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https://github.com/NVIDIA/TensorRT-LLM.git
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bca9a33b02
* Update TensorRT-LLM --------- Co-authored-by: Timur Abishev <abishev.timur@gmail.com> Co-authored-by: MahmoudAshraf97 <hassouna97.ma@gmail.com> Co-authored-by: Saeyoon Oh <saeyoon.oh@furiosa.ai> Co-authored-by: hattizai <hattizai@gmail.com>
102 lines
4.4 KiB
C++
102 lines
4.4 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: Apache-2.0
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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/batch_manager/kvCacheConfig.h"
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#include "tensorrt_llm/batch_manager/peftCacheManagerConfig.h"
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#include "tensorrt_llm/executor/executor.h"
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#include "tensorrt_llm/runtime/common.h"
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#include <optional>
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#include <utility>
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#include <vector>
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namespace tensorrt_llm::batch_manager
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{
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class TrtGptModelOptionalParams
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{
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using KvCacheConfig = kv_cache_manager::KvCacheConfig;
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public:
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using SizeType32 = tensorrt_llm::runtime::SizeType32;
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explicit TrtGptModelOptionalParams(KvCacheConfig const& kvCacheConfig = KvCacheConfig{},
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bool enableTrtOverlap = false, std::optional<std::vector<SizeType32>> const& deviceIds = std::nullopt,
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bool normalizeLogProbs = true, bool enableChunkedContext = false,
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PeftCacheManagerConfig const& peftCacheManagerConfig = PeftCacheManagerConfig{},
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executor::DecodingConfig decodingConfig = executor::DecodingConfig{}, float gpuWeightsPercent = 1,
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std::optional<SizeType32> maxBeamWidth = std::nullopt, std::optional<SizeType32> maxBatchSize = std::nullopt,
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std::optional<SizeType32> maxNumTokens = std::nullopt,
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executor::SchedulerConfig const& schedulerConfig = executor::SchedulerConfig{}, bool multiBlockMode = false)
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: kvCacheConfig{kvCacheConfig}
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, enableTrtOverlap{enableTrtOverlap}
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, deviceIds(deviceIds)
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, normalizeLogProbs{normalizeLogProbs}
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, enableChunkedContext{enableChunkedContext}
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, peftCacheManagerConfig(peftCacheManagerConfig)
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, decodingConfig(std::move(decodingConfig))
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, gpuWeightsPercent(gpuWeightsPercent)
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, maxBeamWidth(maxBeamWidth)
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, maxBatchSize(maxBatchSize)
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, maxNumTokens(maxNumTokens)
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, schedulerConfig{schedulerConfig}
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, multiBlockMode(multiBlockMode)
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{
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}
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explicit TrtGptModelOptionalParams(executor::ExecutorConfig const& executorConfig)
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: TrtGptModelOptionalParams(KvCacheConfig(executorConfig.getKvCacheConfig()), false,
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executorConfig.getParallelConfig().value_or(executor::ParallelConfig()).getDeviceIds(),
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executorConfig.getNormalizeLogProbs(), executorConfig.getEnableChunkedContext(),
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PeftCacheManagerConfig(executorConfig.getPeftCacheConfig().value_or(executor::PeftCacheConfig())),
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executorConfig.getDecodingConfig().value_or(executor::DecodingConfig{}),
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executorConfig.getGpuWeightsPercent(), executorConfig.getMaxBeamWidth(), executorConfig.getMaxBatchSize(),
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executorConfig.getMaxNumTokens(), executorConfig.getSchedulerConfig(), executorConfig.getMultiBlockMode())
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{
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}
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bool operator==(TrtGptModelOptionalParams const& other) const
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{
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return kvCacheConfig == other.kvCacheConfig && enableTrtOverlap == other.enableTrtOverlap
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&& deviceIds == other.deviceIds && normalizeLogProbs == other.normalizeLogProbs
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&& enableChunkedContext == other.enableChunkedContext && decodingConfig == other.decodingConfig
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&& gpuWeightsPercent == other.gpuWeightsPercent && multiBlockMode == other.multiBlockMode;
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}
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friend std::ostream& operator<<(std::ostream& os, TrtGptModelOptionalParams const& self);
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KvCacheConfig kvCacheConfig;
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bool enableTrtOverlap;
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std::optional<std::vector<SizeType32>> deviceIds;
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bool normalizeLogProbs;
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bool enableChunkedContext;
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PeftCacheManagerConfig peftCacheManagerConfig;
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executor::DecodingConfig decodingConfig;
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// Percentage of weights on the gpu at runtime
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float gpuWeightsPercent;
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std::optional<SizeType32> maxBeamWidth;
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std::optional<SizeType32> maxBatchSize;
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std::optional<SizeType32> maxNumTokens;
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executor::SchedulerConfig schedulerConfig;
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bool multiBlockMode;
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};
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} // namespace tensorrt_llm::batch_manager
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