pickler pickler([&](const char* buf, size_t size) {

@@ -102,7 +102,7 @@ std::vector<char> pickle_save(const at::

#endif

}

size_t VectorReader::read(uint64_t pos, void* buf, size_t n, const char* what)

const {

std::copy(

@@ -123,7 +123,7 @@ size_t StringViewReader::read(

IValue pickle_load(const std::vector<char>& data) {

// Read in the pickle data

caffe2::serialize::PyTorchStreamReader reader(

std::make_unique<VectorReader>(data));

@@ -144,7 +144,7 @@ IValue pickle_load(const std::vector<cha

// A specialized version of pickle_load that can load custom objects.

c10::IValue pickle_load_obj(std::string_view data) {

caffe2::serialize::PyTorchStreamReader reader(

std::make_unique<torch::jit::StringViewReader>(data));

return torch::jit::readArchiveAndTensors(

@@ -106,7 +106,7 @@ TORCH_API IValue unpickle(

c10::TypePtr (*type_parser)(const std::string&) =

Unpickler::defaultTypeParser);

class VectorReader : public caffe2::serialize::ReadAdapterInterface {

public:

VectorReader(std::vector<char> data) : data_(std::move(data)) {}