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https://github.com/NVIDIA/TensorRT-LLM.git
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59 lines
1.7 KiB
C++
59 lines
1.7 KiB
C++
/*
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* SPDX-FileCopyrightText: Copyright (c) 2025 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/common.h"
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#include "tensorrt_llm/runtime/iTensor.h"
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namespace tensorrt_llm::runtime
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{
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class TllmRuntime;
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} // namespace tensorrt_llm::runtime
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namespace tensorrt_llm::batch_manager
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{
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namespace rnn_state_manager
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{
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class RnnStateManager;
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}
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class RnnStateBuffers
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{
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public:
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using SizeType32 = tensorrt_llm::runtime::SizeType32;
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using TensorPtr = runtime::ITensor::SharedPtr;
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using TensorMap = runtime::StringPtrMap<runtime::ITensor>;
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// others should be in rnnStateManager, we only need slotMapping here.
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TensorPtr slotMappingHost; // [batch_size]
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TensorPtr slotMappingDevice; // [batch_size]
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RnnStateBuffers(SizeType32 maxBatchSize, runtime::TllmRuntime const& runtime);
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void reshape(SizeType32 numSequences);
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void fillSlotMappings(RequestVector const& contextRequests, rnn_state_manager::RnnStateManager* rnnStateManager);
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void copySlotMappingH2D(runtime::TllmRuntime const& runtime);
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void getBuffers(TensorMap& inputBuffers) const;
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};
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} // namespace tensorrt_llm::batch_manager
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