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https://github.com/NVIDIA/TensorRT-LLM.git
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9bd15f1937
* TensorRT-LLM Release 0.10.0 --------- Co-authored-by: Loki <lokravi@amazon.com> Co-authored-by: meghagarwal <16129366+megha95@users.noreply.github.com>
92 lines
3.2 KiB
C++
92 lines
3.2 KiB
C++
/*
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* Copyright (c) 2022-2024, NVIDIA CORPORATION. All rights reserved.
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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/layers/banWordsLayer.h"
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#include "tensorrt_llm/layers/baseLayer.h"
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#include "tensorrt_llm/layers/decodingLayer.h"
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#include "tensorrt_llm/layers/penaltyLayer.h"
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#include "tensorrt_llm/layers/stopCriteriaLayer.h"
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#include <memory>
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#include <vector>
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namespace tensorrt_llm::layers
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{
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enum DecodingLayers_t
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{
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PENALTY_LAYER,
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BAN_WORDS_LAYER,
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DECODING_LAYER,
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STOP_CRITERIA_LAYER
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};
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static std::vector<DecodingLayers_t> createDecodingLayerTypes(runtime::DecodingMode const& mode)
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{
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std::vector<DecodingLayers_t> types;
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if (mode.isTopKorTopP() || mode.isBeamSearch())
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{
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return {DecodingLayers_t::PENALTY_LAYER, DecodingLayers_t::BAN_WORDS_LAYER, DecodingLayers_t::DECODING_LAYER,
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DecodingLayers_t::STOP_CRITERIA_LAYER};
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}
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else if (mode.isMedusa())
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{
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return {
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DecodingLayers_t::PENALTY_LAYER, DecodingLayers_t::DECODING_LAYER, DecodingLayers_t::STOP_CRITERIA_LAYER};
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}
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TLLM_CHECK_WITH_INFO(false, "layer types are not defined for mode (%d)",
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*reinterpret_cast<runtime::DecodingMode::UnderlyingType const*>(&mode));
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return {};
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}
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template <typename T>
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static std::vector<std::unique_ptr<BaseLayer>> createLayers(runtime::DecodingMode const& mode,
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DecoderDomain const& decodingDomain, cudaStream_t stream,
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std::shared_ptr<tensorrt_llm::common::IAllocator> allocator)
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{
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std::vector<std::unique_ptr<BaseLayer>> layers;
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auto layerTypes = createDecodingLayerTypes(mode);
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TLLM_CHECK_WITH_INFO(layerTypes.size() && layerTypes[0] == DecodingLayers_t::PENALTY_LAYER,
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"Penalty layer is required to be the first layer for any decoder configuration");
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for (auto&& type : layerTypes)
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{
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std::unique_ptr<BaseLayer> layer;
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switch (type)
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{
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case DecodingLayers_t::PENALTY_LAYER:
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layer = std::make_unique<PenaltyLayer<T>>(mode, decodingDomain, stream, allocator);
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break;
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case DecodingLayers_t::BAN_WORDS_LAYER:
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layer = std::make_unique<BanWordsLayer<T>>(mode, decodingDomain, stream, allocator);
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break;
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case DecodingLayers_t::DECODING_LAYER:
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layer = std::make_unique<DecodingLayer<T>>(mode, decodingDomain, stream, allocator);
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break;
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case DecodingLayers_t::STOP_CRITERIA_LAYER:
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layer = std::make_unique<StopCriteriaLayer<T>>(mode, decodingDomain, stream, allocator);
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break;
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default: TLLM_CHECK_WITH_INFO(false, "Unknown DecodingLayers_t"); break;
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}
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layers.push_back(std::move(layer));
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}
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return layers;
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}
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} // namespace tensorrt_llm::layers
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