Executor

types.h

template<> struct TypeTraits<std::int8_t>

Public Static Attributes

static constexpr auto value = DataType::kINT8 

template<> struct TypeTraits<std::int32_t>

Public Static Attributes

static constexpr auto value = DataType::kINT32 

template<> struct TypeTraits<std::int64_t>

Public Static Attributes

static constexpr auto value = DataType::kINT64 

template<> struct TypeTraits<std::uint8_t>

Public Static Attributes

static constexpr auto value = DataType::kUINT8 

namespace tensorrt_llm

namespace executor

Typedefs

using TensorPtr = std::shared_ptr<Tensor>

using SizeType32 = std::int32_t

using FloatType = float

using TokenIdType = std::int32_t

using VecTokens = std::vector<TokenIdType>

using BeamTokens = std::vector<VecTokens>

using IdType = std::uint64_t

using VecTokenExtraIds = std::vector<IdType>

using IterationType = std::uint64_t

using RandomSeedType = std::uint64_t

using VecLogProbs = std::vector<FloatType>

using StreamPtr = std::shared_ptr<tensorrt_llm::runtime::CudaStream>

using MillisecondsType = std::chrono::milliseconds

using LogitsPostProcessor = std::function<void(IdType, Tensor&, BeamTokens const&, StreamPtr const&, std::optional<IdType>)>

using LogitsPostProcessorMap = std::unordered_map<std::string, LogitsPostProcessor>

using LogitsPostProcessorBatched = std::function<void(std::vector<IdType> const&, std::vector<Tensor>&, std::vector<std::reference_wrapper<BeamTokens const>> const&, StreamPtr const&, std::vector<std::optional<IdType>> const&)>

using MedusaChoices = std::vector<std::vector<SizeType32>>

using EagleChoices = std::vector<std::vector<SizeType32>>

using PriorityType = float

using BufferView = std::basic_string_view<uint8_t>

Enums

enum class DataType

Values:

enumerator kBOOL

enumerator kUINT8

enumerator kINT8

enumerator kINT32

enumerator kINT64

enumerator kBF16

enumerator kFP8

enumerator kFP16

enumerator kFP32

enumerator kUNKNOWN

enum class RequestType

Values:

enumerator REQUEST_TYPE_CONTEXT_AND_GENERATION

enumerator REQUEST_TYPE_CONTEXT_ONLY

enumerator REQUEST_TYPE_GENERATION_ONLY

enum class MemoryType

Values:

enumerator kCPU

enumerator kCPU_PINNED

enumerator kCPU_PINNEDPOOL

enumerator kGPU

enumerator kUVM

enumerator kUNKNOWN

enum class ModelType

Values:

enumerator kDECODER_ONLY

enumerator kENCODER_ONLY

enumerator kENCODER_DECODER

enum class BatchingType

The batching type.

Values:

enumerator kSTATIC: STATIC refers to the traditional batching scheme with a batch of requests running in lockstep until the full generation for all of them is complete. Requests in a batch are all padded up to the maximum input and output sequence length of any member of the batch.

enumerator kINFLIGHT: INFLIGHT refers to a scheme where newly arrived requests are dynamically incorporated into the batch under execution, and requests are returned as soon as the end condition is met without any padding.

enum class CapacitySchedulerPolicy

The policy used to select the subset of available requests in each iteration of the executor generation loop.

Values:

enumerator kMAX_UTILIZATION: MAX_UTILIZATION packs as many requests as the underlying TRT engine can support in any iteration of the InflightBatching generation loop. While this is expected to maximize GPU throughput, it might require that some requests be paused and restarted depending on peak KV cache memory availability.

enumerator kGUARANTEED_NO_EVICT: GUARANTEED_NO_EVICT uses KV cache more conservatively guaranteeing that a request, once started, will run to completion without eviction.

enumerator kSTATIC_BATCH: kSTATIC_BATCH does not schedule new requests until all requests in current batch are completed. Similar to kGUARANTEED_NO_EVICT, requests will run to completion without eviction.

enum class ContextChunkingPolicy

Values:

enumerator kFIRST_COME_FIRST_SERVED: Sequential chunking, complete the unfinished context phase first.

enumerator kEQUAL_PROGRESS: Iterate through each context request in sequence and attempt to increase its chunk count until the constraint is exceeded.

enum class CommunicationType

Values:

enumerator kMPI

enum class CommunicationMode

Values:

enumerator kLEADER

enumerator kORCHESTRATOR

enum class RequestStage

Enum class that represents the state of a request.

Values:

enumerator kQUEUED: Request that have been received but not yet included in the active requests (due to constraints such as maximum batch size for example).

enumerator kENCODER_IN_PROGRESS: Active request in encoder phase.

enumerator kCONTEXT_IN_PROGRESS: Active request in context phase.

enumerator kGENERATION_IN_PROGRESS: Active request in generation phase.

enumerator kGENERATION_COMPLETE: Active request for which generation has completed.

enum class FinishReason

The reason why the model stopped generating tokens for a request.

Values:

enumerator kNOT_FINISHED: The request is not finished.

enumerator kEND_ID: The request finished because the end id was generated.

enumerator kSTOP_WORDS: The request finished because a stop word was generated.

enumerator kLENGTH: The request finished because the maximum number of tokens was reached.

enumerator kTIMED_OUT: The request finished because it got timed out (via the mAllotedTime parameter)

enumerator kCANCELLED: The request was cancelled by calling cancelRequest.

Functions

std::ostream &operator<<(std::ostream &os, CapacitySchedulerPolicy policy)

std::ostream &operator<<(std::ostream &os, ContextChunkingPolicy policy)

template<typename T, bool = false> struct TypeTraits: #include <types.h>

For converting a C++ data type to a TrtLmmDataType.

template<> struct TypeTraits<float>

Public Static Attributes

static constexpr auto value = DataType::kFP32 

template<> struct TypeTraits<half>

Public Static Attributes

static constexpr auto value = DataType::kFP16 

template<> int8_t >

Public Static Attributes

static constexpr auto value = DataType::kINT8 

template<> int32_t >

Public Static Attributes

static constexpr auto value = DataType::kINT32

template<> int64_t >

Public Static Attributes

static constexpr auto value = DataType::kINT64

template<> struct TypeTraits<bool>

Public Static Attributes

static constexpr auto value = DataType::kBOOL 

template<> uint8_t >

Public Static Attributes

static constexpr auto value = DataType::kUINT8

template<typename T> struct TypeTraits<T*>

Public Static Attributes

static constexpr auto value = DataType::kINT64 

struct KvCacheStats

#include <types.h>

Struct that holds the stats of a KV cache manager.

Public Members

SizeType32 maxNumBlocks: Max number of blocks.

SizeType32 freeNumBlocks: Number of free blocks.

SizeType32 usedNumBlocks: Number of used blocks.

SizeType32 tokensPerBlock: Number of tokens per block.

SizeType32 allocTotalBlocks: Number of total allocated block.

SizeType32 allocNewBlocks: Number of newly allocated block.

SizeType32 reusedBlocks: Number of reused block.

SizeType32 missedBlocks: Number of not reused block.

float cacheHitRate: Measuring the KV Cache reuse rate. cacheHitRate = reusedBlocks / (reusedBlocks + missedBlocks).

struct StaticBatchingStats

#include <types.h>

Struct that holds the stats of static batching models for a single iteration.

Public Members

SizeType32 numScheduledRequests: Number of scheduled requests.

SizeType32 numContextRequests: Number of requests in context stage.

SizeType32 numCtxTokens: Total number of context tokens in the iteration.

SizeType32 numGenTokens: Total number of tokens to generate in the iteration.

SizeType32 emptyGenSlots: Total number of unused generation token slots.

struct InflightBatchingStats

#include <types.h>

Struct that holds the stats of inflight batching models for a single iteration.

Public Members

SizeType32 numScheduledRequests: Number of scheduled requests.

SizeType32 numContextRequests: Number of requests in context stage.

SizeType32 numGenRequests: Number of requests in generation stage.

SizeType32 numPausedRequests: Number of paused requests.

SizeType32 numCtxTokens: Total number of context tokens in the iteration.

SizeType32 microBatchId: Index of mirco batch.

float avgNumDecodedTokensPerIter: Average number of tokens decoded per request per iteration.

struct IterationStats

#include <types.h>

Struct that holds the stats of a single iteration.

Public Members

std::string timestamp: Ending time of this iteration.

IterationType iter: Iteration id.

double iterLatencyMS: Iteration latency (ms)

double newActiveRequestsQueueLatencyMS: The total time spent in queue by the requests that became active in this iteration (ms)

SizeType32 numNewActiveRequests: Number of new fetched active requests.

SizeType32 numActiveRequests: Number of active requests.

SizeType32 numQueuedRequests: Number of queued requests.

SizeType32 numCompletedRequests: Number of requests that were completed in this iteration.

SizeType32 maxNumActiveRequests: Number of max active requests.

SizeType32 maxBatchSizeStatic: Static max batch size passed to the executor.

SizeType32 maxBatchSizeTunerRecommended: Batch size produced by dynamic tuner based on input stats.

SizeType32 maxBatchSizeRuntime: @brife The min of maxBatchSizeStatic and maxBatchSizeRuntimeUpperbound

SizeType32 maxNumTokensStatic: @brife Static max num tokens passed to the executor

SizeType32 maxNumTokensTunerRecommended: @brife Max num tokens produced by dynamic tuner based on input stats

SizeType32 maxNumTokensRuntime: @brife The runtime max num tokens

size_t gpuMemUsage: GPU memory usage in bytes.

size_t cpuMemUsage: CPU memory usage in bytes.

size_t pinnedMemUsage: Pinned memory usage in bytes.

std::optional<KvCacheStats> kvCacheStats: Stats specific to KV caches.

std::optional<KvCacheStats> crossKvCacheStats: Stats specific to cross KV caches.

std::optional<StaticBatchingStats> staticBatchingStats: Stats specific to static batching.

std::optional<InflightBatchingStats> inflightBatchingStats: Stats specific to inflight batching.

struct DisServingRequestStats

#include <types.h>

Struct that holds the request stats in the case of disaggregated serving.

Public Members

double kvCacheTransferMS: The total time spent on transferring KV cache from context phase to generation phase (ms)

struct RequestStats

#include <types.h>

Struct that holds the stats of a single request.

Public Members

IdType id: The request id.

RequestStage stage: The current stage the request is in.

SizeType32 contextPrefillPosition: If using chunked context, the current context prefill position.

SizeType32 numGeneratedTokens: The number of generated tokens so far.

float avgNumDecodedTokensPerIter: The average number of decoded tokens per iteration. It is >= 1 for speculative decoding.

bool scheduled: Whether the request is scheduled for the current iteration.

bool paused: Whether the request is being paused at the current iteration due to lack of resources (KV cache blocks exhaustion for example)

std::optional<DisServingRequestStats> disServingStats: Stats specific to disaggregated serving.

SizeType32 allocTotalBlocksPerRequest: Number of total allocated blocks per request.

SizeType32 allocNewBlocksPerRequest: Number of newly allocated blocks per request.

SizeType32 reusedBlocksPerRequest: Number of reused blocks per request.

SizeType32 missedBlocksPerRequest: Number of missed blocks per request.

SizeType32 kvCacheHitRatePerRequest: KV Cache Hit Rate per request, defined as reusedBlocks / (reusedBlocks + missedBlocks)

struct RequestStatsPerIteration

#include <types.h>

Struct that holds the stats of all requests in an iteration.

Public Members

IterationType iter: The iteration id for these stats.

std::vector<RequestStats> requestStats: The stats of all active requests for this iteration.

struct RequestPerfMetrics

#include <types.h>

Struct that holds the stats of a request.

Public Types

using TimePoint = std::chrono::time_point<std::chrono::steady_clock>

Public Members

TimingMetrics timingMetrics

KvCacheMetrics kvCacheMetrics

std::optional<IterationType> firstIter: First iteration where the request was processed.

std::optional<IterationType> lastIter: Last iteration where a token was generated.

std::optional<IterationType> iter: Current iteration.

struct KvCacheMetrics

Public Members

SizeType32 numTotalAllocatedBlocks = {0}: Number of total allocated blocks.

SizeType32 numNewAllocatedBlocks = {0}: Number of newly allocated blocks.

SizeType32 numReusedBlocks = {0}: Number of reused blocks.

SizeType32 numMissedBlocks = {0}: Number of missed blocks.

SizeType32 kvCacheHitRate = {0}: KV Cache Hit Rate, defined as reusedBlocks / (reusedBlocks + missedBlocks)

struct TimingMetrics

Public Members

TimePoint arrivalTime: The time when the request arrived.

TimePoint firstScheduledTime: The time when the request was first scheduled.

TimePoint firstTokenTime: The time when the first token was generated.

TimePoint lastTokenTime: The time when the request was finished.

TimePoint kvCacheTransferStart: Start time of the KV cache transfer for disaggregated serving.

TimePoint kvCacheTransferEnd: End time of the KV cache transfer for disaggregated serving.

struct DebugTensorsPerIteration

#include <types.h>

Struct that holds the debug tensors in an iteration.

Public Members

IterationType iter: The iteration id for these tensors.

std::map<std::string, Tensor> debugTensors: The debug tensors for this iteration.

class DecodingMode

#include <types.h>

mode of the decoder

Public Types

using UnderlyingType = uint32_t

Public Functions

inline constexpr auto useTemperature(bool useTemp)

inline constexpr auto useOccurrencePenalties(bool usePenalty)

inline constexpr auto usePresencePenalty(bool usePenalty)

inline constexpr auto useRepetitionPenalty(bool usePenalty)

inline constexpr auto useFrequencyPenalty(bool usePenalty)

inline constexpr auto useMinLength(bool useMinLen)

inline constexpr auto useBanTokens(bool banTokens)

inline constexpr auto useBanWords(bool banWords)

inline constexpr auto useNoRepeatNgramSize(bool noRepeatNgramSize)

inline constexpr auto useStopWords(bool stopWords)

inline constexpr auto useMaxLengthStop(bool maxLengthStop)

inline constexpr auto useExplicitEosStop(bool explicitEosStop)

inline constexpr bool isAuto() const

inline constexpr bool isTopK() const

inline constexpr bool isTopP() const

inline constexpr bool isTopKorTopP() const

inline constexpr bool isTopKandTopP() const

inline constexpr bool isBeamSearch() const

inline constexpr bool isMedusa() const

inline constexpr bool isLookahead() const

inline constexpr bool isExplicitDraftTokens() const

inline constexpr bool isExternalDraftTokens() const

inline constexpr bool isEagle() const

inline constexpr bool isUseTemperature() const

inline constexpr bool isUsePresencePenalty() const

inline constexpr bool isUseFrequencyPenalty() const

inline constexpr bool isUseRepetitionPenalty() const

inline constexpr bool isUseMinLength() const

inline constexpr bool isUseOccurrencePenalty() const

inline constexpr bool isUsePenalty() const

inline constexpr bool isUseBanWords() const

inline constexpr bool isUseNoRepeatNgramSize() const

inline constexpr bool isUseBanTokens() const

inline constexpr bool isUseStopWords() const

inline constexpr bool isUseMaxLengthStop() const

inline constexpr bool isUseExplicitEosStop() const

inline constexpr bool isUseStopCriteria() const

inline bool operator==(DecodingMode const &other) const

inline explicit constexpr DecodingMode(UnderlyingType state)

inline constexpr UnderlyingType getState() const

Public Static Functions

static inline constexpr auto Auto(): No mode specified. Config will be determined from the beam width of the first request at runtime TopKTopP if beamWidth == 1, BeamSearch otherwise.

static inline constexpr auto TopK()

static inline constexpr auto TopP()

static inline constexpr auto TopKTopP()

static inline constexpr auto BeamSearch()

static inline constexpr auto Medusa()

static inline constexpr auto Lookahead()

static inline constexpr auto ExplicitDraftTokens()

static inline constexpr auto ExternalDraftTokens()

static inline constexpr auto Eagle()

Private Functions

inline constexpr bool anyBitSet(UnderlyingType bits) const

inline constexpr bool allBitSet(UnderlyingType bits) const

inline constexpr UnderlyingType setBitTo(UnderlyingType state, bool x)

Private Members

UnderlyingType mState = {}

Private Static Attributes

static constexpr UnderlyingType kUseRepetitionPenalties = {1u << 0}

static constexpr UnderlyingType kUseFrequencyPenalties = {1u << 1}

static constexpr UnderlyingType kUsePresencePenalties = {1u << 2}

static constexpr UnderlyingType kUseTemperature = {1u << 3}

static constexpr UnderlyingType kUseMinLength = {1u << 4}

static constexpr UnderlyingType kUseBanWords = {1u << 5}

static constexpr UnderlyingType kUseStopWords = {1u << 6}

static constexpr UnderlyingType kUseMaxLengthStop = {1u << 7}

static constexpr UnderlyingType kUseExplicitEosStop = {1u << 8}

static constexpr UnderlyingType kUseNoRepeatNgramSize = {1u << 9}

static constexpr UnderlyingType kStandardStopCriteria = {kUseStopWords | kUseMaxLengthStop}

static constexpr UnderlyingType kUseOccurrencePenalties{kUseRepetitionPenalties | kUseFrequencyPenalties | kUsePresencePenalties}

static constexpr UnderlyingType kUsePenalties = {kUseOccurrencePenalties | kUseTemperature | kUseMinLength}

static constexpr UnderlyingType kUseBanTokens = {kUseNoRepeatNgramSize | kUseBanWords}

static constexpr SizeType32 kNumFlags = {10}

static constexpr UnderlyingType kAuto = {1u << (kNumFlags + 0)}

static constexpr UnderlyingType kTopK = {1u << (kNumFlags + 1)}

static constexpr UnderlyingType kTopP = {1u << (kNumFlags + 2)}

static constexpr UnderlyingType kBeamSearch = {1u << (kNumFlags + 3)}

static constexpr UnderlyingType kMedusa = {1u << (kNumFlags + 4)}

static constexpr UnderlyingType kLookahead = {1u << (kNumFlags + 5)}

static constexpr UnderlyingType kExplicitDraftTokens = {1u << (kNumFlags + 6)}

static constexpr UnderlyingType kExternalDraftTokens = {1u << (kNumFlags + 7)}

static constexpr UnderlyingType kEagle = {1u << (kNumFlags + 8)}

static constexpr UnderlyingType kTopKTopP = {kTopK | kTopP}

namespace runtime

disaggServerUtil.h

namespace tensorrt_llm

namespace executor

namespace disagg_executor

struct ResponseWithId

Public Functions

inline ResponseWithId(tensorrt_llm::executor::Response &&response, IdType gid)

inline ResponseWithId(tensorrt_llm::executor::Response const &response, IdType gid)

inline ResponseWithId(ResponseWithId &&other) noexcept

ResponseWithId(ResponseWithId const &other) = default

inline ResponseWithId &operator=(ResponseWithId &&other) noexcept

inline ResponseWithId &operator=(ResponseWithId const &other)

~ResponseWithId() = default

Public Members

tensorrt_llm::executor::Response response

IdType gid

class DisaggExecutorOrchestrator

Public Functions

DisaggExecutorOrchestrator(std::vector<std::filesystem::path> const &ctxEnginePaths, std::vector<std::filesystem::path> const &genEnginePaths, std::vector<executor::ExecutorConfig> const &ctxExecutorConfigs, std::vector<executor::ExecutorConfig> const &genExecutorConfigs, bool hasContextAwaitThreads, bool hasGenAwaitThreads)

Constructs a DisaggExecutorOrchestrator object.

Parameters:

ctxEnginePaths – A vector of file paths to context engine files.
genEnginePaths – A vector of file paths to generation engine files.
ctxExecutorConfigs – A vector of ExecutorConfig for context executors.
genExecutorConfigs – A vector of ExecutorConfig for generation executors.
hasContextAwaitThreads – Whether or not there are threads that receive response for each generation executor.
hasGenAwaitThreads – Whether or not there are threads that receive response for each generation executor.

std::vector<IdType> enqueueContext(std::vector<texec::Request> const &requests, std::optional<int> selectContextId = std::nullopt, bool batch = false)

Enqueue context-only requests to context executors.

Parameters:

requests – A vector of context-only requests.
selectContextId – The index of the context executor to use. If std::nullopt, the executor that has the smallest number of inflight requests will be used.
batch – If true,enqueue requests in same context executor.If false, will try to use a different executor for each request.

Returns:

A vector of global request ids, corresponding to the order of the requests in requests, the id returned may be different from the request id in each executor.

void enqueueGeneration(std::vector<texec::Request> const &requests, std::vector<IdType> const &globalRequestIds, std::optional<int> selectGenIdx = std::nullopt, bool batch = false)

Enqueue generation-only requests to generation executors.

Parameters:

requests – A vector of generation-only requests.
globalRequestIds – A vector of global request ids, corresponding to the order of the requests,and must be the ids returned by the enqueueContext function.
selectGenIdx – The index of the generation executor to use. If std::nullopt, the executor that has the smallest number of inflight requests will be used.
batch – If true,enqueue requests in same generation executor.If false, will try to use a different executor for each request.

std::vector<ResponseWithId> awaitContextResponses(std::optional<std::chrono::milliseconds> const &timeout, std::optional<int> contextIdx = std::nullopt)

Await for context responses.

Parameters:

timeout – The maximum time to wait for new responses
contextIdx – The index of the context executor to use. If std::nullopt, return ready responses in all context executors,if hasContextAwaitThreads is true, then this parameter must be std::nullopt.

Returns:

A vector of responses with corresponding global request ids

std::vector<ResponseWithId> awaitGenerationResponses(std::optional<std::chrono::milliseconds> const &timeout, std::optional<int> genIdx = std::nullopt)

Await for generation responses.

Parameters:

timeout – The maximum time to wait for new responses.
genIdx – The index of the generation executor to use. If std::nullopt, return ready responses in all generation executors,if hasGenAwaitThreads is true, then this parameter must be std::nullopt.

Returns:

A vector of responses with corresponding global request ids.

bool canEnqueue() const: Indicates if the current process is allowed to enqueueRequests.

std::vector<std::unique_ptr<texec::Executor>> const &getContextExecutors() const: Get context executors.

std::vector<std::unique_ptr<texec::Executor>> const &getGenExecutors() const: Get generation executors.

~DisaggExecutorOrchestrator()

Private Members

std::unique_ptr<Impl> mImpl

tensor.h

namespace tensorrt_llm

namespace executor

class Shape : public tensorrt_llm::common::ArrayView<detail::DimType64 const>

Public Types

using Base = tensorrt_llm::common::ArrayView<detail::DimType64 const>

using DimType64 = typename std::remove_cv_t<Base::value_type>

Public Functions

inline Shape()

inline Shape(DimType64 const *data, Base::size_type size)

inline Shape(std::initializer_list<DimType64> dims)

class Tensor

Public Types

using CudaStreamPtr = std::shared_ptr<runtime::CudaStream>

Public Functions

Tensor copyToCpu(Tensor::CudaStreamPtr stream = nullptr) const

Tensor copyToPinned(Tensor::CudaStreamPtr stream = nullptr) const

Tensor copyToPooledPinned(Tensor::CudaStreamPtr stream = nullptr) const

Tensor copyToManaged(Tensor::CudaStreamPtr stream = nullptr) const

Tensor copyToGpu(Tensor::CudaStreamPtr stream) const

Tensor() noexcept = default

~Tensor() = default

Tensor(Tensor const &other) noexcept = default

Tensor(Tensor &&other) noexcept = default

Tensor &operator=(Tensor const &other) noexcept = default

Tensor &operator=(Tensor &&other) noexcept = default

void *getData(): Returns a pointer to underlying array.

void const *getData() const: Returns a pointer to underlying array.

DataType getDataType() const: Returns the data type of the buffer.

MemoryType getMemoryType() const: Returns the memory type of the buffer.

Shape getShape() const: Returns the tensor dimensions.

std::size_t getSize() const: Returns the number of elements in the tensor.

std::size_t getSizeInBytes() const: Returns the size of the tensor in bytes.

void setZero(CudaStreamPtr stream = nullptr)

Set the entire memory to zero.

Parameters:: stream – Must be a valid CUDA stream if the memory type is GPU.

void setFrom(Tensor const &other, CudaStreamPtr stream = nullptr)

Copy the data and shape from another tensor.

Parameters:

other – A tensor to copy from.
stream – Must be a valid CUDA stream if the memory type is GPU.

inline explicit operator bool() const

inline bool operator==(Tensor const &rhs) const

inline bool operator!=(Tensor const &rhs) const

Public Static Functions

static Tensor cpu(DataType dataType, Shape shape = {})

Allocate a cpu tensor with the given shape and data type.

Parameters:

shape – The shape of the tensor.
dataType – The data type of the tensor.

template<typename T> static inline Tensor cpu(Shape shape = {})

static Tensor pinned(DataType dataType, Shape shape = {})

Allocate a cpu tensor in pinned memory with the given shape and data type.

Parameters:

shape – The shape of the tensor.
dataType – The data type of the tensor.

template<typename T> static inline Tensor pinned(Shape shape = {})

static Tensor pooledPinned(DataType dataType, Shape shape = {})

Allocate a cpu tensor in pooled pinned memory with the given shape and data type.

Parameters:

shape – The shape of the tensor.
dataType – The data type of the tensor.

template<typename T> static inline Tensor pooledPinned(Shape shape = {})

static Tensor managed(DataType dataType, Shape shape = {})

Allocate a tensor in managed memory (UVM) with the given shape and data type.

Parameters:

shape – The shape of the tensor.
dataType – The data type of the tensor.

template<typename T> static inline Tensor managed(Shape shape = {})

static Tensor gpu(DataType dataType, CudaStreamPtr stream, Shape shape = {})

Allocate a gpu tensor with the given shape and data type on a particular cuda stream.

Parameters:

shape – The shape of the tensor.
stream – Specifies the CUDA stream on which to allocate the tensor for GPU memory.
dataType – The data type of the tensor.

template<typename T> static inline Tensor gpu(CudaStreamPtr stream, Shape shape = {})

static Tensor of(DataType dataType, void *data, Shape shape)

Wrap a data pointer into a tensor without taking ownership.

Parameters:

shape – The shape of the tensor.
dataType – The data type of the tensor.
stream – Specifies the CUDA stream on which to allocate the tensor for GPU memory.

template<typename T> static inline Tensor of(T *data, Shape shape)

Wrap a data pointer into a tensor without taking ownership.

Parameters:

shape – The shape of the tensor.
dataType – The data type of the tensor.
stream – Specifies the CUDA stream on which to allocate the tensor for GPU memory.

template<typename T> static inline Tensor of(T &data)

Wrap any container into a tensor without taking ownership.

Parameters:

shape – The shape of the tensor.
dataType – The data type of the tensor.
stream – Specifies the CUDA stream on which to allocate the tensor for GPU memory.

Private Types

using Impl = runtime::ITensor 

Private Functions

explicit Tensor(std::shared_ptr<runtime::ITensor> tensor)

Tensor copyTo(std::shared_ptr<Impl> tensor, CudaStreamPtr stream) const

Private Members

std::shared_ptr<Impl> mTensor

Private Static Functions

template<typename T> static inline DataType getRuntimeType()

Friends

friend class Serialization

friend std::shared_ptr<runtime::ITensor> const &toITensor(Tensor const &tensor)

friend Tensor ofITensor(std::shared_ptr<runtime::ITensor> tensor)

namespace detail

Typedefs

using DimType64 = int64_t

Functions

std::shared_ptr<runtime::ITensor> const &toITensor(Tensor const &tensor)

Tensor ofITensor(std::shared_ptr<runtime::ITensor> tensor)

namespace runtime

executor.h

namespace tensorrt_llm

namespace batch_manager

namespace kv_cache_manager

namespace executor

Typedefs

using RetentionPriority = SizeType32 

using KVCacheEventData = std::variant<KVCacheCreatedData, KVCacheStoredData, KVCacheRemovedData, KVCacheUpdatedData>

Functions

char const *version() noexcept: Version of TRT-LLM.

class SamplingConfig

#include <executor.h>

Sampling configuration.

Public Functions

explicit SamplingConfig(SizeType32 beamWidth = 1, std::optional<SizeType32> const &topK = std::nullopt, std::optional<FloatType> const &topP = std::nullopt, std::optional<FloatType> const &topPMin = std::nullopt, std::optional<TokenIdType> const &topPResetIds = std::nullopt, std::optional<FloatType> const &topPDecay = std::nullopt, std::optional<RandomSeedType> const &seed = std::nullopt, std::optional<FloatType> const &temperature = std::nullopt, std::optional<SizeType32> const &minTokens = std::nullopt, std::optional<FloatType> const &beamSearchDiversityRate = std::nullopt, std::optional<FloatType> const &repetitionPenalty = std::nullopt, std::optional<FloatType> const &presencePenalty = std::nullopt, std::optional<FloatType> const &frequencyPenalty = std::nullopt, std::optional<FloatType> const &lengthPenalty = std::nullopt, std::optional<SizeType32> const &earlyStopping = std::nullopt, std::optional<SizeType32> const &noRepeatNgramSize = std::nullopt, std::optional<SizeType32> const &numReturnSequences = std::nullopt): Constructor for SamplingConfig See description of parameters below.

bool operator==(SamplingConfig const &other) const

SizeType32 getBeamWidth() const

SizeType32 getNumReturnBeams() const

std::optional<SizeType32> getTopK() const

std::optional<FloatType> getTopP() const

std::optional<FloatType> getTopPMin() const

std::optional<SizeType32> getTopPResetIds() const

std::optional<FloatType> getTopPDecay() const

std::optional<RandomSeedType> getSeed() const

std::optional<RandomSeedType> getRandomSeed() const

std::optional<FloatType> getTemperature() const

std::optional<SizeType32> getMinTokens() const

std::optional<SizeType32> getMinLength() const

std::optional<FloatType> getBeamSearchDiversityRate() const

std::optional<FloatType> getRepetitionPenalty() const

std::optional<FloatType> getPresencePenalty() const

std::optional<FloatType> getFrequencyPenalty() const

std::optional<FloatType> getLengthPenalty() const

std::optional<SizeType32> getEarlyStopping() const

std::optional<SizeType32> getNoRepeatNgramSize() const

std::optional<SizeType32> getNumReturnSequences() const

void setBeamWidth(SizeType32 beamWidth)

void setTopK(std::optional<SizeType32> const &topK)

void setTopP(std::optional<FloatType> const &topP)

void setTopPMin(std::optional<FloatType> const &topPMin)

void setTopPResetIds(std::optional<TokenIdType> const &topPResetIds)

void setTopPDecay(std::optional<FloatType> const &topPDecay)

void setSeed(std::optional<RandomSeedType> const &seed)

void setRandomSeed(std::optional<RandomSeedType> const &randomSeed)

void setTemperature(std::optional<FloatType> const &temperature)

void setMinTokens(std::optional<SizeType32> const &minTokens)

void setMinLength(std::optional<SizeType32> const &minLength)

void setBeamSearchDiversityRate(std::optional<FloatType> const &beamSearchDiversityRate)

void setRepetitionPenalty(std::optional<FloatType> const &repetitionPenalty)

void setPresencePenalty(std::optional<FloatType> const &presencePenalty)

void setFrequencyPenalty(std::optional<FloatType> const &frequencyPenalty)

void setLengthPenalty(std::optional<FloatType> const &lengthPenalty)

void setEarlyStopping(std::optional<SizeType32> const &earlyStopping)

void setNoRepeatNgramSize(std::optional<SizeType32> const &noRepeatNgramSize)

void setNumReturnSequences(std::optional<SizeType32> const &numReturnSequences)

Private Functions

void updateNumReturnBeams()

Private Members

SizeType32 mBeamWidth: The beam width. Default is 1 which disables beam search.

std::optional<SizeType32> mTopK: Controls number of logits to sample from. Default is 0 (all logits).

std::optional<FloatType> mTopP: Controls the top-P probability to sample from. Default is 0.f.

std::optional<FloatType> mTopPMin: Controls decay in the top-P algorithm. topPMin is lower-bound. Default is 1.e-6.

std::optional<TokenIdType> mTopPResetIds: Controls decay in the top-P algorithm. Indicates where to reset the decay. Default is 1.

std::optional<FloatType> mTopPDecay: Controls decay in the top-P algorithm. The decay value. Default is 1.f.

std::optional<RandomSeedType> mSeed: Controls the random seed used by the random number generator in sampling.

std::optional<FloatType> mTemperature: Controls the modulation of logits when sampling new tokens. It can have values > 0.f. Default is 1.0f.

std::optional<SizeType32> mMinTokens: Lower bound on the number of tokens to generate. Values < 1 have no effect. Default is 1.

std::optional<FloatType> mBeamSearchDiversityRate: Controls the diversity in beam search.

std::optional<FloatType> mRepetitionPenalty: Used to penalize tokens based on how often they appear in the sequence. It can have any value > 0.f. Values < 1.f encourages repetition, values > 1.f discourages it. Default is 1.f.

std::optional<FloatType> mPresencePenalty: Used to penalize tokens already present in the sequence (irrespective of the number of appearances). It can have any values. Values < 0.f encourage repetition, values > 0.f discourage it. Default is 0.f.

std::optional<FloatType> mFrequencyPenalty: Used to penalize tokens already present in the sequence (dependent on the number of appearances). It can have any values. Values < 0.f encourage repetition, values > 0.f discourage it. Default is 0.f.

std::optional<FloatType> mLengthPenalty: Controls how to penalize longer sequences in beam search. Default is 0.f.

std::optional<SizeType32> mEarlyStopping: Controls whether the generation process finishes once beamWidth sentences are generated (ends with end_token)

std::optional<SizeType32> mNoRepeatNgramSize: Controls how many repeat ngram size are acceptable. Default is 1 << 30.

std::optional<SizeType32> mNumReturnSequences: The number of return sequences or beams. In beam search, the value should be less than or equal to mBeamWidth. In sampling, it specifies the total number of independently generated sequences.

SizeType32 mNumReturnBeams: The number of beams to return. It is equal to beamWidth unless numReturnSequences is set. If beamWidth > 1 and numReturnSequences is set, then numReturnBeams is equal to numReturnSequences.

Private Static Functions

static SizeType32 checkBeamWidth(SizeType32 beamWidth)

static std::optional<FloatType> const &checkTopK(std::optional<FloatType> const &topK)

static std::optional<FloatType> const &checkTopP(std::optional<FloatType> const &topP)

static std::optional<FloatType> const &checkTopPMin(std::optional<FloatType> const &topPMin)

static std::optional<TokenIdType> const &checkTopPResetIds(std::optional<TokenIdType> const &topPResetIds)

static std::optional<FloatType> const &checkTopPDecay(std::optional<FloatType> const &topPDecay)

static std::optional<FloatType> const &checkTemperature(std::optional<FloatType> const &temperature)

static std::optional<FloatType> const &checkRepetitionPenalty(std::optional<FloatType> const &penalty)

static std::optional<SizeType32> const &checkMinTokens(std::optional<SizeType32> const &minTokens)

static std::optional<SizeType32> const &checkNoRepeatNgramSize(std::optional<SizeType32> const &noRepeatNgramSize)

static std::optional<FloatType> const &checkBeamSearchDiversityRate(std::optional<FloatType> const &beamSearchDiversityRate)

static std::optional<SizeType32> const &checkNumReturnSequences(std::optional<SizeType32> const &numReturnSequences, SizeType32 beamWidth)

Friends

friend class Serialization

class OutputConfig

#include <executor.h>

Configuration that controls the outputs of a Result.

Public Functions

explicit OutputConfig(bool returnLogProbs = false, bool returnContextLogits = false, bool returnGenerationLogits = false, bool excludeInputFromOutput = false, bool returnEncoderOutput = false, bool returnPerfMetrics = false)

Public Members

bool returnLogProbs: Controls if Result should contain log probabilities. Default is false.

bool returnContextLogits: Controls if Result should contain the context logits. Default is false.

bool returnGenerationLogits: Controls if Result should contain the generation logits. Default is false.

bool excludeInputFromOutput: Controls if output tokens in Result should include the input tokens. Default is false.

bool returnEncoderOutput: Controls if Result should contain encoder output hidden states (for encoder-only and encoder-decoder models). Default is false.

bool returnPerfMetrics: Controls if Result should contain performance metrics.

class ExternalDraftTokensConfig

#include <executor.h>

Configuration for speculative decoding with external draft tokens. Allows to include draft tokens, draft logits and specify acceptance threshold.

Public Functions

explicit ExternalDraftTokensConfig(VecTokens tokens, std::optional<Tensor> logits = std::nullopt, std::optional<FloatType> const &acceptanceThreshold = std::nullopt, std::optional<bool> const &fastLogits = std::nullopt)

VecTokens getTokens() const

std::optional<Tensor> getLogits() const

std::optional<FloatType> getAcceptanceThreshold() const

std::optional<bool> getFastLogits() const

Private Members

VecTokens mTokens: The draft tokens.

std::optional<Tensor> mLogits: The draft logits. Expected shape: [num_draft_tokens, vocab_size].

std::optional<FloatType> mAcceptanceThreshold: The acceptance threshold. Must be > 0.f and <= 1.f.

std::optional<bool> mFastLogits: Use direct transfer for draft logits.

Friends

friend class Serialization

class PromptTuningConfig

#include <executor.h>

Configuration for prompt tuning.

Public Functions

explicit PromptTuningConfig(Tensor embeddingTable, std::optional<VecTokenExtraIds> inputTokenExtraIds = std::nullopt)

Tensor getEmbeddingTable() const

std::optional<VecTokenExtraIds> getInputTokenExtraIds() const

Private Members

Tensor mEmbeddingTable: The prompt embedding table. Expected shape: [task vocab_size, hidden_size]. Data type must match model weights.

std::optional<VecTokenExtraIds> mInputTokenExtraIds: The input token extra ids for KV Cache reuse when p-tuning is enabled.

Friends

friend class Serialization

class MropeConfig

#include <executor.h>

Configuration for mrope.

Public Functions

explicit MropeConfig(Tensor mropeRoratySinCos, SizeType32 mropePositionDeltas)

Tensor getMRopeRotarySinCos() const

SizeType32 getMRopePositionDeltas() const

Private Members

Tensor mMRopeRotarySinCos: The mrope rotary sin and cos cache. Expected shape: [maxPositionEmbeddings*rotaryEmbeddingDim],Data type must float32.

SizeType32 mMRopePositionDeltas: The mrope position deltas.

Friends

friend class Serialization

class LoraConfig

#include <executor.h>

Configuration for LoRA.

Public Functions

explicit LoraConfig(IdType taskId, std::optional<Tensor> weights = std::nullopt, std::optional<Tensor> config = std::nullopt)

IdType getTaskId() const

std::optional<Tensor> getWeights() const

std::optional<Tensor> getConfig() const

Private Members

IdType mTaskId: The Lora task id.

std::optional<Tensor> mWeights: The Lora weights. See TRT-LLM documentation for expected shapes and types.

std::optional<Tensor> mConfig: The Lora configuration. See TRT-LLM documentation for detailed description of the config tensor.

Friends

friend class Serialization

struct LookaheadDecodingConfig

Public Functions

LookaheadDecodingConfig(SizeType32 windowSize, SizeType32 ngramSize, SizeType32 verificationSetSize)

inline explicit LookaheadDecodingConfig()

bool operator==(LookaheadDecodingConfig const &other) const

std::tuple<SizeType32 const, SizeType32 const, SizeType32 const> get() const

SizeType32 getWindowSize() const

SizeType32 getNgramSize() const

SizeType32 getVerificationSetSize() const

std::tuple<SizeType32, SizeType32, SizeType32, SizeType32> calculateSpeculativeResource() const: return <maxDecodingTokens, maxPathLen, maxDraftTokens, maxDraftPathLen>

bool isLE(LookaheadDecodingConfig const &that) const: return true when this can be executed on resources defined by that

Public Static Functions

static bool isLegal(SizeType32 windowSize, SizeType32 ngramSize, SizeType32 verificationSetSize) noexcept: return true when the parameter combination is valid.

Private Members

SizeType32 mWindowSize

SizeType32 mNgramSize

SizeType32 mVerificationSetSize

Friends

friend class Serialization

struct EagleConfig

Public Functions

explicit EagleConfig(std::optional<EagleChoices> eagleChoices = std::nullopt, bool greedySampling = true, std::optional<float> posteriorThreshold = std::nullopt)

bool operator==(EagleConfig const &other) const

std::optional<EagleChoices> getEagleChoices() const

std::optional<float> getPosteriorThreshold() const

bool isGreedySampling() const

Private Functions

std::optional<float> const &checkPosteriorValue(std::optional<float> const &value)

Private Members

std::optional<EagleChoices> mEagleChoices: choices forming tree for EAGLE-1.

bool mGreedySampling: Flag to use greedy or typical acceptance.

std::optional<float> mPosteriorThreshold: Minimum token probability of the typical acceptance. Corresponds to epsilon in https://arxiv.org/pdf/2401.10774. Default is 0.09f.

Friends

friend class Serialization

class ContextPhaseParams

Public Types

using RequestIdType = std::uint64_t

Public Functions

explicit ContextPhaseParams(VecTokens firstGenTokens, RequestIdType reqId)

ContextPhaseParams(VecTokens firstGenTokens, RequestIdType reqId, void *state)

ContextPhaseParams(ContextPhaseParams const&)

ContextPhaseParams(ContextPhaseParams&&) noexcept

ContextPhaseParams &operator=(ContextPhaseParams const&)

ContextPhaseParams &operator=(ContextPhaseParams&&) noexcept

~ContextPhaseParams()

bool operator==(ContextPhaseParams const&) const noexcept

VecTokens const &getFirstGenTokens() const & noexcept

VecTokens popFirstGenTokens() && noexcept

RequestIdType getReqId() const noexcept

void const *getState() const noexcept

void *getState() noexcept

void *releaseState() noexcept

Private Types

using StatePtr = std::unique_ptr<void, decltype(&deleter)>

Private Members

RequestIdType mReqId = {0}: This request corresponds to the request ID in the context phase.

VecTokens mFirstGenTokens: The first tokens generated by context executor.

StatePtr mState = {nullptr, deleter}: Context phase state of this request.

Private Static Functions

static void deleter(void const *data)

Friends

friend class Serialization

class SpeculativeDecodingConfig

#include <executor.h>

Configuration for speculative decoding (both draft and target models)

Public Functions

explicit SpeculativeDecodingConfig(bool fastLogits = false)

bool operator==(SpeculativeDecodingConfig const &other) const

Public Members

bool fastLogits: Send logits tensor directly from draft to target model.

class GuidedDecodingParams

#include <executor.h>

Guided decoding parameters for a request.

Public Types

enum class GuideType

Values:

enumerator kJSON: The generated text is amenable to json format.

enumerator kJSON_SCHEMA: The generated text is amenable to json format with additional user-specified restrictions, namely schema.

enumerator kREGEX: The generated text is amenable to the user-specified regular expression.

enumerator kEBNF_GRAMMAR: The generated text is amenable to the user-specified extended Backus-Naur form (EBNF) grammar. EBNF grammar is widely-used to express context-free grammars.

Public Functions

explicit GuidedDecodingParams(GuideType guideType, std::optional<std::string> guide = std::nullopt)

bool operator==(GuidedDecodingParams const &other) const

GuideType getGuideType() const

std::optional<std::string> getGuide() const

Private Members

GuideType mGuideType: The guide type. See GuideType.

std::optional<std::string> mGuide: The detailed guide string. It could be a json schema, a regular expression or a EBNF grammar depending on mGuideType.

Friends

friend class Serialization

struct RetentionPriorityAndDuration

Public Functions

inline RetentionPriorityAndDuration(std::optional<RetentionPriority> const &retentionPriority, std::optional<std::chrono::milliseconds> const &durationMs)

Public Members

std::optional<RetentionPriority> retentionPriority

std::optional<std::chrono::milliseconds> durationMs

class KvCacheRetentionConfig

#include <executor.h>

Configuration for the request’s retention in the KV Cache.

Public Functions

inline explicit KvCacheRetentionConfig()

explicit KvCacheRetentionConfig(std::vector<TokenRangeRetentionConfig> const &tokenRangeRetentionPriorities, RetentionPriority decodeRetentionPriority = kDefaultRetentionPriority, std::optional<std::chrono::milliseconds> decodeDurationMs = std::nullopt)

std::vector<TokenRangeRetentionConfig> getTokenRangeRetentionConfigs() const

RetentionPriority getDecodeRetentionPriority() const

std::optional<std::chrono::milliseconds> getDecodeDurationMs() const

std::vector<RetentionPriorityAndDuration> getPerBlockRetentionPriorityDuration(SizeType32 blockSize, SizeType32 seqLen) const: Convert the token range data into an entry per kv block. Returns a tuple of vectors corresponding to the priorities and durations for each block.

Public Static Attributes

static constexpr RetentionPriority kMinRetentionPriority = 0

static constexpr RetentionPriority kMaxRetentionPriority = 100

static constexpr RetentionPriority kDefaultRetentionPriority = 35

Private Members

std::vector<TokenRangeRetentionConfig> mTokenRangeRetentionConfigs: The token ranges and priority levels to update. Ranges must be non-overlapping. For example [(0, 64), (100, 128), (70, 80)] is valid, whereas [(0, 64), (60, 128)] is not.

RetentionPriority mDecodeRetentionPriority: The priority level to assign to blocks allocated in the decode phase.

std::optional<std::chrono::milliseconds> mDecodeDurationMs: The duration in ms that decode blocks should remain at their assigned priority level.

struct TokenRangeRetentionConfig

#include <executor.h>

A single entry to set block priorities over a token range. Earlier ranges always take priority over later ones. For example, with a block size of 16, a range of [0, 17] would be applied to the first two blocks.

Public Functions

inline explicit TokenRangeRetentionConfig(SizeType32 tokenStart, std::optional<SizeType32> tokenEnd = std::nullopt, RetentionPriority priority = KvCacheRetentionConfig::kDefaultRetentionPriority, std::optional<std::chrono::milliseconds> durationMs = std::nullopt)

inline bool operator==(TokenRangeRetentionConfig const &other) const

Public Members

SizeType32 tokenStart: The first token of this range.

std::optional<SizeType32> tokenEnd: The final token of this range. The end is not included in the range. This can be set to std::nullopt to extend the range to the end of the sequence.

RetentionPriority priority: The priority of this token range. Higher priorities are less likely to be evicted or offloaded.

std::optional<std::chrono::milliseconds> durationMs: The duration in ms that the block should remain at the given priority level. Set to std::nullopt to have no expiration time, and keep the block at the given priority level until it gets reclaimed. After the duration has passed, the block will be moved back to the kDefaultRetentionPriority level.

class Request

#include <executor.h>

A class that holds information about the request.

Public Functions

Request(VecTokens inputTokenIds, SizeType32 maxTokens, bool streaming = false, SamplingConfig const &samplingConfig = SamplingConfig(), OutputConfig const &outputConfig = OutputConfig(), std::optional<SizeType32> const &endId = std::nullopt, std::optional<SizeType32> const &padId = std::nullopt, std::optional<std::vector<SizeType32>> positionIds = std::nullopt, std::optional<std::list<VecTokens>> badWords = std::nullopt, std::optional<std::list<VecTokens>> stopWords = std::nullopt, std::optional<Tensor> embeddingBias = std::nullopt, std::optional<ExternalDraftTokensConfig> externalDraftTokensConfig = std::nullopt, std::optional<PromptTuningConfig> pTuningConfig = std::nullopt, std::optional<MropeConfig> mRopeConfig = std::nullopt, std::optional<LoraConfig> loraConfig = std::nullopt, std::optional<LookaheadDecodingConfig> lookaheadConfig = std::nullopt, std::optional<KvCacheRetentionConfig> kvCacheRetentionConfig = std::nullopt, std::optional<std::string> logitsPostProcessorName = std::nullopt, std::optional<VecTokens> encoderInputTokenIds = std::nullopt, std::optional<IdType> clientId = std::nullopt, bool returnAllGeneratedTokens = false, PriorityType priority = kDefaultPriority, RequestType type = RequestType::REQUEST_TYPE_CONTEXT_AND_GENERATION, std::optional<ContextPhaseParams> contextPhaseParams = std::nullopt, std::optional<Tensor> encoderInputFeatures = std::nullopt, std::optional<SizeType32> encoderOutputLength = std::nullopt, std::optional<Tensor> crossAttentionMask = std::nullopt, SizeType32 numReturnSequences = 1, std::optional<EagleConfig> eagleConfig = std::nullopt, std::optional<Tensor> skipCrossAttnBlocks = std::nullopt, std::optional<GuidedDecodingParams> guidedDecodingParams = std::nullopt, std::optional<MillisecondsType> allottedTimeMs = std::nullopt)

The Request constructor.

Parameters:

inputTokenIds – The input token ids
maxTokens – The maximum number of tokens to generate
streaming – Indicates if the responses should be streamed or not. Default is false.
samplingConfig – The sampling config