Files
pytorch/c10/core/DispatchKeySet.h
cyy 7c1f627828 Fix 'dllimport attribute ignored on inline function' (#157670)
There are lots of warnings in builds:
```
 2025-07-05T16:59:46.9208806Z C:\actions-runner\_work\pytorch\pytorch\build\aten\src\ATen\core\TensorBody.h(5043,29): warning: 'at::Tensor::less_' redeclared inline; 'dllimport' attribute ignored [-Wignored-attributes]
2025-07-05T16:59:46.9209030Z  5043 | inline at::Tensor & Tensor::less_(const at::Scalar & other) const {
2025-07-05T16:59:46.9209104Z       |                             ^
2025-07-05T16:59:46.9209671Z C:\actions-runner\_work\pytorch\pytorch\build\aten\src\ATen\core\TensorBody.h(5048,29): warning: 'at::Tensor::less_' redeclared inline; 'dllimport' attribute ignored [-Wignored-attributes]
2025-07-05T16:59:46.9209860Z  5048 | inline at::Tensor & Tensor::less_(const at::Tensor & other) const
```
This PR has fixed them and turned the warning into an error.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/157670
Approved by: https://github.com/albanD
2025-07-07 16:57:48 +00:00

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#pragma once
#include <c10/core/DispatchKey.h>
#include <c10/macros/Export.h>
#include <c10/macros/Macros.h>
#include <c10/util/Exception.h>
#include <c10/util/Metaprogramming.h>
#include <c10/util/TypeList.h>
#include <c10/util/llvmMathExtras.h>
#include <array>
#include <cstddef>
#include <cstdint>
#include <initializer_list>
#include <iterator>
#include <ostream>
#include <string>
#include <type_traits>
namespace c10 {
struct FunctionalityOffsetAndMask {
// empty constructor shouldn't be used; only needed to initialize
// the array before populating it.
FunctionalityOffsetAndMask() = default;
FunctionalityOffsetAndMask(uint16_t offset, uint16_t mask)
: offset(offset), mask(mask) {}
// This needs to big enough to cover the size of the operator table.
uint16_t offset{};
// See Note [No More Than 16 Backends]
// This mask needs to be big enough to mask all of the backend bits.
// We probably don't ever want to have more than 16 backend bits, so uint16_t
// should be enough.
uint16_t mask{};
};
static_assert(
c10::num_runtime_entries < 65536,
"The dispatcher currently only supports up to 2^16 runtime entries");
C10_API std::array<FunctionalityOffsetAndMask, num_functionality_keys>
initializeFunctionalityOffsetsAndMasks();
C10_ALWAYS_INLINE static const std::
array<FunctionalityOffsetAndMask, num_functionality_keys>&
offsetsAndMasks() {
static auto offsets_and_masks_ = initializeFunctionalityOffsetsAndMasks();
return offsets_and_masks_;
}
// A representation of a set of DispatchKeys. A DispatchKeySet contains both
// "functionality" bits and "backend bits", and every tensor holds its own
// DispatchKeySet. The Dispatcher implements multiple dispatch by grabbing the
// keyset on every input tensor, oring them together, and dispatching to a
// specific piece of functionality. The functionality bits are *ordered*. When
// multiple functionality bits are set, we use the highest priority
// functionality. Similarly, multiple backend bits can theoretically be set if
// you call an operator with multiple tensors from difference devices (e.g. CPU
// and CUDA), although support for mixed device dispatch is limited (the only
// kernels that gracefully handle mixed device inputs for now are cuda kernels
// that take in a scalar cpu tensor).
// A representation of a set of DispatchKeys. A tensor may have multiple
// tensor type ids, e.g., a Variable tensor can also be a CPU tensor; the
// DispatchKeySet specifies what type ids apply. The internal representation is
// as a 64-bit bit set (this means only 64 tensor type ids are supported).
//
// As mentioned above, DispatchKeys are ordered; thus, we can ask questions like
// "what is the highest priority DispatchKey in the set"? (The set itself is
// not ordered; two sets with the same ids will always have the ids ordered in
// the same way.)
//
// Note [DispatchKeySet Internal Representation]
// Internally, dispatch keys are packed into 64-bit DispatchKeySet objects
// that get passed around at runtime.
// However, there isn't necessarily a 1-to-1 mapping between bits in the keyset
// and individual dispatch keys.
//
// First: why do we have this distinction, and why not map every dispatch key
// directly to a bit? This is mostly because we have several types of
// functionalities that different backends would like to customize. For example,
// we have:
// - "Dense": CPU, CUDA, XLA, ... (~12 keys)
// - "Sparse": SparseCPU, SparseCUDA, ...
// - "SparseCsr": SparseCsrCPU, SparseCsrCUDA, ...
// - "Quantized": QuantizedCPU, QuantizedCUDA, QuantizedXLA, ...
// - "Autograd": AutogradCPU, AutogradCUDA, Autograd XLA, ...
// The problem is that total number of keys grows quadratically with [#
// backends] x [# functionalities], making it very difficult to map each key
// directly to a bit in a bitset without dramatically increasing the size of the
// bitset over time.
//
// The two enums (BackendComponent and DispatchKey) can be divided roughly into
// 5 categories.
//
// (1) "Building block" keys
// (a) backends: Everything in the BackendComponent enum (e.g. CPUBit,
// CUDABit) (b) functionalities: (per-backend) functionality-bit DispatchKeys
// (e.g. AutogradFunctionality, SparseCsr, Sparse, Dense)
// (2) "Runtime" keys
// (a) "non-customizable backends" (e.g. FPGA)
// (b) "non-customizable functionalities" (e.g. Functionalize)
// (c) "per-backend instances of customizable functionalities" (e.g. CPU,
// SparseCPU, AutogradCPU)
// (3) "Alias" DispatchKeys (see Note [Alias Dispatch Keys])
//
// (1) Building block keys always correspond to individual bits in a
// DispatchKeySet. They can also be combined in a DispatchKeySet to form actual
// runtime keys. e.g.
// auto dense_cpu_ks = DispatchKeySet({DispatchKey::CPUBit,
// DispatchKey::Dense});
// // The keyset has the runtime dense-cpu key.
// dense_cpu_ks.has(DispatchKey::CPU);
// // And it contains the building block keys too.
// dense_cpu_ks.has(DispatchKey::CPUBit);
// dense_cpu_ks.has(DispatchKey::Dense);
//
// Not every backend and not every functionality counts as a "building block
// key". This is mostly to give us more levers to pull in the design space.
// Backend keys and functionality keys that count as "building blocks" will
// contribute to a full cross product of functionality that can be overridden.
//
// For example, right now we have at least 12 "backend" building
// blocks (CPU, CUDA, XLA, ...) and at least 5 "functionality"
// building blocks (Dense, Sparse, SparseCsr, Quantized,
// AutogradFunctionality, ...). These keys together allow every
// dispatcher operator to be customized in up to 12*4 different
// ways. Each of those requires a slot in the operator table of every
// dispatcher operator. Not every piece of functionality necessarily
// needs to be customizable per-backend, and not every backend
// necessarily needs to be able to customize every type of
// functionality.
//
//
// (2) Every runtime key corresponds directly to a slot in an operator's runtime
// dispatch table, and you can directly register kernels to a runtime dispatch
// key.
//
// For per-backend functionalities like "Dense" or "AutogradFunctionality",
// you can think of the corresponding runtime dispatch keys as "instances" of
// that functionality, per backend. E.g. "CPU", "CUDA", "XLA", etc. are all
// runtime instances of the "Dense" building block key.
// (2a) and (2b) are represented identically in the DispatchKeySet logic:
// - backend-agnostic functionalities (e.g. FuncTorchBatched) are NOT
// customizable per backend.
// In order to do so, we'd need to promote it to a per-backend functionality
// "building block" key.
// - non-customizable backends (e.g. FPGA) can NOT customize existing
// functionality like Sparse, Autograd, etc.
// In order to do so, we'd need to promote it to a backend "building block"
// key.
//
// In both cases, these keys directly correspond to runtime slots in the
// operator table.
//
//
// (3) "Alias" keys
// See Note [Alias Dispatch Keys]
//
// Final note: for anyone making future changes to the Dispatcher +
// DispatchKeySet internals, there's a closed PR with a basic
// python-implementation of the Dispatcher that might be useful in quickly
// testing out and validating changes. See it at
// https://github.com/pytorch/pytorch/pull/68743
// An undefined tensor is one with an empty tensor type set.
class DispatchKeySet final {
public:
enum Full { FULL };
enum FullAfter { FULL_AFTER };
enum Raw { RAW };
// NB: default constructor representation as zero is MANDATORY as
// use of DispatchKeySet in TLS requires this.
constexpr DispatchKeySet() = default;
constexpr DispatchKeySet(Full)
: repr_((1ULL << (num_backends + num_functionality_keys - 1)) - 1) {}
constexpr DispatchKeySet(FullAfter, DispatchKey t)
// LSB after t are OK, but not t itself.
// "functionalities" have a notion of ordering (e.g. Autograd > Sparse >
// Quantized > Dense). But backends don't really have an ordering.
// Therefore, we're enforcing that FullAfter can only be used on
// "functionality" keys.
: repr_(
(1ULL
<< (num_backends + static_cast<uint8_t>(toFunctionalityKey(t)) -
1)) -
1) {
*this = add(DispatchKey::PythonDispatcher);
}
// Public version of DispatchKeySet(uint64_t) API; external users
// must be explicit when they do this!
constexpr DispatchKeySet(Raw, uint64_t x) : repr_(x) {}
constexpr explicit DispatchKeySet(BackendComponent k) {
if (k == BackendComponent::InvalidBit) {
repr_ = 0;
} else {
repr_ = 1ULL << (static_cast<uint8_t>(k) - 1);
}
}
constexpr explicit DispatchKeySet(DispatchKey k) {
// NOLINTNEXTLINE(bugprone-branch-clone)
if (k == DispatchKey::Undefined) {
// Case 1: handle Undefined specifically
repr_ = 0;
} else if (k <= DispatchKey::EndOfFunctionalityKeys) {
// Case 2: handle "functionality-only" keys
// These keys have a functionality bit set, but no backend bits
// These can technically be either:
// - valid runtime keys (e.g. DispatchKey::AutogradOther,
// DispatchKey::FuncTorchBatched, etc)
// - "building block" keys that aren't actual runtime keys (e.g.
// DispatchKey::Dense or Sparse)
uint64_t functionality_val = 1ULL
<< (num_backends + static_cast<uint8_t>(k) - 1);
repr_ = functionality_val;
} else if (k <= DispatchKey::EndOfRuntimeBackendKeys) {
// Case 3: "runtime" keys that have a functionality bit AND a backend bit.
// First compute which bit to flip for the functionality.
auto functionality_k = toFunctionalityKey(k);
// The - 1 is because Undefined is technically a "functionality" that
// doesn't show up in the bitset. So e.g. Dense is technically the second
// functionality, but the lowest functionality bit.
uint64_t functionality_val = 1ULL
<< (num_backends + static_cast<uint8_t>(functionality_k) - 1);
// then compute which bit to flip for the backend
// Case 4a: handle the runtime instances of "per-backend functionality"
// keys For example, given DispatchKey::CPU, we should set:
// - the Dense functionality bit
// - the CPUBit backend bit
// first compute which bit to flip for the backend
auto backend_k = toBackendComponent(k);
uint64_t backend_val = backend_k == BackendComponent::InvalidBit
? 0
: 1ULL << (static_cast<uint8_t>(backend_k) - 1);
repr_ = functionality_val + backend_val;
} else {
// At this point, we should have covered every case except for alias keys.
// Technically it would be possible to add alias dispatch keys to a
// DispatchKeySet, but the semantics are a little confusing and this
// currently isn't needed anywhere.
repr_ = 0;
}
}
constexpr uint64_t keys_to_repr(std::initializer_list<DispatchKey> ks) {
uint64_t repr = 0;
for (auto k : ks) {
repr |= DispatchKeySet(k).repr_;
}
return repr;
}
constexpr uint64_t backend_bits_to_repr(
std::initializer_list<BackendComponent> ks) {
uint64_t repr = 0;
for (auto k : ks) {
repr |= DispatchKeySet(k).repr_;
}
return repr;
}
explicit constexpr DispatchKeySet(std::initializer_list<DispatchKey> ks)
: repr_(keys_to_repr(ks)) {}
explicit constexpr DispatchKeySet(std::initializer_list<BackendComponent> ks)
// Note: for some reason, putting this logic directly in the constructor
// appears to fail to compile on CUDA 10.1.
// See an example internal failure at
// https://www.internalfb.com/intern/skycastle/run/76561193669136035/artifact/actionlog.76561193742069401.stderr
: repr_(backend_bits_to_repr(ks)) {}
// Test if a DispatchKey is in the set
inline bool has(DispatchKey t) const {
TORCH_INTERNAL_ASSERT_DEBUG_ONLY(t != DispatchKey::Undefined);
return has_all(DispatchKeySet(t));
}
constexpr bool has_backend(BackendComponent t) const {
return has_all(DispatchKeySet(t));
}
// Test if a DispatchKey is in the set
// Given a DispatchKeySet of functionality keys and (potentially) backend
// keys, tests if all of them are in the current set.
constexpr bool has_all(DispatchKeySet ks) const {
return static_cast<bool>((repr_ & ks.repr_) == ks.repr_);
}
// Given a DispatchKeySet of functionality keys and (potentially) backend
// keys, tests if any of them are in the current set. This could technically
// be pretty easily implemented using has(). It is strictly a perf
// optimization though. There are many places in the code base where we want
// to test for multiple functionality keys together. HOWEVER, runtime
// per-backend functionality keys aren't allowed to be used with this
// function, because you can end up with weird results. e.g.
// DispatchKeySet(DispatchKey::AutogradCPU).has_any(DispatchKeySet(DispatchKey::CPU))
// would return true.
inline bool has_any(DispatchKeySet ks) const {
TORCH_INTERNAL_ASSERT_DEBUG_ONLY(
// Either there are no backend bits in the input keyset
((ks.repr_ & full_backend_mask) == 0) ||
// or there are no per-backend-functionality bits
// See [Note: Per-Backend Functionality Dispatch Keys]
((ks &
DispatchKeySet({
DispatchKey::Dense,
DispatchKey::Quantized,
DispatchKey::Sparse,
DispatchKey::SparseCsr,
DispatchKey::AutogradFunctionality,
})
.repr_) == 0));
return static_cast<bool>((repr_ & ks.repr_) != 0);
}
// Test if DispatchKeySet is a superset of ks.
bool isSupersetOf(DispatchKeySet ks) const {
return (repr_ & ks.repr_) == ks.repr_;
}
// Perform set union
constexpr DispatchKeySet operator|(DispatchKeySet other) const {
return DispatchKeySet(repr_ | other.repr_);
}
// Perform set intersection
constexpr DispatchKeySet operator&(DispatchKeySet other) const {
return DispatchKeySet(repr_ & other.repr_);
}
// Compute the set difference self - other,
// but ONLY for the functionality keys.
// Any backend bits set on self will remain unchanged.
// See Note [Removing keys from DispatchKeySet Only Affects Functionality
// Keys]
constexpr DispatchKeySet operator-(DispatchKeySet other) const {
return DispatchKeySet(repr_ & (full_backend_mask | ~other.repr_));
}
// Compute self ^ other
constexpr DispatchKeySet operator^(DispatchKeySet other) const {
return DispatchKeySet(repr_ ^ other.repr_);
}
bool operator==(DispatchKeySet other) const {
return repr_ == other.repr_;
}
bool operator!=(DispatchKeySet other) const {
return repr_ != other.repr_;
}
// Add a DispatchKey to the DispatchKey set. Does NOT mutate,
// returns the extended DispatchKeySet!
[[nodiscard]] constexpr DispatchKeySet add(DispatchKey t) const {
return *this | DispatchKeySet(t);
}
[[nodiscard]] constexpr DispatchKeySet add(DispatchKeySet ks) const {
return *this | ks;
}
// Remove a DispatchKey from the DispatchKey set.
// This is generally not an operation you should be doing
// (it's used to implement the printing overload, operator<<)
//
// Note [Removing keys from DispatchKeySet Only Affects Functionality Keys]
// Only functionality bits are allowed to be removed from a keyset.
// For now, we're only allowing removal of "functionality bits" from the
// keyset, which is specifically needed by the fallthrough key calculation
// logic. Why is removing backend bits problematic? Consider this example:
//
// DispatchKeySet([DispatchKey.CPU, DispatchKey.AutogradCUDA,
// DispatchKey.CUDA]).remove(DispatchKey.AutogradCUDA)
// DispatchKeySet([DispatchKey.CPU,
// DispatchKey.AutogradCUDA]).remove(DispatchKey.AutogradCUDA)
//
// What do we want to happen?
// Technically, we'd like it to be true that after removal,
// the first keyset still has the CUDA dispatch key while the second doesn't.
// Unfortunately there's no way to represent that, because the two keysets are
// represented the same way internally: functionality bits: Autograd, Dense
// backend bits: CPU, CUDA
//
// Instead, remove(DispatchKey.AutogradCPU) will only remove the "Autograd"
// bit from the bitset.
[[nodiscard]] constexpr DispatchKeySet remove(DispatchKey t) const {
return DispatchKeySet(
repr_ & ~(DispatchKeySet(t).repr_ & ~full_backend_mask));
}
// You're allowed to remove a backend bit from a DispatchKeySet,
// but you have to be explicit about it (remove_backend() instead of
// remove()).
constexpr DispatchKeySet remove_backend(BackendComponent b) const {
return DispatchKeySet(repr_ & ~(DispatchKeySet(b).repr_));
}
// Is the set empty? (AKA undefined tensor)
bool empty() const {
return repr_ == 0;
}
uint64_t raw_repr() const {
return repr_;
}
static DispatchKeySet from_raw_repr(uint64_t x) {
return DispatchKeySet(RAW, x);
}
DispatchKey highestFunctionalityKey() const {
auto functionality_idx = indexOfHighestBit();
// This means that none of the functionality bits were set.
if (functionality_idx < num_backends)
return DispatchKey::Undefined;
// The first num_backend bits in the keyset don't correspond to real
// dispatch keys.
return static_cast<DispatchKey>(functionality_idx - num_backends);
}
// This is similar like toBackendComponent(DispatchKey), but less restrictive.
// toBackendComponent() errors out if the key that it was passed has no
// backend bits, which is useful for error checking. We need a version of that
// here that can also handle "fake" backends like FPGA, because they need to
// map to the AutogradOther key. For those backends, we return
// BackendComponent::InvalidBit.
BackendComponent highestBackendKey() const {
// mask to mask out functionality bits
auto backend_idx =
DispatchKeySet(repr_ & full_backend_mask).indexOfHighestBit();
// all zeros across the backend bits means that no backend bits are set.
if (backend_idx == 0)
return BackendComponent::InvalidBit;
return static_cast<BackendComponent>(backend_idx);
}
// returns the DispatchKey of highest priority in the set.
DispatchKey highestPriorityTypeId() const {
auto functionality_k = highestFunctionalityKey();
if (isPerBackendFunctionalityKey(functionality_k)) {
return toRuntimePerBackendFunctionalityKey(
functionality_k, highestBackendKey());
}
return functionality_k;
}
// Returns the index of the most-significant bit in the keyset.
// This is used to as part of the calculation into the operator table to get:
// - the highest "functionality" bit in the keyset.
// - the highest "backend" bit in the keyset.
uint8_t indexOfHighestBit() const {
return 64 - llvm::countLeadingZeros(repr_);
}
#if defined(C10_MOBILE_TRIM_DISPATCH_KEYS)
// [Note: Trimmed Mobile Dispatch Keys]
/**
* The method below maps the dispatch key in the enum DispatchKey to an
* integer index in the dispatchTable_ array in OperatorEntry. The array
* is trimmed for mobile to reduce peak memory usage since it's
* unnecessary to reserve additional space for dispatch keys that will
* never be used on mobile.
*/
int getDispatchTableIndexForDispatchKeySet() const {
auto dk = highestPriorityTypeId();
switch (dk) {
case DispatchKey::Undefined:
return 0;
case DispatchKey::CPU:
return 1;
case DispatchKey::QuantizedCPU:
return 2;
case DispatchKey::SparseCPU:
return 3;
case DispatchKey::BackendSelect:
return 4;
case DispatchKey::ADInplaceOrView:
return 5;
case DispatchKey::AutogradOther:
return 6;
case DispatchKey::AutogradCPU:
return 7;
default:
return -1;
}
}
#else
// returns the index in the operator table of highest priority key in the the
// keyset Note that we could in theory implement this using
// highestPriorityTypeId(), but this code is very hotpath and we can do it
// faster without it.
int getDispatchTableIndexForDispatchKeySet() const {
auto functionality_idx =
DispatchKeySet(repr_ >> num_backends).indexOfHighestBit();
auto offset_and_mask = offsetsAndMasks()[functionality_idx];
// Mask the functionality bits out first, then right-shift by 1.
// right-shifting by 1 because everything is zero-indexed.
// E.g. 000001 (CPU) should give us an offset of 0, 000010 (CUDA) should
// give us an offset of 1, etc.
auto backend_idx =
DispatchKeySet((repr_ & offset_and_mask.mask) >> 1).indexOfHighestBit();
return offset_and_mask.offset + backend_idx;
}
#endif
// returns the "index" of the highest priority backend in the keyset.
// This is pretty similar to getBackendKey(), but:
// - It's hotpath code (part of the runtime bitset calculation)
// - I's returns an integer index, not an enum value
// - Everything is shifted to the right by 1.
// BackendComponent::InvalidBit is technically the lowest enum value,
// but it isn't included in the runtime table. So CPUBit = 1, CUDABit = 2,
// etc.
uint64_t getBackendIndex() const {
return DispatchKeySet((repr_ & full_backend_mask) >> 1).indexOfHighestBit();
}
private:
constexpr DispatchKeySet(uint64_t repr) : repr_(repr) {}
uint64_t repr_ = 0;
public:
// STL iterator for DispatchKeySet. Iterates through all runtime DispatchKeys
// in the set. The iterator is only invalidated by the destruction of the
// underlying DispatchKeySet as the iterator stores a pointer to the raw
// representation of the DispatchKeySet. Note: When we encounter a per-backend
// functionality (e.g. Dense or Sparse), we will iterate through EVERY backend
// in the keyset, for that functionality. For example, if the next
// functionality key to iterate over is Autograd, and the backend bits in the
// keyset correspond to [BackendComponent::CPUBit, BackendComponent::CUDABit],
// then the next two keys we return will be DispatchKey::AutogradCPU,
// DispatchKey::AutogradCUDA (CPU first because it has lower precedence than
// CUDA in DispatchKey.h).
class iterator {
public:
using self_type = iterator;
using iterator_category = std::input_iterator_tag;
using value_type = DispatchKey;
using difference_type = ptrdiff_t;
using reference = value_type&;
using pointer = value_type*;
// final mask value should mask out the entire keyset
static const uint8_t end_iter_mask_val =
num_backends + num_functionality_keys;
// final key value should be the last DispatchKey
static const uint8_t end_iter_key_val = num_functionality_keys;
// current_dispatchkey_idx_ will iterate through all functionality bits.
// current_backendcomponent_idx_ will iterate through all backend bits.
explicit iterator(
const uint64_t* data_ptr,
uint8_t next_functionality = num_backends,
uint8_t next_backend = 0)
: data_ptr_(data_ptr),
next_functionality_(next_functionality),
next_backend_(next_backend),
// These are in an invalid state at construction time, and set by the
// first increment call
current_dispatchkey_idx_(end_iter_key_val),
current_backendcomponent_idx_(end_iter_key_val) {
// Go to the first key in the set
TORCH_INTERNAL_ASSERT(
next_functionality_ >= num_backends,
"num_backends=",
static_cast<uint32_t>(num_backends),
"next_functionality_=",
static_cast<uint32_t>(next_functionality_));
++(*this);
}
C10_API self_type& operator++();
self_type operator++(int) {
self_type previous_iterator = *this;
++(*this);
return previous_iterator;
}
bool operator==(const self_type& rhs) const {
return next_functionality_ == rhs.next_functionality_ &&
current_dispatchkey_idx_ == rhs.current_dispatchkey_idx_ &&
next_backend_ == rhs.next_backend_ &&
current_backendcomponent_idx_ == rhs.current_backendcomponent_idx_;
}
bool operator!=(const self_type& rhs) const {
return next_functionality_ != rhs.next_functionality_ ||
current_dispatchkey_idx_ != rhs.current_dispatchkey_idx_ ||
next_backend_ != rhs.next_backend_ ||
current_backendcomponent_idx_ != rhs.current_backendcomponent_idx_;
}
DispatchKey operator*() const {
auto functionality_key =
static_cast<DispatchKey>(current_dispatchkey_idx_);
if (isPerBackendFunctionalityKey(functionality_key)) {
auto next_key = toRuntimePerBackendFunctionalityKey(
functionality_key,
static_cast<BackendComponent>(current_backendcomponent_idx_));
// We expect all of the Dense, Sparse, Quantized, and Autograd keys to
// be ordered the same way with respect to their backends
TORCH_INTERNAL_ASSERT(
toBackendComponent(next_key) ==
static_cast<BackendComponent>(current_backendcomponent_idx_),
"Tried to map functionality key ",
toString(functionality_key),
" and backend bit ",
toString(
static_cast<BackendComponent>(current_backendcomponent_idx_)),
" to a runtime key, but ended up with ",
toString(next_key),
". This can happen if the order of the backend dispatch keys in DispatchKey.h isn't consistent.",
" Please double check that enum for inconsistencies.");
return next_key;
} else {
return functionality_key;
}
}
private:
const uint64_t* data_ptr_;
uint8_t next_functionality_;
uint8_t next_backend_;
uint8_t current_dispatchkey_idx_;
uint8_t current_backendcomponent_idx_;
};
public:
// Returns iterator to the first key in the set. If no keys are in the
// set, then will return the end iterator.
iterator begin() const {
return iterator(&repr_);
}
// We do not need to iterate beyond EndOfFunctionalityKeys so we will treat
// this as the end iterator.
iterator end() const {
return iterator(&repr_, iterator::end_iter_mask_val);
}
};
C10_API std::string toString(DispatchKeySet);
C10_API std::ostream& operator<<(std::ostream&, DispatchKeySet);
inline int getDispatchTableIndexForDispatchKey(DispatchKey k) {
return DispatchKeySet(k).getDispatchTableIndexForDispatchKeySet();
}
// Alias key DispatchKey::Autograd maps to
// (autograd_dispatch_keyset x full_backend_mask)
// NB: keys in this set also get associated with CompositeImplicitAutograd
//
// Note [autograd_dispatch_keyset Does Not Include Backend Bits]
// We don't want to include any backend bits (BackendComponent::CPUBit, etc)
// directly in autograd_dispatch_keyset.
// Why? keysets like autograd_dispatch_keyset are commonly used to remove
// autograd keys from a DispatchKeySet throughout the code base. However, you
// are only allowed to remove functionality bits from a keyset, not backend
// bits. See Note [Removing keys from DispatchKeySet Only Affects Functionality
// Keys] for details. To be consistent and avoid confusion, we're explicitly
// setting up autograd_dispatch_keyset to not have any backend bits.
constexpr DispatchKeySet autograd_dispatch_keyset = DispatchKeySet({
DispatchKey::AutogradFunctionality,
DispatchKey::AutogradOther,
DispatchKey::AutogradNestedTensor,
});
constexpr DispatchKeySet autocast_dispatch_keyset = DispatchKeySet({
DispatchKey::AutocastCPU,
DispatchKey::AutocastMPS,
DispatchKey::AutocastCUDA,
DispatchKey::AutocastXPU,
DispatchKey::AutocastIPU,
DispatchKey::AutocastHPU,
DispatchKey::AutocastXLA,
DispatchKey::AutocastPrivateUse1,
DispatchKey::AutocastMTIA,
DispatchKey::AutocastMAIA,
});
// See Note [TLS Initialization]
constexpr DispatchKeySet default_included_set = DispatchKeySet({
DispatchKey::BackendSelect,
DispatchKey::ADInplaceOrView,
});
constexpr DispatchKeySet default_excluded_set = DispatchKeySet({
DispatchKey::AutocastCPU,
DispatchKey::AutocastMPS,
DispatchKey::AutocastCUDA,
DispatchKey::AutocastXPU,
DispatchKey::AutocastIPU,
DispatchKey::AutocastHPU,
DispatchKey::AutocastXLA,
DispatchKey::AutocastPrivateUse1,
DispatchKey::AutocastMTIA,
DispatchKey::AutocastMAIA,
});
constexpr DispatchKeySet autograd_dispatch_keyset_with_ADInplaceOrView =
autograd_dispatch_keyset | DispatchKeySet(DispatchKey::ADInplaceOrView);
constexpr DispatchKeySet python_ks = DispatchKeySet({
DispatchKey::Python,
DispatchKey::PythonTLSSnapshot,
});
constexpr DispatchKeySet sparse_ks = DispatchKeySet(DispatchKey::Sparse);
constexpr DispatchKeySet sparse_csr_ks = DispatchKeySet(DispatchKey::SparseCsr);
constexpr DispatchKeySet mkldnn_ks = DispatchKeySet(DispatchKey::MkldnnCPU);
// backend dispatch keys that map to DispatchKey::AutogradOther
// NB: keys in this set also get associated with CompositeImplicitAutograd
constexpr DispatchKeySet autogradother_backends =
DispatchKeySet(
// HIP and VE aren't in this list: they now have their own backend bits
// which means that they can now have their own Autograd keys.
// Technically, HIP will now redispatch to its own custom AutogradHIP
// slot in the runtime table.
{DispatchKey::FPGA,
DispatchKey::Vulkan,
DispatchKey::Metal,
DispatchKey::CustomRNGKeyId,
DispatchKey::MkldnnCPU,
// Sparse and Quantized backends also live here.
DispatchKey::Sparse,
DispatchKey::SparseCsr,
DispatchKey::Quantized})
// Including the backend bits because this keyset is used during op
// registration, which requires looping over all runtime autogradother
// backend keys.
| DispatchKeySet(DispatchKeySet::RAW, full_backend_mask);
// The set of dispatch keys that come after autograd
// n.b. this relies on the fact that AutogradOther is currently the lowest
// Autograd key
constexpr DispatchKeySet after_autograd_keyset =
DispatchKeySet(DispatchKeySet::FULL_AFTER, c10::DispatchKey::AutogradOther);
// The set of dispatch keys that come after ADInplaceOrView
constexpr DispatchKeySet after_ADInplaceOrView_keyset = DispatchKeySet(
DispatchKeySet::FULL_AFTER,
c10::DispatchKey::ADInplaceOrView);
// The set of dispatch keys that come after Functionalize
constexpr DispatchKeySet after_func_keyset =
DispatchKeySet(DispatchKeySet::FULL_AFTER, c10::DispatchKey::Functionalize)
.remove(
// NOTE: we also need to remove ADInplaceOrView from the keyset when
// redispatching after the func kernels. This is because we're not
// calling the same op; we originally called an inplace op, and now
// we aren't. The original key calculation figured out which keys
// were Fallthrough based on the inplace op. That means that it did
// not include the ADInPlaceOrView kernel as a fallthrough key.
// However, we WANT the ADInPlaceOrView kernel to be ignored now
// that we're calling an out-of-place op. Re-invoking
// Dispatcher::call would re-run the Fallthrough key calculation and
// get us that, But at::redispatch is more performant. We can get
// away with it by explicitly removing the key here.
c10::DispatchKey::ADInplaceOrView);
constexpr DispatchKeySet backend_bitset_mask =
DispatchKeySet(DispatchKeySet::RAW, (1ULL << num_backends) - 1);
constexpr auto inplace_or_view_ks =
DispatchKeySet(DispatchKey::ADInplaceOrView);
constexpr auto autograd_cpu_ks = DispatchKeySet(DispatchKey::AutogradCPU);
constexpr auto autograd_ipu_ks = DispatchKeySet(DispatchKey::AutogradIPU);
constexpr auto autograd_mtia_ks = DispatchKeySet(DispatchKey::AutogradMTIA);
constexpr auto autograd_maia_ks = DispatchKeySet(DispatchKey::AutogradMAIA);
constexpr auto autograd_xpu_ks = DispatchKeySet(DispatchKey::AutogradXPU);
constexpr auto autograd_cuda_ks = DispatchKeySet(DispatchKey::AutogradCUDA);
constexpr auto autograd_xla_ks = DispatchKeySet(DispatchKey::AutogradXLA);
constexpr auto autograd_lazy_ks = DispatchKeySet(DispatchKey::AutogradLazy);
constexpr auto autograd_meta_ks = DispatchKeySet(DispatchKey::AutogradMeta);
constexpr auto autograd_mps_ks = DispatchKeySet(DispatchKey::AutogradMPS);
constexpr auto autograd_hpu_ks = DispatchKeySet(DispatchKey::AutogradHPU);
constexpr auto autograd_privateuse1_ks =
DispatchKeySet(DispatchKey::AutogradPrivateUse1);
constexpr auto autograd_privateuse2_ks =
DispatchKeySet(DispatchKey::AutogradPrivateUse2);
constexpr auto autograd_privateuse3_ks =
DispatchKeySet(DispatchKey::AutogradPrivateUse3);
constexpr auto autograd_other_ks = DispatchKeySet(DispatchKey::AutogradOther);
constexpr auto autograd_nested =
DispatchKeySet(DispatchKey::AutogradNestedTensor);
// keyset corresponding to functorch keys that have their own dedicated
// TensorImpl subclass.
constexpr auto functorch_transforms_ks = DispatchKeySet(
{DispatchKey::FuncTorchBatched,
DispatchKey::FuncTorchVmapMode,
DispatchKey::Batched,
DispatchKey::VmapMode,
DispatchKey::FuncTorchGradWrapper});
constexpr auto functorch_batched_ks =
DispatchKeySet({DispatchKey::FuncTorchBatched});
// This keyset has:
// (1) the functionality bits corresponding to backends (dense, sparse,
// quantized) (2) all of the backend bits set
constexpr DispatchKeySet backend_functionality_keys =
DispatchKeySet({
DispatchKey::Dense,
DispatchKey::Quantized,
DispatchKey::Sparse,
DispatchKey::SparseCsr,
}) |
DispatchKeySet(DispatchKeySet::RAW, full_backend_mask);
struct OpTableOffsetAndMask {
uint16_t offset;
uint16_t backend_mask;
};
static_assert(
num_backends <= 16,
"Right now we expect the number of backends not to exceed 16. In the (unlikely) event"
" that this changes, the size of OpTableOffsetAndMask::backend_mask needs to be increased too.");
// true if t is a backend dispatch key
C10_API bool isBackendDispatchKey(DispatchKey t);
// Resolve alias dispatch key to DispatchKeySet if applicable
C10_API DispatchKeySet getRuntimeDispatchKeySet(DispatchKey t);
// Resolve alias dispatch key to DispatchKeySet if applicable,
// and check if k is a part of that set
C10_API bool runtimeDispatchKeySetHas(DispatchKey t, DispatchKey k);
// Returns a DispatchKeySet of all backend keys mapped to Autograd dispatch key
// t, DispatchKeySet is empty if t is not alias of DispatchKey::Autograd.
C10_API DispatchKeySet getBackendKeySetFromAutograd(DispatchKey t);
// Returns a DispatchKeySet of autograd related keys mapped to backend.
// for a given backend key, use the associated autograd key.
// for non-backend keys, use AutogradOther as a default.
// Note: it's convenient and fast to return a default here rather than (say)
// returning an std::optional<DispatchKey>, or throwing. But it makes callers
// responsible for either a) enforcing the invariant that only backend keys
// be passed as arguments, or b) interpreting our return value carefully.
inline DispatchKeySet getAutogradRelatedKeySetFromBackend(BackendComponent t) {
switch (t) {
case BackendComponent::CPUBit:
return inplace_or_view_ks | autograd_cpu_ks;
case BackendComponent::IPUBit:
return inplace_or_view_ks | autograd_ipu_ks;
case BackendComponent::MTIABit:
return inplace_or_view_ks | autograd_mtia_ks;
case BackendComponent::MAIABit:
return inplace_or_view_ks | autograd_maia_ks;
case BackendComponent::XPUBit:
return inplace_or_view_ks | autograd_xpu_ks;
case BackendComponent::CUDABit:
return inplace_or_view_ks | autograd_cuda_ks;
case BackendComponent::XLABit:
return inplace_or_view_ks | autograd_xla_ks;
case BackendComponent::LazyBit:
return inplace_or_view_ks | autograd_lazy_ks;
case BackendComponent::MetaBit:
return inplace_or_view_ks | autograd_meta_ks;
case BackendComponent::MPSBit:
return inplace_or_view_ks | autograd_mps_ks;
case BackendComponent::HPUBit:
return inplace_or_view_ks | autograd_hpu_ks;
case BackendComponent::PrivateUse1Bit:
return inplace_or_view_ks | autograd_privateuse1_ks;
case BackendComponent::PrivateUse2Bit:
return inplace_or_view_ks | autograd_privateuse2_ks;
case BackendComponent::PrivateUse3Bit:
return inplace_or_view_ks | autograd_privateuse3_ks;
default:
return inplace_or_view_ks | autograd_other_ks;
}
}
// Returns a DispatchKeySet of autocast related keys mapped to backend.
inline DispatchKeySet getAutocastRelatedKeySetFromBackend(BackendComponent t) {
constexpr auto autocast_cpu_ks = DispatchKeySet(DispatchKey::AutocastCPU);
constexpr auto autocast_mtia_ks = DispatchKeySet(DispatchKey::AutocastMTIA);
constexpr auto autocast_maia_ks = DispatchKeySet(DispatchKey::AutocastMAIA);
constexpr auto autocast_xpu_ks = DispatchKeySet(DispatchKey::AutocastXPU);
constexpr auto autocast_ipu_ks = DispatchKeySet(DispatchKey::AutocastIPU);
constexpr auto autocast_hpu_ks = DispatchKeySet(DispatchKey::AutocastHPU);
constexpr auto autocast_cuda_ks = DispatchKeySet(DispatchKey::AutocastCUDA);
constexpr auto autocast_xla_ks = DispatchKeySet(DispatchKey::AutocastXLA);
constexpr auto autocast_privateuse1_ks =
DispatchKeySet(DispatchKey::AutocastPrivateUse1);
constexpr auto autocast_mps_ks = DispatchKeySet(DispatchKey::AutocastMPS);
switch (t) {
case BackendComponent::CPUBit:
return autocast_cpu_ks;
case BackendComponent::MTIABit:
return autocast_mtia_ks;
case BackendComponent::MAIABit:
return autocast_maia_ks;
case BackendComponent::XPUBit:
return autocast_xpu_ks;
case BackendComponent::IPUBit:
return autocast_ipu_ks;
case BackendComponent::HPUBit:
return autocast_hpu_ks;
case BackendComponent::CUDABit:
return autocast_cuda_ks;
case BackendComponent::XLABit:
return autocast_xla_ks;
case BackendComponent::PrivateUse1Bit:
return autocast_privateuse1_ks;
case BackendComponent::MPSBit:
return autocast_mps_ks;
default:
return DispatchKeySet();
}
}
// returns the "backend" DispatchKey of highest priority in the set.
// This is basically like highestBackendKey(), except that we have some
// "functionality" bits that correspond to backends (Sparse, Quantized)
inline DispatchKey highestPriorityBackendTypeId(DispatchKeySet ks) {
return (ks & backend_functionality_keys).highestPriorityTypeId();
}
// This API exists because we have a use case for checking
// getRuntimeDispatchKeySet(alias).has(DispatchKey::Undefined)
// in OperatorEntry.cpp but we disallow it in has() API.
C10_API bool isIncludedInAlias(DispatchKey k, DispatchKey alias);
// Historically, every tensor only had a single DispatchKey, and it was always
// something like CPU, and there wasn't any of this business where TLS
// could cause the DispatchKey of a tensor to change. But we still have some
// legacy code that is still using DispatchKey for things like instanceof
// checks; if at all possible, refactor the code to stop using DispatchKey in
// those cases.
inline DispatchKey legacyExtractDispatchKey(DispatchKeySet s) {
// NB: If you add any extra keys that can be stored in TensorImpl on
// top of existing "backend" keys like CPU/CUDA, you need to add it
// here. At the moment, autograd keys and ADInplaceOrView key need this
// treatment;
return (s - autograd_dispatch_keyset_with_ADInplaceOrView -
autocast_dispatch_keyset -
DispatchKeySet(
{DispatchKey::Functionalize,
DispatchKey::PythonTLSSnapshot,
DispatchKey::FuncTorchGradWrapper,
DispatchKey::FuncTorchVmapMode,
DispatchKey::FuncTorchBatched,
DispatchKey::Python}))
.highestPriorityTypeId();
}
template <class T>
using is_not_DispatchKeySet = std::negation<std::is_same<DispatchKeySet, T>>;
// Given a function type, constructs a function_traits type that drops the first
// parameter type if the first parameter is of type DispatchKeySet. NB:
// DispatchKeySet is currently explicitly hidden from JIT (mainly to avoid
// pushing unnecessary arguments on the stack - see Note [ Plumbing Keys Through
// the Dispatcher] for details). If at any point in the future we need to expose
// this type to JIT, revisit the usage of this type alias.
template <class FuncType>
using remove_DispatchKeySet_arg_from_func = guts::make_function_traits_t<
typename guts::infer_function_traits_t<FuncType>::return_type,
typename std::conditional_t<
std::is_same_v<
DispatchKeySet,
typename guts::typelist::head_with_default_t<
void,
typename guts::infer_function_traits_t<
FuncType>::parameter_types>>,
guts::typelist::drop_if_nonempty_t<
typename guts::infer_function_traits_t<FuncType>::parameter_types,
1>,
typename guts::infer_function_traits_t<FuncType>::parameter_types>>;
} // namespace c10