TensorRT-LLMs/cpp/tensorrt_llm/layers/topPSamplingLayer.h
Kaiyu Xie c89653021e
Update TensorRT-LLM (20240116) (#891)
* Update TensorRT-LLM

---------

Co-authored-by: Eddie-Wang1120 <81598289+Eddie-Wang1120@users.noreply.github.com>
Co-authored-by: Shixiaowei02 <39303645+Shixiaowei02@users.noreply.github.com>
2024-01-16 20:03:11 +08:00

88 lines
2.8 KiB
C++

/*
* Copyright (c) 2019-2023, 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/tensor.h"
#include "tensorrt_llm/kernels/decodingCommon.h"
#include "tensorrt_llm/layers/baseSamplingLayer.h"
namespace tc = tensorrt_llm::common;
namespace tensorrt_llm
{
namespace layers
{
template <typename T>
class TopPSamplingLayer : public BaseSamplingLayer<T>
{
public:
using Base = BaseSamplingLayer<T>;
using SetupParams = typename Base::SetupParams;
TopPSamplingLayer(std::size_t vocab_size, std::size_t vocab_size_padded, cudaStream_t stream,
std::shared_ptr<tensorrt_llm::common::IAllocator> allocator, bool is_free_buffer_after_forward,
cudaDeviceProp* cuda_device_prop, bool is_deterministic = true);
TopPSamplingLayer(TopPSamplingLayer<T> const& top_p_sampling_layer);
~TopPSamplingLayer();
void setup(std::size_t batch_size, SetupParams const& setupParams) override;
protected:
void runSampling(DecodingOutputParams& outputs, DecodingParams const& params) override;
void freeBuffer() override;
std::uint32_t* runtime_top_k_buf_ = nullptr;
float* runtime_top_p_buf_ = nullptr;
float runtime_max_top_p_;
float* initial_top_p_buf_ = nullptr;
float* top_p_decay_buf_ = nullptr;
float* top_p_min_buf_ = nullptr;
std::int32_t* top_p_reset_ids_buf_ = nullptr;
std::int32_t* topp_id_vals_buf_ = nullptr;
std::int32_t* topp_offset_buf_ = nullptr;
std::int32_t* begin_topp_offset_buf_ = nullptr;
std::size_t cub_temp_storage_size_;
bool is_deterministic_ = true;
int air_topp_block_num_;
using Base::vocab_size_;
using Base::vocab_size_padded_;
using Base::sampling_workspace_size_;
using Base::sampling_workspace_;
using Base::curandstate_buf_;
using Base::random_seeds_buf_;
using Base::skip_decode_buf_;
using Base::skip_decode_;
using Base::skip_any_;
using Base::runtime_logits_buf_;
using Base::stream_;
using Base::allocator_;
using Base::is_allocate_buffer_;
using Base::cuda_device_prop_;
private:
void allocateBuffer(std::size_t batch_size, std::vector<float> const& top_k);
};
} // namespace layers
} // namespace tensorrt_llm