TensorRT-LLMs/cpp/tensorrt_llm/kernels/samplingTopKKernels.h
Kaiyu Xie bf0a5afc92
Update TensorRT-LLM (#1598)
* Update TensorRT-LLM
2024-05-14 16:43:41 +08:00

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/*
* Copyright (c) 2020-2024, NVIDIA CORPORATION. All rights reserved.
* Copyright (c) 2021, NAVER Corp. Authored by CLOVA.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#pragma once
#include "tensorrt_llm/common/cudaUtils.h"
#include "tensorrt_llm/common/memoryUtils.h"
#include "tensorrt_llm/kernels/decodingCommon.h"
#include "tensorrt_llm/runtime/common.h"
#include <curand_kernel.h>
#include <numeric>
namespace tensorrt_llm
{
namespace kernels
{
static constexpr runtime::SizeType32 TOP_K_MAX = 1024;
template <typename T>
struct TopKSamplingKernelParams
{
//! Input buffer [batchSize, maxTokensPerStep, vocabSizePadded].
//! Log probabilities of each token in the vocab. If logitsHasProbs is true,
//! logProbs must contain **just** probabilities instead of log probabilities.
T const* logProbs{nullptr};
//! input buffer [batchSize][vocabSizePadded] array of pointers to logits.
//! If nullptr, logProbs is used. Only maxTokensPerStep == 1 is supported.
T const* const* logProbsPtrs{nullptr};
//! output buffer [maxBatchSize][maxSeqLen], optional. Contains pointers to rows
//! with output tokens per request. If nullptr, outputIds must be provided.
runtime::TokenIdType** outputIdsPtrs{nullptr};
//! output buffer [maxBatchSize, maxSeqLen], optional. Tensor to store output tokens.
//! Not used if outputIdsPtrs != nullptr
runtime::TokenIdType* outputIds{nullptr};
//! Required. Pointer to the workspace of size returned by getTopKWorkspaceSize.
//! Has to be pre-allocated by caller.
//! Function does not take ownership of the buffer
void* workspace{nullptr};
//! input buffer [maxBatchSize], optional. EOS token ids per request
runtime::TokenIdType const* endIds{nullptr};
//! input/output buffer [maxBatchSize], optional. If nullptr, seqLen is 0
//! Current sequence length of the request. Set up to, but excluding endId token.
runtime::SizeType32* sequenceLengths{nullptr};
//! input buffer[batchSize], optional. Indices of rows of data in memory pool.
//! Linear indexing (batchIdx) is used if nullptr.
runtime::SizeType32 const* batchSlots{nullptr};
//! input buffer [maxBatchSize], optional. Number of tokens per step for each request.
//! It is assumed that all requests have maxTokensPerStep tokens per step if nullptr.
runtime::SizeType32 const* tokensPerStep{nullptr};
//! input buffer [maxBatchSize], optional. If true, request exits early.
FinishedState const* finishedInput{nullptr};
//! output buffer [maxBatchSize], optional.
//! Set to true if sequence has finished (if finished || outputId == endId).
FinishedState* finishedOutput{nullptr};
//! input buffer [maxBatchSize]. Flags whether to skip decoding per request
bool const* skipDecode{nullptr};
//! input/output buffer [maxBatchSize], optional.
//! Cumulative log probability of selected tokens. Ignored if nullptr
float* cumLogProbs{nullptr};
//! output buffer [maxBatchSize]. Log probs is the probability induced by the top-k sampling.
//! If normalizeLogProbs is true, we normalize the probability 'expLogit' of the selected token
//! by the probability 's_sum' of a set of top-k tokens, meaning the logProb is the probability
//! of the selected token, conditioned on the event that it is selected,
//! i.e., log_prob = log P(i | i is in top-k) = log(expLogit / s_sum).
//! Ignored if nullptr.
float* outputLogProbs{nullptr};
//! input buffer [maxBatchSize]. Initialized curand states
curandState_t* curandState{nullptr};
//! input buffer [maxBatchSize]. K for topK sampling per request.
//! Supported K is in range [1; 1024]. Where K=1 is greedy search.
//! If nullptr maxTopK is used for all requests.
runtime::SizeType32 const* topKs{nullptr};
//! input buffer [maxBatchSize]. Probability for topP sampling per request.
//! Supported P is in range (0.0, 1.0]. If nullptr, topP is used for all requests
float const* topPs{nullptr};
//! maximum among all topKs K for topK sampling
runtime::SizeType32 maxTopK{TOP_K_MAX};
//! probability for topP sampling.
float maxTopP{1.0f};
runtime::SizeType32 batchSize{-1};
runtime::SizeType32 maxBatchSize{-1};
runtime::SizeType32 vocabSizePadded{-1};
runtime::SizeType32 maxTokensPerStep{-1};
runtime::SizeType32 maxSeqLen{-1};
//! when set to True outputLogProbs are normalized to TopK
bool normalizeLogProbs{false};
//! flag to highlight that logProbs contains probabilities
bool logitsHasProbs{false};
//! flag to return all selectedTopK results
bool returnAllTopK{false};
void checkParams() const
{
TLLM_CHECK(batchSize > 0);
TLLM_CHECK(maxBatchSize > 0);
TLLM_CHECK(maxBatchSize >= batchSize);
TLLM_CHECK(vocabSizePadded > 0);
TLLM_CHECK(maxTokensPerStep > 0);
TLLM_CHECK(logProbs || logProbsPtrs);
TLLM_CHECK(outputIds || outputIdsPtrs);
if (maxTokensPerStep > 1)
{
TLLM_CHECK(tokensPerStep);
}
if (outputIds)
{
TLLM_CHECK(maxSeqLen > 0);
}
TLLM_CHECK(workspace);
TLLM_CHECK(curandState);
TLLM_CHECK(maxTokensPerStep != 1 || returnAllTopK || sequenceLengths);
TLLM_CHECK(maxTokensPerStep != 1 || returnAllTopK || endIds);
if (cumLogProbs != nullptr || outputLogProbs != nullptr)
{
TLLM_CHECK(maxTokensPerStep == 1 && !returnAllTopK);
}
TLLM_CHECK(((finishedOutput == nullptr) ^ (endIds == nullptr)) == 0);
TLLM_CHECK(0 < maxTopP && maxTopP <= 1.f);
TLLM_CHECK(0 <= maxTopK && maxTopK <= TOP_K_MAX);
}
};
// clang-format off
//! \brief Given logProbs, performs top K **and** top P sampling at the same time. Fills sampled tokens to outputIds.
//! Computes sequenceLength, finished state, cumLogProbs inplace.
//! Sampling per request can be controlled using skipDecode, topPs and topKs parameters.
//! Function sets workspaceSize and exits early if workspace is nullptr.
//! If logits are Nan, we set output token to be the last in the vocabulary.
// clang-format on
template <typename T>
void invokeBatchTopKSampling(TopKSamplingKernelParams<T> const& params, cudaStream_t stream);
template <typename T>
[[nodiscard]] std::vector<size_t> getTopKWorkspaceSizes(runtime::SizeType32 batchSize,
runtime::SizeType32 maxTokensPerStep, runtime::SizeType32 maxTopK, runtime::SizeType32 vocabSizePadded)
{
runtime::SizeType32 constexpr maxBlockPerBeam = 8;
auto const tempLogProbsBufSize = sizeof(T) * batchSize * maxTokensPerStep * vocabSizePadded; // type T
auto const topKTmpIdsBufSize
= sizeof(runtime::SizeType32) * batchSize * maxTokensPerStep * maxTopK * maxBlockPerBeam; // type int
auto const topKTmpValBufSize = sizeof(T) * batchSize * maxTokensPerStep * maxTopK * maxBlockPerBeam; // type T
return {tempLogProbsBufSize, topKTmpIdsBufSize, topKTmpValBufSize};
}
//! \brief Returns workspace size in bytes needed for sampling TopK computation
//! \param batchSize batch size
//! \param maxTokensPerStep maximum number of tokens per computed per step
//! \param maxTopK maximum among all topKs K for topK sampling
//! \param vocabSizePadded size of padded vocab
template <typename T>
[[nodiscard]] size_t getTopKWorkspaceSize(runtime::SizeType32 batchSize, runtime::SizeType32 maxTokensPerStep,
runtime::SizeType32 maxTopK, runtime::SizeType32 vocabSizePadded)
{
auto const workspaceSizes = getTopKWorkspaceSizes<T>(batchSize, maxTokensPerStep, maxTopK, vocabSizePadded);
return tensorrt_llm::common::calcAlignedSize(workspaceSizes, 256);
}
} // namespace kernels
} // namespace tensorrt_llm