TensorRT-LLMs/cpp/include/tensorrt_llm/batch_manager/trtGptModelOptionalParams.h
Kaiyu Xie 250d9c293d
Update TensorRT-LLM Release branch (#1445)
* Update TensorRT-LLM

---------

Co-authored-by: Bhuvanesh Sridharan <bhuvan.sridharan@gmail.com>
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>
Co-authored-by: Eddie-Wang1120 <wangjinheng1120@163.com>
Co-authored-by: meghagarwal <16129366+megha95@users.noreply.github.com>
2024-04-12 17:59:19 +08:00

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3.4 KiB
C++

/*
* SPDX-FileCopyrightText: Copyright (c) 2022-2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* 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/batch_manager/kvCacheConfig.h"
#include "tensorrt_llm/batch_manager/peftCacheManagerConfig.h"
#include "tensorrt_llm/executor/executor.h"
#include "tensorrt_llm/runtime/common.h"
#include "tensorrt_llm/runtime/decodingMode.h"
#include "tensorrt_llm/runtime/medusaModule.h"
#include <optional>
#include <vector>
namespace tensorrt_llm::batch_manager
{
class TrtGptModelOptionalParams
{
using KvCacheConfig = kv_cache_manager::KvCacheConfig;
public:
using SizeType = tensorrt_llm::runtime::SizeType;
explicit TrtGptModelOptionalParams(KvCacheConfig const& kvCacheConfig = KvCacheConfig{},
bool enableTrtOverlap = false, std::optional<std::vector<SizeType>> const& deviceIds = std::nullopt,
bool normalizeLogProbs = true, bool enableChunkedContext = false,
std::optional<runtime::DecodingMode> const& decodingMode = std::nullopt,
PeftCacheManagerConfig const& peftCacheManagerConfig = PeftCacheManagerConfig{},
std::optional<runtime::MedusaModule::MedusaChoices> const& medusaChoices = std::nullopt)
: kvCacheConfig{kvCacheConfig}
, enableTrtOverlap{enableTrtOverlap}
, deviceIds(deviceIds)
, normalizeLogProbs{normalizeLogProbs}
, enableChunkedContext{enableChunkedContext}
, decodingMode{decodingMode}
, peftCacheManagerConfig(peftCacheManagerConfig)
, medusaChoices(medusaChoices)
{
}
explicit TrtGptModelOptionalParams(executor::ExecutorConfig const& executorConfig)
: TrtGptModelOptionalParams(KvCacheConfig(executorConfig.getKvCacheConfig()), false,
executorConfig.getParallelConfig().value_or(executor::ParallelConfig()).getDeviceIds(),
executorConfig.getNormalizeLogProbs(), executorConfig.getEnableChunkedContext(), std::nullopt,
PeftCacheManagerConfig(executorConfig.getPeftCacheConfig().value_or(executor::PeftCacheConfig())),
executorConfig.getMedusaChoices())
{
}
bool operator==(TrtGptModelOptionalParams const& other) const
{
return kvCacheConfig == other.kvCacheConfig && enableTrtOverlap == other.enableTrtOverlap
&& deviceIds == other.deviceIds && normalizeLogProbs == other.normalizeLogProbs
&& enableChunkedContext == other.enableChunkedContext && decodingMode == other.decodingMode;
}
KvCacheConfig kvCacheConfig;
bool enableTrtOverlap;
std::optional<std::vector<SizeType>> deviceIds;
bool normalizeLogProbs;
bool enableChunkedContext;
std::optional<runtime::DecodingMode> decodingMode;
PeftCacheManagerConfig peftCacheManagerConfig;
std::optional<runtime::MedusaModule::MedusaChoices> medusaChoices;
};
} // namespace tensorrt_llm::batch_manager