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ivalue.h
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#pragma once
#include <ATen/core/TensorBody.h>
#include <ATen/core/blob.h>
#include <c10/util/C++17.h>
#include <c10/util/intrusive_ptr.h>
#include <torch/csrc/WindowsTorchApiMacro.h>
#include <typeindex>
namespace torch {
class TORCH_API CustomClassHolder : public c10::intrusive_ptr_target {};
namespace jit {
using ::torch::CustomClassHolder;
struct Function;
struct CompilationUnit;
struct Module;
} // namespace jit
} // namespace torch
namespace c10 {
template <class Key, class Value>
class Dict;
template <class T>
class List;
struct IValue;
struct ClassType;
struct Type;
class RRefInterface;
using TypePtr = std::shared_ptr<Type>;
struct ClassType;
using ClassTypePtr = std::shared_ptr<ClassType>;
TORCH_API bool _fastEqualsForContainer(const IValue& lhs, const IValue& rhs);
TORCH_API torch::jit::Function* checkObjectSortSchema(
const c10::ClassTypePtr& t,
std::stringstream& why_not);
// A comparator that checks ordering of two IValues of same type.
typedef std::function<bool(const IValue& a, const IValue& b)> IValueComparator;
TORCH_API IValueComparator getLessThanComparator(const IValue& v);
TORCH_API IValueComparator getGreaterThanComparator(const IValue& v);
namespace ivalue {
struct Tuple;
struct Future;
struct ConstantString;
struct GenericDict;
struct Object;
struct PyObjectHolder;
struct EnumHolder;
} // namespace ivalue
// This is an owning wrapper for a c10::optional<std::vector<T>>
// that can be implicitly converted to a (non-owning) optional<ArrayRef<T>>.
// Its purpose is to be used in generated code to keep the vector alive
// either until the end of a statement (as a temporary), or as a saved arg
// in autograd.
template <typename T>
struct OptionalArray {
c10::optional<std::vector<T>> list;
OptionalArray(){}
OptionalArray(std::vector<T> val) : list(std::move(val)) {}
// Used when saving an argument for the backwards pass.
OptionalArray& operator=(c10::optional<ArrayRef<T>> ref) {
if (ref) {
list = std::vector<T>(ref->begin(), ref->end());
} else {
list = nullopt;
}
return *this;
}
operator c10::optional<c10::ArrayRef<T>>() {
if (!list) {
return nullopt;
}
return *list;
}
};
// IValue is the generic tagged union used by the interpreter to hold
// all value types.
// It is a 16-byte object with an 8-byte payload and an 8-byte tag.
// The tag is currently 4 bytes to determine the type, and 1 byte
// to mark whether that type is a subtype of c10::intrusive_ptr_target and needs
// retain/release calls.
#define TORCH_FORALL_TAGS(_) \
_(None) \
_(Tensor) \
_(Double) \
_(Int) \
_(Bool) \
_(Tuple) \
_(String) \
_(Blob) \
_(GenericList) \
_(GenericDict) \
_(Future) \
_(Device) \
_(Stream) \
_(Object) \
_(PyObject) \
_(Uninitialized) \
_(Capsule) \
_(RRef) \
_(Quantizer) \
_(Generator) \
_(Enum)
// [doxygen private]
// These methods are not actually private but we don't want to document them, so
// they are marked `@private`, which hides them on the doxygen documentation for
// this page.
/// IValue (Interpreter Value) is a tagged union over the types supported by the
/// TorchScript interpreter. IValues contain their values as an
/// `IValue::Payload`, which holds primitive types (`int64_t`, `bool`, `double`,
/// `Device`), as values and all other types as a `c10::intrusive_ptr`.
///
/// IValues are used as inputs to and outputs from the TorchScript interpreter.
/// To retrieve the value contained within an IValue, use the `.toX()` methods,
/// where `X` is the type you are trying to get. Note that neither the `.toX()`
/// methods nor the templated `.to<T>` functions do any kind of casting, they
/// only unwrap the contained value. For example:
///
/// \rst
/// .. code-block:: cpp
///
/// // Make the IValue
/// torch::IValue my_ivalue(26);
/// std::cout << my_ivalue << "\n";
///
/// // Unwrap the IValue
/// int64_t my_int = my_ivalue.toInt()
/// std::cout << my_int << "\n";
///
/// // This will throw an error!
/// // `my_ivalue` is tagged as an int and cannot be used as another type
/// torch::Tensor my_tensor = my_ivalue.toTensor()
/// \endrst
struct CAFFE2_API IValue final {
IValue(const IValue& rhs)
: IValue(rhs.payload, rhs.tag, rhs.is_intrusive_ptr) {
if (is_intrusive_ptr) {
c10::raw::intrusive_ptr::incref(payload.as_intrusive_ptr);
}
}
IValue(IValue&& rhs) noexcept : IValue() {
swap(rhs);
}
/// @private [doxygen private]
~IValue() {
if (is_intrusive_ptr) {
c10::raw::intrusive_ptr::decref(payload.as_intrusive_ptr);
}
}
IValue& operator=(IValue&& rhs) & noexcept {
IValue(std::move(rhs)).swap(*this); // this also sets rhs to None
return *this;
}
IValue& operator=(IValue const& rhs) & {
IValue(rhs).swap(*this);
return *this;
}
void dump() const;
/**
* Equality comparison. The semantics are the same as Python's `==`:
* 1. Numerical types are compared by value.
* 2. Tensors compute element-wise equality, returning a BoolTensor (see:
* `torch.eq()`)
* 3. Strings are compared by value.
* 4. Sequence types (list, tuple) are compared lexicographically by
* comparing their elements. Different sequence types never compare equal.
* 5. Mappings (dict) must have equal (key, value) pairs.
* 6. If not listed above, the default behavior for is to test identity
* equality (e.g. pointer equality).
*
* Why does this return an IValue instead of a bool? Because in PyTorch,
* `tensor1 == tensor2` returns a `BoolTensor`, not a bool.
*
* NOTE: we (like Python) assume that identity equality implies value equality
* for efficiency.
* TODO: need to support customizing equality
*/
IValue equals(const IValue& rhs) const;
/**
* This implements the same semantics as `bool(lhs == rhs)` in Python. which
* is the same as `equals()` except for Tensor types.
*/
TORCH_API friend bool operator==(const IValue& lhs, const IValue& rhs);
TORCH_API friend bool operator!=(const IValue& lhs, const IValue& rhs);
/**
* Identity comparison. Checks if `this` is the same object as `rhs`. The
* semantics are the same as Python's `is` operator.
*
* NOTE: Like in Python, this operation is poorly defined for primitive types
* like numbers and strings. Prefer to use `==` unless you really want to
* check identity equality.
*/
bool is(const IValue& rhs) const;
/**
* @private [doxygen private]
* [container equality]
* This is an equality implementation that assumes objects with the same
* identity equal themselves, for efficiency reasons. We primarily have this
* for consistency, because Python does the same thing. This actually
* provokes user-visible changes in behavior due to quirks in torch:
* [tensor1] == [tensor1] -> True (because container equality will first
* compare identity) [tensor1] == [tensor1_copy] -> RuntimeError: bool value
* of Tensor is ambiguous
*/
TORCH_API friend bool _fastEqualsForContainer(
const IValue& lhs,
const IValue& rhs);
/// @private [doxygen private]
bool isAliasOf(const IValue& rhs) const {
if (this->tag != rhs.tag) {
// Trivially don't alias if the type is different
return false;
}
if (!this->is_intrusive_ptr) {
// Primitive types don't alias anything
return false;
}
AT_ASSERT(rhs.is_intrusive_ptr);
// Tensors should be compared based on internal storage
if (this->isTensor()) {
const auto thisTensor = this->toTensor();
const auto rhsTensor = rhs.toTensor();
return thisTensor.is_alias_of(rhsTensor);
}
// Other types can be compared by their ptr value
return this->payload.as_intrusive_ptr == rhs.payload.as_intrusive_ptr;
}
/// @private [doxygen private]
size_t use_count() const noexcept {
if (!is_intrusive_ptr) {
return 1;
}
return c10::raw::intrusive_ptr::use_count(payload.as_intrusive_ptr);
}
/// @private [doxygen private]
void swap(IValue& rhs) noexcept {
std::swap(payload, rhs.payload);
std::swap(is_intrusive_ptr, rhs.is_intrusive_ptr);
std::swap(tag, rhs.tag);
}
// Accessors for subtypes are arranged together below
// While some of these accessors could be generated through templates,
// we prefer to write them manually for clarity
IValue(at::Tensor t) : tag(Tag::Tensor), is_intrusive_ptr(t.defined()) {
// Note: the undefined tensor is not refcounted, so while it
// is tagged as a tensor, is_intrusive_ptr is set to false.
// This is not an optional optimization: our incref call
// *will not* do the right thing when called on an
// undefined tensor.
payload.as_intrusive_ptr = t.unsafeReleaseTensorImpl();
}
bool isTensor() const {
return Tag::Tensor == tag;
}
at::Tensor toTensor() &&;
at::Tensor toTensor() const&;
at::TensorImpl* unsafeToTensorImpl() const {
return static_cast<at::TensorImpl*>(payload.as_intrusive_ptr);
}
const IValue& toIValue() const {
return *this;
}
IValue& toIValue() {
return *this;
}
/// @private [doxygen private]
IValue(intrusive_ptr<caffe2::Blob> blob)
: tag(Tag::Blob), is_intrusive_ptr(true) {
// TODO (after Tensor merge) If we pass in a Blob holding a Tensor, extract
// and store it as a Tensor instead.
payload.as_intrusive_ptr = blob.release();
}
/// @private [doxygen private]
bool isBlob() const {
return Tag::Blob == tag;
}
/// @private [doxygen private]
c10::intrusive_ptr<caffe2::Blob> toBlob() &&;
/// @private [doxygen private]
c10::intrusive_ptr<caffe2::Blob> toBlob() const&;
// Capsule. Capsule is an internal implementation detail
// of custom C++ classes. No new callsites of these APIs should
// be introduced.
static inline IValue make_capsule(
intrusive_ptr<torch::CustomClassHolder> blob);
bool isCapsule() const {
return Tag::Capsule == tag;
}
c10::intrusive_ptr<torch::CustomClassHolder> toCapsule() &&;
c10::intrusive_ptr<torch::CustomClassHolder> toCapsule() const&;
// Custom C++ classes
template <
typename T,
std::enable_if_t<
std::is_base_of<torch::CustomClassHolder, T>::value,
int> = 0>
IValue(intrusive_ptr<T> custom_class);
bool isCustomClass() const;
template <typename T>
c10::intrusive_ptr<T> toCustomClass() &&;
template <typename T>
c10::intrusive_ptr<T> toCustomClass() const&;
// Tuple
IValue(c10::intrusive_ptr<ivalue::Tuple> v);
template <
typename... Args,
std::enable_if_t<
!guts::disjunction<
std::is_lvalue_reference<Args>...,
guts::negation<std::is_constructible<IValue, Args>>...>::value,
std::nullptr_t> = nullptr>
IValue(const std::tuple<Args...>& t);
bool isTuple() const {
return Tag::Tuple == tag;
}
c10::intrusive_ptr<ivalue::Tuple> toTuple() &&;
c10::intrusive_ptr<ivalue::Tuple> toTuple() const&;
// Double
IValue(double d) : tag(Tag::Double), is_intrusive_ptr(false) {
payload.as_double = d;
}
bool isDouble() const {
return Tag::Double == tag;
}
double toDouble() const {
AT_ASSERT(isDouble());
return payload.as_double;
}
// Future
IValue(c10::intrusive_ptr<ivalue::Future> v);
bool isFuture() const {
return Tag::Future == tag;
}
c10::intrusive_ptr<ivalue::Future> toFuture() &&;
c10::intrusive_ptr<ivalue::Future> toFuture() const&;
// RRef
IValue(c10::intrusive_ptr<c10::RRefInterface> v);
bool isRRef() const {
return Tag::RRef == tag;
}
c10::intrusive_ptr<c10::RRefInterface> toRRef() &&;
c10::intrusive_ptr<c10::RRefInterface> toRRef() const&;
// Quantizer
IValue(c10::intrusive_ptr<at::Quantizer> v);
bool isQuantizer() const {
return Tag::Quantizer == tag;
}
c10::intrusive_ptr<at::Quantizer> toQuantizer() &&;
c10::intrusive_ptr<at::Quantizer> toQuantizer() const&;
// Int
IValue(int64_t i) : tag(Tag::Int), is_intrusive_ptr(false) {
payload.as_int = i;
}
// allow you to pass literals (3, 4) without ambiguity
IValue(int32_t i) : IValue(static_cast<int64_t>(i)) {}
bool isInt() const {
return Tag::Int == tag;
}
int64_t toInt() const {
AT_ASSERT(isInt());
return payload.as_int;
}
// Bool
IValue(bool b) : tag(Tag::Bool), is_intrusive_ptr(false) {
#if defined(__clang__) && defined(__x86_64__)
// Initializing entire payload stops valgrind's from reporting
// "jump or move depends on uninitialised value" in IValue copy constructor
// See https://github.com/pytorch/pytorch/issues/37117
payload.as_int = b;
#else
payload.as_bool = b;
#endif
}
bool isBool() const {
return Tag::Bool == tag;
}
bool toBool() const {
AT_ASSERT(isBool());
return payload.as_bool;
}
// IntList
bool isIntList() const;
c10::List<int64_t> toIntList() &&;
c10::List<int64_t> toIntList() const&;
std::vector<int64_t> toIntVector() const;
// ConstantString
IValue(c10::intrusive_ptr<ivalue::ConstantString> v);
IValue(std::string v);
IValue(const char* v) : IValue(std::string(v)) {}
bool isString() const {
return Tag::String == tag;
}
c10::intrusive_ptr<ivalue::ConstantString> toString() &&;
c10::intrusive_ptr<ivalue::ConstantString> toString() const&;
const std::string& toStringRef() const;
c10::optional<std::reference_wrapper<const std::string>> toOptionalStringRef()
const;
// DoubleList
bool isDoubleList() const;
c10::List<double> toDoubleList() &&;
c10::List<double> toDoubleList() const&;
std::vector<double> toDoubleVector() const;
// BoolList
bool isBoolList() const;
c10::List<bool> toBoolList() &&;
c10::List<bool> toBoolList() const&;
// TensorList
bool isTensorList() const;
c10::List<at::Tensor> toTensorList() &&;
c10::List<at::Tensor> toTensorList() const&;
std::vector<at::Tensor> toTensorVector() const;
// GenericList
IValue(c10::List<IValue> v);
bool isList() const {
return Tag::GenericList == tag;
}
c10::List<IValue> toList() &&;
c10::List<IValue> toList() const&;
c10::ArrayRef<IValue> toListRef() const;
// Some template constructors of IValue calls another constructor recursively.
// This SNIFAEs the called constructor exists.
template <class T>
using enable_if_ivalue_constructible =
std::enable_if_t<std::is_constructible<IValue, T>::value, std::nullptr_t>;
template <class T, enable_if_ivalue_constructible<T> = nullptr>
IValue(c10::List<T> v);
template <class T, enable_if_ivalue_constructible<T> = nullptr>
IValue(at::ArrayRef<T> v);
template <class T, enable_if_ivalue_constructible<T> = nullptr>
IValue(const std::vector<T>& v);
template <class T, size_t N>
IValue(std::array<T, N> v);
// GenericDict
IValue(c10::Dict<IValue, IValue> v);
bool isGenericDict() const {
return Tag::GenericDict == tag;
}
c10::Dict<IValue, IValue> toGenericDict() &&;
c10::Dict<IValue, IValue> toGenericDict() const&;
template <class Key, class Value>
IValue(c10::Dict<Key, Value> v);
template <class Key, class Value>
/// \cond
/// DOXYGEN_CANNOT_HANDLE_CONSTRUCTORS_WITH_MACROS_SO_EXCLUDE_THIS_LINE_FROM_DOXYGEN
C10_DEPRECATED_MESSAGE(
"IValues based on std::unordered_map<K, V> are slow and deprecated. Please use c10::Dict<K, V> instead.")
/// \endcond
IValue(std::unordered_map<Key, Value> v);
template <class T, enable_if_ivalue_constructible<T> = nullptr>
IValue(c10::optional<T> v);
IValue(c10::nullopt_t);
// ClassType
IValue(c10::intrusive_ptr<ivalue::Object> v);
bool isObject() const {
return tag == Tag::Object;
}
c10::intrusive_ptr<ivalue::Object> toObject() &&;
c10::intrusive_ptr<ivalue::Object> toObject() const&;
const ivalue::Object& toObjectRef() const;
torch::jit::Module toModule() const;
bool isModule() const;
// PyObject
IValue(c10::intrusive_ptr<ivalue::PyObjectHolder> v);
bool isPyObject() const {
return tag == Tag::PyObject;
}
c10::intrusive_ptr<ivalue::PyObjectHolder> toPyObjectHolder() &&;
c10::intrusive_ptr<ivalue::PyObjectHolder> toPyObjectHolder() const&;
PyObject* toPyObject() const;
// Enum
explicit IValue(c10::intrusive_ptr<ivalue::EnumHolder> v);
bool isEnum() const {
return tag == Tag::Enum;
}
c10::intrusive_ptr<ivalue::EnumHolder> toEnumHolder() &&;
c10::intrusive_ptr<ivalue::EnumHolder> toEnumHolder() const&;
// None
IValue() : payload{0}, tag(Tag::None), is_intrusive_ptr(false) {}
bool isNone() const {
return Tag::None == tag;
}
std::string toNone() const {
AT_ASSERT(isNone());
return "None";
}
static IValue uninitialized() {
auto i = IValue();
i.tag = Tag::Uninitialized;
return i;
}
// Scalar, which gets encoded as either an Int or a Double
IValue(at::Scalar s) : IValue() {
if (s.isFloatingPoint()) {
*this = s.toDouble();
} else {
*this = s.toLong();
}
}
bool isScalar() const {
return isDouble() || isInt();
}
at::Scalar toScalar() const {
if (isDouble())
return toDouble();
else if (isInt())
return toInt();
throw std::runtime_error("IValue is not a Scalar");
}
// Device
IValue(c10::Device d) : tag(Tag::Device), is_intrusive_ptr(false) {
payload.as_device.type = d.type();
payload.as_device.index = d.index();
}
bool isDevice() const {
return Tag::Device == tag;
}
c10::Device toDevice() const {
AT_ASSERT(isDevice());
return c10::Device(payload.as_device.type, payload.as_device.index);
}
//Stream
IValue(c10::Stream stream)
: tag(Tag::Stream), is_intrusive_ptr(false) {
payload.as_int = stream.pack();
}
c10::Stream toStream() &&;
c10::Stream toStream() const &;
bool isStream() const { return Tag::Stream == tag; }
// ScalarType
IValue(ScalarType t)
: IValue(static_cast<std::underlying_type<ScalarType>::type>(t)) {}
at::ScalarType toScalarType() const {
return static_cast<at::ScalarType>(toInt());
}
// Layout
IValue(Layout l)
: IValue(static_cast<std::underlying_type<Layout>::type>(l)) {}
at::Layout toLayout() const {
return static_cast<at::Layout>(toInt());
}
// MemoryFormat
IValue(MemoryFormat m)
: IValue(static_cast<std::underlying_type<MemoryFormat>::type>(m)) {}
at::MemoryFormat toMemoryFormat() const {
return static_cast<at::MemoryFormat>(toInt());
}
// QScheme
IValue(at::QScheme qscheme) : tag(Tag::Int), is_intrusive_ptr(false) {
payload.as_int = static_cast<int64_t>(qscheme);
}
at::QScheme toQScheme() const {
return static_cast<at::QScheme>(toInt());
}
// Dimname
IValue(at::Dimname dimname) : IValue(dimname.symbol().toQualString()) {}
at::Dimname toDimname() const {
return at::Dimname::fromSymbol(Symbol::fromQualString(toStringRef()));
}
// Generator
IValue(at::Generator g) : tag(Tag::Generator), is_intrusive_ptr(g.defined()) {
// Note: the undefined generator is not refcounted, so while it
// is tagged as a generator, is_intrusive_ptr is set to false.
// This is not an optional optimization: our incref call
// *will not* do the right thing when called on an
// undefined generator.
payload.as_intrusive_ptr = g.unsafeReleaseGeneratorImpl();
}
bool isGenerator() const {
return Tag::Generator == tag;
}
at::Generator toGenerator() &&;
at::Generator toGenerator() const&;
// for debugging
std::string tagKind() const {
switch (tag) {
#define DEFINE_CASE(x) \
case Tag::x: \
return #x;
TORCH_FORALL_TAGS(DEFINE_CASE)
#undef DEFINE_CASE
}
return "InvalidTag(" + c10::guts::to_string(static_cast<int>(tag)) + ")";
}
// generic v.to<at::Tensor>() implementations
// that can be used in special functions like pop/push
// that use template meta-programming.
// prefer the directly named methods when you can,
// since they are simpler to understand
// Note: if you get linker errors saying one of these is missing,
// change it to ... && = delete; and you will see better error messages for
// why However, we cannot commit this because some compiler versions barf on
// it.
template <typename T>
T to() &&;
template <typename T>
T to() const&;
// ToOptional: convert a IValue to the Optional obj that accepts both T and
// None
template <typename T>
optional<T> toOptional();
/// @private [doxygen private]
/// Only for use in generated code.
OptionalArray<int64_t> toOptionalIntArray();
/// @private [doxygen private]
/// Only for use in generated code.
OptionalArray<double> toOptionalDoubleArray();
/// @private [doxygen private]
/// this is a shallow comparison of two IValues to test the object identity
bool isSameIdentity(const IValue& rhs) const;
// Computes the "official" string representation of an IValue. This produces a
// TorchScript expression that can be used to recreate an IValue with the same
// value (e.g. when we are printing constants in the serializer).
//
// Callers can use `customFormatter` to override how `repr()` prints out an
// IValue. This is useful if you have some other environment where you can
// look up values, and you want to print a reference to that environment (like
// the serializer's constant table).
//
// repr() is not necessarily defined on all objects!
std::ostream& repr(
std::ostream& stream,
std::function<bool(std::ostream&, const IValue& v)> customFormatter)
const;
// Computes an "informal" string representation of an IValue. This should be
// used for debugging, or servicing `print()`-like functions.
// This is different from `repr()` in that there is no expectation that we can
// exactly reconstruct an IValue from the output; feel free to use a
// concise/pretty form
CAFFE2_API friend std::ostream& operator<<(
std::ostream& out,
const IValue& v);
bool isPtrType() const {
return is_intrusive_ptr;
}
/// @private [doxygen private]
const void* internalToPointer() const {
TORCH_INTERNAL_ASSERT(
isPtrType(), "Can only call internalToPointer() for pointer types");
return payload.as_intrusive_ptr;
}
TypePtr type() const;
// Detect aliased tensors.
struct HashAliasedIValue {
size_t operator()(const IValue& val) const {
if (val.isTensor()) {
return reinterpret_cast<size_t>(
val.toTensor().storage().unsafeGetStorageImpl());
}
// If it is not a Tensor, then two mutable IValues alias each other only
// if they are the same pointer.
return val.payload.as_int;
}
};
struct CompAliasedIValues {
bool operator()(const IValue& lhs, const IValue& rhs) const {
return lhs.isAliasOf(rhs);
}
};
using HashAliasedIValues =
std::unordered_set<IValue, HashAliasedIValue, CompAliasedIValues>;
using HashAliasedIValueMap =
std::unordered_map<IValue, IValue, HashAliasedIValue, CompAliasedIValues>;
// Chechs if this and rhs has a subvalues in common.
// [t1,t2] and [t2, t3] returns true.
bool overlaps(const IValue& rhs) const;
// Inserts all subvalues of this in subValues.
void getSubValues(HashAliasedIValues& subValues) const;
// Apply visitor to every subvalue.
// TODO: There are several places that recurse over IValue. This is fragile.
// This visitor should be used to recurse over ivalues.
void visit(const std::function<bool(const IValue&)>& visitor) const;
IValue deepcopy() const;
IValue deepcopy(HashAliasedIValueMap& memo) const;
private:
static bool ptrEqual(const IValue& lhs, const IValue& rhs);
// NOTE: IValue tags are intentionally private. In the future we may encode
// this value different (e.g. using NaN boxing), and this would make it more
// costly to determine the tag for all types vs just determining if something
// is a particular type. Instead we want clients to use the `isX` methods when
// possible. If for perf. reasons you really, absolutely, must have a jump
// table, then we can revisit this.
enum class Tag : uint32_t {
#define DEFINE_TAG(x) x,
TORCH_FORALL_TAGS(DEFINE_TAG)
#undef DEFINE_TAG
};
template <
class T,
class NullType = c10::detail::intrusive_target_default_null_type<T>>
c10::intrusive_ptr<T, NullType> moveToIntrusivePtr();
template <
typename T,
class NullType = c10::detail::intrusive_target_default_null_type<T>>
c10::intrusive_ptr<T, NullType> toIntrusivePtr() const;
void clearToNone() {
payload.as_int = 0;
tag = Tag::None;
is_intrusive_ptr = false;
}
union Payload {
int64_t as_int;
double as_double;
bool as_bool;
c10::intrusive_ptr_target* as_intrusive_ptr;
struct {
DeviceType type;
DeviceIndex index;
} as_device;
};
IValue(Payload p, Tag t, bool i) : payload(p), tag(t), is_intrusive_ptr(i) {}
Payload payload;
Tag tag;
bool is_intrusive_ptr;
friend struct WeakIValue;
};
struct CAFFE2_API WeakIValue final {
WeakIValue() : payload{0}, tag(IValue::Tag::None), is_intrusive_ptr(false) {}
WeakIValue(const WeakIValue& rhs)
: payload(rhs.payload),
tag(rhs.tag),
is_intrusive_ptr(rhs.is_intrusive_ptr) {
if (is_intrusive_ptr) {
c10::raw::weak_intrusive_ptr::incref(payload.as_intrusive_ptr);
}
}
WeakIValue(const IValue& rhs)
: payload(rhs.payload),
tag(rhs.tag),
is_intrusive_ptr(rhs.is_intrusive_ptr) {
if (is_intrusive_ptr) {
c10::raw::weak_intrusive_ptr::incref(payload.as_intrusive_ptr);
}
}
WeakIValue(WeakIValue&& rhs) noexcept : WeakIValue() {
swap(rhs);
}
~WeakIValue() {
if (is_intrusive_ptr) {
c10::raw::weak_intrusive_ptr::decref(payload.as_intrusive_ptr);
}
}
WeakIValue& operator=(WeakIValue&& rhs) & noexcept {
WeakIValue(std::move(rhs)).swap(*this); // this also sets rhs to None
return *this;
}
WeakIValue& operator=(WeakIValue const& rhs) & {
WeakIValue(rhs).swap(*this);
return *this;
}
void swap(WeakIValue& rhs) noexcept {
std::swap(payload, rhs.payload);
std::swap(is_intrusive_ptr, rhs.is_intrusive_ptr);
std::swap(tag, rhs.tag);
}
bool isSameIdentity(const WeakIValue& rhs) const {
return payload.as_int == rhs.payload.as_int && tag == rhs.tag &&
is_intrusive_ptr == rhs.is_intrusive_ptr;
}
IValue lock() const {
if (!is_intrusive_ptr) {
return IValue(payload, tag, false);
}
auto temp = c10::weak_intrusive_ptr<c10::intrusive_ptr_target>::reclaim(
payload.as_intrusive_ptr);
IValue::Payload pl;
pl.as_intrusive_ptr = temp.lock().release();
temp.release();
if (!pl.as_intrusive_ptr) {
return IValue();
} else {
return IValue(pl, tag, true);
}
}
size_t use_count() const noexcept {
if (!is_intrusive_ptr) {
return 1;
}
auto temp = c10::weak_intrusive_ptr<c10::intrusive_ptr_target>::reclaim(
payload.as_intrusive_ptr);
size_t result = temp.use_count();
temp.release();
return result;
}
size_t weak_use_count() const noexcept {
if (!is_intrusive_ptr) {
return 1;
}
auto temp = c10::weak_intrusive_ptr<c10::intrusive_ptr_target>::reclaim(
payload.as_intrusive_ptr);
size_t result = temp.weak_use_count();
temp.release();
return result;
}
size_t hash() const {
return payload.as_int;
}
private:
IValue::Payload payload;
IValue::Tag tag;
bool is_intrusive_ptr;
};
// An owning pointer to a type. When the type is class type, it requires a pair
// of shared_ptrs to the class type and its owning CU, so that the class type is
// guaranteed to stay alive as long as we hold this object.
struct TORCH_API StrongTypePtr {
StrongTypePtr(
std::shared_ptr<torch::jit::CompilationUnit> cu,
std::shared_ptr<Type> type);
std::shared_ptr<torch::jit::CompilationUnit> cu_;
std::shared_ptr<Type> type_;
};
TORCH_API ska::flat_hash_map<std::type_index, c10::ClassTypePtr>&
getCustomClassTypeMap();
template <typename T>
c10::ClassTypePtr getCustomClassType() {
auto tmap = c10::getCustomClassTypeMap();
auto res = tmap.find(std::type_index(typeid(T)));
if (res == tmap.end()) {
throw c10::Error("Can't find class id in custom class type map", "");
}
return res->second;
}
template <typename T>
inline bool isCustomClassRegistered() {
auto tmap = c10::getCustomClassTypeMap();
return tmap.find(std::type_index(typeid(T))) != tmap.end();
}
TORCH_API std::unordered_map<std::string, std::function<PyObject*(void*)>>&
getClassConverter();
} // namespace c10
#include <ATen/core/ivalue_inl.h>