mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
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74 lines
2.2 KiB
C++
74 lines
2.2 KiB
C++
/*
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* Copyright (c) 2019-2023, NVIDIA CORPORATION. All rights reserved.
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* Copyright (c) 2021, NAVER Corp. Authored by CLOVA.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#pragma once
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#include "tensorrt_llm/common/memoryUtils.h"
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#include "tensorrt_llm/common/tensor.h"
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#include "tensorrt_llm/kernels/decodingCommon.h"
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#include "tensorrt_llm/layers/baseSamplingLayer.h"
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namespace tensorrt_llm
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{
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namespace layers
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{
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template <typename T>
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class TopKSamplingLayer : public BaseSamplingLayer<T>
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{
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public:
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using Base = BaseSamplingLayer<T>;
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using SetupParams = typename Base::SetupParams;
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TopKSamplingLayer(size_t vocab_size, size_t vocab_size_padded, cudaStream_t stream,
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tensorrt_llm::common::IAllocator* allocator, bool is_free_buffer_after_forward);
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TopKSamplingLayer(TopKSamplingLayer<T> const& top_k_sampling_layer);
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~TopKSamplingLayer();
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void setup(size_t batch_size, SetupParams const& setupParams);
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protected:
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void runSampling(DecodingOutputParams& outputs, DecodingParams const& params) override;
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void freeBuffer() override;
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uint32_t runtime_max_top_k_ = 1;
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uint32_t* runtime_top_k_buf_ = nullptr;
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float* runtime_top_p_buf_ = nullptr;
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using Base::vocab_size_;
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using Base::vocab_size_padded_;
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using Base::sampling_workspace_size_;
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using Base::sampling_workspace_;
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using Base::curandstate_buf_;
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using Base::random_seeds_buf_;
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using Base::skip_decode_buf_;
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using Base::skip_decode_;
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using Base::skip_any_;
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using Base::runtime_logits_buf_;
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using Base::stream_;
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using Base::allocator_;
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using Base::is_allocate_buffer_;
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private:
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void allocateBuffer(size_t batch_size, std::vector<uint32_t> const& top_k);
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};
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} // namespace layers
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} // namespace tensorrt_llm
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