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Jun 18, 2025
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refactor: Update decoder buffer and logits management #4450

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18aa725
refactor: Update decoder buffer and logits management
Funatiq Apr 13, 2025
f9ea995
refactor: Move decoder_state from algs to store
Funatiq Jun 3, 2025
d663001
fix: check buffers before access
Funatiq Jun 12, 2025
c90f89b
refactor: use pure python type for decoder buffer logits
Funatiq Jun 16, 2025
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59 changes: 35 additions & 24 deletions cpp/include/tensorrt_llm/batch_manager/decoderBuffers.h
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Expand Up @@ -36,18 +36,28 @@ class DecoderInputBuffers
using SizeType32 = runtime::SizeType32;
using TensorPtr = runtime::ITensor::SharedPtr;

explicit DecoderInputBuffers(
SizeType32 maxBatchSize, SizeType32 maxDecoderSteps, runtime::BufferManager const& manager);
explicit DecoderInputBuffers(SizeType32 maxNumSequences, SizeType32 maxBatchSize, SizeType32 maxDecoderSteps,
runtime::BufferManager const& manager);

// buffers for setup
//! Buffers for decoder setup

//! Input IDs of new requests, [maxBatchSize]
TensorPtr inputsIds;
//! Batch slots for setup step, [maxBatchSize]
TensorPtr setupBatchSlots;
TensorPtr setupBatchSlotsDevice;
//! Helper buffer for copying sequence lengths, [maxBatchSize]
TensorPtr fillValues;
TensorPtr fillValuesDevice;

// buffers for forward
//! Buffers for decoder forward

//! Batch slots for all decoder steps, [maxDecoderSteps][maxBatchSize]
std::vector<TensorPtr> forwardBatchSlots;

//! Logits for all batch slots, [maxNumSequences]
//! The vector is sparse, only slots in forwardBatchSlots are used.
std::vector<TensorPtr> logits;
};

class DecoderOutputBuffers
Expand All @@ -70,35 +80,36 @@ class DecoderOutputBuffers
TensorPtr finishReasonsHost; // [mMaxNumRequests, beamWidth], pinned host tensor
};

class DecoderBuffers
class DraftBuffers
{
public:
using SizeType32 = runtime::SizeType32;
using TensorPtr = runtime::ITensor::SharedPtr;

std::vector<TensorPtr> logits;
TensorPtr nextDraftTokensDevice; // [mMaxNumRequests, maxTokensPerStep-1]
TensorPtr nextDraftTokensHost; // [mMaxNumRequests, maxTokensPerStep-1]
TensorPtr prevDraftTokensLengthsDevice; // [mMaxNumRequests]
TensorPtr prevDraftTokensLengthsHost; // [mMaxNumRequests]
TensorPtr nextDraftTokensLengthsDevice; // [mMaxNumRequests]
TensorPtr nextDraftTokensLengthsHost; // [mMaxNumRequests]
TensorPtr acceptedLengthsCumSumDevice; // [mMaxNumRequests+1]
TensorPtr acceptedPackedPathsDevice; // [mMaxNumRequests * maxAcceptedTokens]
std::vector<std::vector<runtime::ITensor::SharedPtr>>
predictedDraftLogits; // [mMaxNumRequests][mMaxNumHeads][maxDraftTokens + 1, vocabSize]

void create(SizeType32 maxNumSequences, SizeType32 maxTokensPerStep, runtime::BufferManager const& manager,
runtime::ModelConfig const& modelConfig);
};

class DecoderBuffers
{
public:
using SizeType32 = runtime::SizeType32;
using TensorPtr = runtime::ITensor::SharedPtr;

TensorPtr cacheIndirectionInput;
TensorPtr cacheIndirectionOutput;

class DraftBuffers
{
public:
TensorPtr nextDraftTokensDevice; // [mMaxNumRequests, maxTokensPerStep-1]
TensorPtr nextDraftTokensHost; // [mMaxNumRequests, maxTokensPerStep-1]
TensorPtr prevDraftTokensLengthsDevice; // [mMaxNumRequests]
TensorPtr prevDraftTokensLengthsHost; // [mMaxNumRequests]
TensorPtr nextDraftTokensLengthsDevice; // [mMaxNumRequests]
TensorPtr nextDraftTokensLengthsHost; // [mMaxNumRequests]
TensorPtr acceptedLengthsCumSumDevice; // [mMaxNumRequests+1]
TensorPtr acceptedPackedPathsDevice; // [mMaxNumRequests * maxAcceptedTokens]
std::vector<std::vector<runtime::ITensor::SharedPtr>>
predictedDraftLogits; // [mMaxNumRequests][mMaxNumHeads][maxDraftTokens + 1, vocabSize]

void create(SizeType32 maxNumSequences, SizeType32 maxTokensPerStep, runtime::BufferManager const& manager,
runtime::ModelConfig const& modelConfig);
};

DraftBuffers draftBuffers;

DecoderBuffers(SizeType32 maxNumSequences, SizeType32 maxBeamWidth, SizeType32 maxAttentionWindow,
Expand Down
12 changes: 6 additions & 6 deletions cpp/include/tensorrt_llm/batch_manager/handleContextLogits.h
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Expand Up @@ -31,8 +31,8 @@ class CudaStream;
namespace tensorrt_llm::batch_manager
{

class RuntimeBuffers;
class DecoderBuffers;
class DecoderInputBuffers;
class DraftBuffers;
class MedusaBuffers;

namespace tr = tensorrt_llm::runtime;
Expand All @@ -47,10 +47,10 @@ class HandleContextLogits : Algorithm

HandleContextLogits() = default;

tr::SizeType32 operator()(RequestVector const& contextRequests,
std::vector<tr::SizeType32> const& numContextLogitsVec, tr::ITensor::SharedPtr const& logits,
DecoderBuffers& decoderBuffers, tr::ModelConfig const& modelConfig, tr::BufferManager const& manager,
tensorrt_llm::runtime::CudaStream const& stream, OptionalRef<MedusaBuffers> medusaBuffers) const;
tr::SizeType32 operator()(DecoderInputBuffers& inputBuffers, RequestVector const& contextRequests,
tr::ITensor::SharedPtr const& logits, std::vector<tr::SizeType32> const& numContextLogitsVec,
tr::ModelConfig const& modelConfig, tr::BufferManager const& manager, OptionalRef<DraftBuffers> draftBuffers,
OptionalRef<MedusaBuffers> medusaBuffers) const;
};

} // namespace tensorrt_llm::batch_manager
10 changes: 6 additions & 4 deletions cpp/include/tensorrt_llm/batch_manager/handleGenerationLogits.h
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Expand Up @@ -30,8 +30,9 @@ class BufferManager;
namespace tensorrt_llm::batch_manager
{

class DecoderInputBuffers;
class DraftBuffers;
class RuntimeBuffers;
class DecoderBuffers;

namespace tr = tensorrt_llm::runtime;

Expand All @@ -45,9 +46,10 @@ class HandleGenerationLogits : Algorithm

HandleGenerationLogits() = default;

void operator()(tr::SizeType32 logitsIndex, RequestVector const& generationRequests, DecoderBuffers& decoderBuffers,
tr::ModelConfig const& modelConfig, tr::BufferManager const& manager, tr::ITensor::SharedPtr const& logits,
OptionalRef<RuntimeBuffers> genRuntimeBuffers) const;
void operator()(DecoderInputBuffers& inputBuffers, RequestVector const& generationRequests,
tr::ITensor::SharedPtr const& logits, tr::SizeType32 logitsIndex, tr::ModelConfig const& modelConfig,
tr::BufferManager const& manager, OptionalRef<RuntimeBuffers> genRuntimeBuffers,
OptionalRef<DraftBuffers> draftBuffers) const;
};

} // namespace tensorrt_llm::batch_manager
8 changes: 2 additions & 6 deletions cpp/include/tensorrt_llm/batch_manager/logitsPostProcessor.h
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Expand Up @@ -30,10 +30,6 @@ class TllmRuntime;
namespace tensorrt_llm::batch_manager
{

class DecoderBuffers;

namespace tr = tensorrt_llm::runtime;

class LogitsPostProcessor : Algorithm
{
public:
Expand All @@ -48,8 +44,8 @@ class LogitsPostProcessor : Algorithm
LogitsPostProcessor() = default;

bool operator()(RequestVector const& contextRequests, RequestVector const& generationRequests,
bool replicateLogitsPostProcessor, DecoderBuffers& decoderBuffers, tr::WorldConfig const& worldConfig,
tr::TllmRuntime& runtime,
bool replicateLogitsPostProcessor, std::vector<batch_manager::LlmRequest::TensorPtr>& seqSlotLogits,
runtime::WorldConfig const& worldConfig, runtime::TllmRuntime& runtime,
std::optional<LogitsPostProcessorBatched> logitsPostProcessorBatched = std::nullopt) const;
};

Expand Down
13 changes: 5 additions & 8 deletions cpp/tensorrt_llm/batch_manager/decoderBuffers.cpp
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Expand Up @@ -30,7 +30,7 @@ namespace tensorrt_llm::batch_manager
{

DecoderInputBuffers::DecoderInputBuffers(
SizeType32 maxBatchSize, SizeType32 maxDecoderSteps, BufferManager const& manager)
SizeType32 maxNumSequences, SizeType32 maxBatchSize, SizeType32 maxDecoderSteps, BufferManager const& manager)
{
auto const maxBatchSizeShape = ITensor::makeShape({maxBatchSize});
auto const nvSizeType = TRTDataType<SizeType32>::value;
Expand All @@ -48,6 +48,8 @@ DecoderInputBuffers::DecoderInputBuffers(
{
forwardBatchSlots.emplace_back(BufferManager::pinnedPool(ITensor::makeShape({maxBatchSize}), nvSizeType));
}

logits.resize(maxNumSequences);
}

DecoderOutputBuffers::DecoderOutputBuffers(SizeType32 maxNumSequences, SizeType32 maxBeamWidth, SizeType32 maxSeqLen,
Expand Down Expand Up @@ -91,11 +93,6 @@ DecoderBuffers::DecoderBuffers(SizeType32 maxNumSequences, SizeType32 maxBeamWid
SizeType32 maxTokensPerStep, BufferManager const& manager, ModelConfig const& modelConfig,
WorldConfig const& worldConfig)
{
if (worldConfig.isLastPipelineParallelRank())
{
logits.resize(maxNumSequences);
}

cacheIndirectionInput = manager.gpu(
ITensor::makeShape({maxNumSequences, maxBeamWidth, maxAttentionWindow}), nvinfer1::DataType::kINT32);
cacheIndirectionOutput = manager.gpu(
Expand All @@ -109,8 +106,8 @@ DecoderBuffers::DecoderBuffers(SizeType32 maxNumSequences, SizeType32 maxBeamWid
}
}

void DecoderBuffers::DraftBuffers::create(SizeType32 maxNumSequences, SizeType32 maxTokensPerStep,
BufferManager const& manager, ModelConfig const& modelConfig)
void DraftBuffers::create(SizeType32 maxNumSequences, SizeType32 maxTokensPerStep, BufferManager const& manager,
ModelConfig const& modelConfig)
{
auto const speculativeDecodingMode = modelConfig.getSpeculativeDecodingMode();

Expand Down
13 changes: 7 additions & 6 deletions cpp/tensorrt_llm/batch_manager/handleContextLogits.cpp
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Expand Up @@ -67,9 +67,9 @@ void setupMedusaLogits(std::vector<TensorPtr>& medusaLogitsHeads, TensorPtr cons

} // namespace

SizeType32 HandleContextLogits::operator()(RequestVector const& contextRequests,
std::vector<SizeType32> const& numContextLogitsVec, TensorPtr const& logits, DecoderBuffers& decoderBuffers,
tr::ModelConfig const& modelConfig, BufferManager const& manager, tensorrt_llm::runtime::CudaStream const& stream,
SizeType32 HandleContextLogits::operator()(DecoderInputBuffers& inputBuffers, RequestVector const& contextRequests,
tr::ITensor::SharedPtr const& logits, std::vector<tr::SizeType32> const& numContextLogitsVec,
tr::ModelConfig const& modelConfig, tr::BufferManager const& manager, OptionalRef<DraftBuffers> draftBuffers,
OptionalRef<MedusaBuffers> medusaBuffers) const
{
TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);
Expand Down Expand Up @@ -114,13 +114,14 @@ SizeType32 HandleContextLogits::operator()(RequestVector const& contextRequests,
// Get the logits from the last context token and draft tokens
auto const numDecoderLogits = 1 + draftLength;
auto const seqSlot = llmReq->mSeqSlot.value();
auto& decoderLogits = decoderBuffers.logits.at(seqSlot);
auto& decoderLogits = inputBuffers.logits.at(seqSlot);
TensorPtr logitsView = ITensor::slice(logits, logitsIndex - numDecoderLogits, numDecoderLogits);

if (modelConfig.getSpeculativeDecodingMode().hasDraftLogits())
{
TLLM_CHECK(draftBuffers);
auto& medusaLogitsHeads = draftBuffers->predictedDraftLogits.at(seqSlot);
TLLM_CHECK(medusaBuffers);
auto& medusaLogitsHeads = decoderBuffers.draftBuffers.predictedDraftLogits.at(seqSlot);
setupMedusaLogits(medusaLogitsHeads, medusaBuffers->medusaLogitsDevice,
modelConfig.getSpeculativeDecodingModule().getMaxDraftPathLen(), logitsIndex - numDecoderLogits,
numDecoderLogits);
Expand All @@ -143,7 +144,7 @@ SizeType32 HandleContextLogits::operator()(RequestVector const& contextRequests,
auto const logitsShape = logitsView->getShape();
auto const logitsType = logitsView->getDataType();
decoderLogits = manager.gpu(ITensor::makeShape({reqBeamWidth, logitsShape.d[1]}), logitsType);
tensorrt_llm::runtime::kernels::tileTensor(*decoderLogits, *logitsView, reqBeamWidth, stream);
tensorrt_llm::runtime::kernels::tileTensor(*decoderLogits, *logitsView, reqBeamWidth, manager.getStream());
decoderLogits->unsqueeze(0);
}
else
Expand Down
13 changes: 8 additions & 5 deletions cpp/tensorrt_llm/batch_manager/handleGenerationLogits.cpp
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Expand Up @@ -73,9 +73,10 @@ void setupMedusaLogits(std::vector<TensorPtr>& medusaLogitsHeads, TensorPtr cons

} // namespace

void HandleGenerationLogits::operator()(SizeType32 logitsIndex, RequestVector const& generationRequests,
DecoderBuffers& decoderBuffers, tr::ModelConfig const& modelConfig, BufferManager const& manager,
TensorPtr const& logits, OptionalRef<RuntimeBuffers> genRuntimeBuffers) const
void HandleGenerationLogits::operator()(DecoderInputBuffers& inputBuffers, RequestVector const& generationRequests,
tr::ITensor::SharedPtr const& logits, tr::SizeType32 logitsIndex, tr::ModelConfig const& modelConfig,
tr::BufferManager const& manager, OptionalRef<RuntimeBuffers> genRuntimeBuffers,
OptionalRef<DraftBuffers> draftBuffers) const
{
TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);
NVTX3_SCOPED_RANGE(HandleGenerationLogits);
Expand All @@ -99,7 +100,7 @@ void HandleGenerationLogits::operator()(SizeType32 logitsIndex, RequestVector co
TensorPtr logitsView = ITensor::slice(logits, logitsIndex, numLogits);
TLLM_CHECK_DEBUG_WITH_INFO(tru::tensorHasInvalid<float>(*logitsView, manager, "logits") == false,
"Found invalid number (NaN or Inf) in logits");
auto& decoderLogits = decoderBuffers.logits.at(seqSlot);
auto& decoderLogits = inputBuffers.logits.at(seqSlot);
auto const logitsViewShape = logitsView->getShape();
if (reqBeamWidth > 1)
{
Expand Down Expand Up @@ -136,8 +137,10 @@ void HandleGenerationLogits::operator()(SizeType32 logitsIndex, RequestVector co
}
if (modelConfig.getSpeculativeDecodingMode().hasDraftLogits())
{
TLLM_CHECK(draftBuffers);
auto& medusaLogitsHeads = draftBuffers->predictedDraftLogits.at(seqSlot);
TLLM_CHECK(genRuntimeBuffers);
auto& medusaLogitsHeads = decoderBuffers.draftBuffers.predictedDraftLogits.at(seqSlot);
TLLM_CHECK(genRuntimeBuffers->mMedusaBuffers);
setupMedusaLogits(medusaLogitsHeads, genRuntimeBuffers->mMedusaBuffers->medusaLogitsDevice,
modelConfig.getSpeculativeDecodingModule().getMaxDraftPathLen(), logitsIndex, draftLength);
}
Expand Down
8 changes: 5 additions & 3 deletions cpp/tensorrt_llm/batch_manager/logitsPostProcessor.cpp
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Expand Up @@ -25,6 +25,8 @@
#include "tensorrt_llm/runtime/tllmRuntime.h"
#include "tensorrt_llm/runtime/utils/debugUtils.h"

namespace tr = tensorrt_llm::runtime;

namespace tensorrt_llm::batch_manager
{

Expand All @@ -34,7 +36,7 @@ using ITensor = runtime::ITensor;
using SizeType32 = tensorrt_llm::runtime::SizeType32;

bool LogitsPostProcessor::operator()(RequestVector const& contextRequests, RequestVector const& generationRequests,
bool replicateLogitsPostProcessor, DecoderBuffers& decoderBuffers, tr::WorldConfig const& worldConfig,
bool replicateLogitsPostProcessor, std::vector<TensorPtr>& seqSlotLogits, tr::WorldConfig const& worldConfig,
tr::TllmRuntime& runtime, std::optional<LogitsPostProcessorBatched> logitsPostProcessorBatched) const
{
TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);
Expand All @@ -59,7 +61,7 @@ bool LogitsPostProcessor::operator()(RequestVector const& contextRequests, Reque
logitsPostProcessorIsApplied = true;
if (replicateLogitsPostProcessor || worldConfig.isFirstTensorParallelRank())
{
auto& logits = decoderBuffers.logits.at(llmReq->mSeqSlot.value());
auto& logits = seqSlotLogits.at(llmReq->mSeqSlot.value());
(*llmReq->mLogitsPostProcessor)(
llmReq->mRequestId, logits, llmReq->getTokens(), runtime.getStreamPtr(), llmReq->mClientId);
}
Expand All @@ -68,7 +70,7 @@ bool LogitsPostProcessor::operator()(RequestVector const& contextRequests, Reque
{
reqIdsVec.push_back(llmReq->mRequestId);

auto& logits = decoderBuffers.logits.at(llmReq->mSeqSlot.value());
auto& logits = seqSlotLogits.at(llmReq->mSeqSlot.value());
logitsVec.push_back(logits);

beamTokensVec.emplace_back(llmReq->getTokens());
Expand Down
2 changes: 1 addition & 1 deletion cpp/tensorrt_llm/batch_manager/makeDecodingBatchInputOutput.cpp
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Expand Up @@ -132,7 +132,7 @@ MakeDecodingBatchInputOutput::operator()(RequestVector const& contextRequests, R

auto [activeSlots, generationSteps] = getActiveSlots(contextRequests, generationRequests);

auto decodingInput = createDecoderBatchInputs(activeSlots, decoderState, decoderBuffers.logits, maxNumSequences,
auto decodingInput = createDecoderBatchInputs(activeSlots, decoderState, inputBuffers.logits, maxNumSequences,
inputBuffers.forwardBatchSlots, decoderBuffers.cacheIndirectionInput);
decodingInput->generationSteps = generationSteps;

Expand Down
19 changes: 11 additions & 8 deletions cpp/tensorrt_llm/batch_manager/trtGptModelInflightBatching.cpp
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Expand Up @@ -1462,7 +1462,7 @@ void TrtGptModelInflightBatching::createBuffers(executor::DecodingConfig const&
for (SizeType32 i = 0; i < mNumMicroBatches; ++i)
{
mDecoderInputBuffers.emplace_back(
getMaxBatchSize(), mModelConfig.getMaxDecodingTokens(), mRuntime->getBufferManager());
getMaxNumSequences(), getMaxBatchSize(), mModelConfig.getMaxDecodingTokens(), mRuntime->getBufferManager());
mDecoderOutputBuffers.emplace_back(getMaxNumSequences(), mOperatingBeamWidth, getMaxSequenceLen(),
mModelConfig.getMaxDecodingTokens(), mRuntime->getBufferManager());
}
Expand Down Expand Up @@ -1995,29 +1995,32 @@ runtime::CudaEvent TrtGptModelInflightBatching::decoderStepAsync(ScheduledReques
TLLM_LOG_TRACE("%s start", __PRETTY_FUNCTION__);
NVTX3_SCOPED_RANGE(decoderStepAsync);

auto& decoderInputBuffers = mDecoderInputBuffers.at(getFusedBufferId());
auto& seqSlotLogits = decoderInputBuffers.logits;

auto const contextBufferId = mCtxGenFusion ? getFusedBufferId() : getContextBufferId();
auto& contextRuntimeBuffers = mBuffers.at(contextBufferId);
auto const logitsIndex = (*mHandleContextLogits)(scheduledRequests.contextRequests,
contextRuntimeBuffers->numContextLogits, contextRuntimeBuffers->logits, *mDecoderBuffers, mModelConfig,
mRuntime->getBufferManager(), mRuntime->getStream(), contextRuntimeBuffers->mMedusaBuffers);
auto const logitsIndex = (*mHandleContextLogits)(decoderInputBuffers, scheduledRequests.contextRequests,
contextRuntimeBuffers->logits, contextRuntimeBuffers->numContextLogits, mModelConfig,
mRuntime->getBufferManager(), mDecoderBuffers->draftBuffers, contextRuntimeBuffers->mMedusaBuffers);

auto const genLogitsIndex = mCtxGenFusion ? logitsIndex : 0;
auto const genBufferId = mCtxGenFusion ? getFusedBufferId() : getGenerationBufferId();
auto& genRuntimeBuffers = mBuffers.at(genBufferId);
(*mHandleGenerationLogits)(genLogitsIndex, scheduledRequests.generationRequests, *mDecoderBuffers, mModelConfig,
mRuntime->getBufferManager(), genRuntimeBuffers->logits, *genRuntimeBuffers);
(*mHandleGenerationLogits)(decoderInputBuffers, scheduledRequests.generationRequests, genRuntimeBuffers->logits,
genLogitsIndex, mModelConfig, mRuntime->getBufferManager(), *genRuntimeBuffers, mDecoderBuffers->draftBuffers);

// Copy indirection output into input
// TODO: Could we avoid this by modifying batchDecoder to take a vector of tensors instead?
copyCacheIndirectionFromOutputsToInputs(scheduledRequests, genBufferId);

mLogitsPostProcessorIsApplied
= (*mLogitsPostProcessor)(scheduledRequests.contextRequests, scheduledRequests.generationRequests,
mReplicateLogitsPostProcessor, *mDecoderBuffers, mWorldConfig, *mRuntime, mLogitsPostProcessorBatched);
mReplicateLogitsPostProcessor, seqSlotLogits, mWorldConfig, *mRuntime, mLogitsPostProcessorBatched);

if (mGuidedDecoder)
{
mGuidedDecoder->execute(scheduledRequests, mRuntime->getBufferManager(), mDecoderBuffers->logits);
mGuidedDecoder->execute(scheduledRequests, mRuntime->getBufferManager(), seqSlotLogits);
}

auto const fusedBufferId = getFusedBufferId();
Expand Down
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