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https://github.com/NVIDIA/TensorRT-LLM.git
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eba3623a54
* feat/vbws-part4-v1.8: rebase Signed-off-by: wili-65535 <wili-65535@users.noreply.github.com> * feat/vbws-part4-v1.9: fix incorrect output when using short output length Signed-off-by: wili-65535 <wili-65535@users.noreply.github.com> * v1.9.1: remove useless variables Signed-off-by: wili-65535 <wili-65535@users.noreply.github.com> * v1.9.2:fix incorrect output when using short output length Signed-off-by: wili-65535 <wili-65535@users.noreply.github.com> * v1.9.3: rebase Signed-off-by: wili-65535 <wili-65535@users.noreply.github.com> * v1.9.4: rebase Signed-off-by: wili-65535 <wili-65535@users.noreply.github.com> * v1.9.5: remove API change Signed-off-by: wili-65535 <wili-65535@users.noreply.github.com> --------- Signed-off-by: wili-65535 <wili-65535@users.noreply.github.com> Co-authored-by: wili-65535 <wili-65535@users.noreply.github.com>
75 lines
2.9 KiB
C++
75 lines
2.9 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/runtime/bufferManager.h"
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#include "tensorrt_llm/runtime/common.h"
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#include "tensorrt_llm/runtime/iTensor.h"
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#include <utility>
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namespace tensorrt_llm::runtime
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{
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template <typename TTensor>
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class GenericPromptTuningParams
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{
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public:
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using TensorPtr = TTensor;
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using SizeType32 = tensorrt_llm::runtime::SizeType32;
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explicit GenericPromptTuningParams(
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TensorPtr embeddingTable = TensorPtr(), TensorPtr tasks = TensorPtr(), TensorPtr vocabSize = TensorPtr())
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: embeddingTable{std::move(embeddingTable)}
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, tasks{std::move(tasks)}
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, vocabSize{std::move(vocabSize)} {};
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// The prompt embedding table
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TensorPtr embeddingTable; // [numTasks * taskVocabSize, hidden_dim], on gpu
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// In GenerationInput, tasks expected shape is [batchSize]
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// For context requests with non-packed inputs, expected shape is [batchSize, 1]
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// For generation requests with non-packed inputs, expected shape is [batchSize*beamWidth] for generation requests.
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// For packed inputs, expected shape is [packedLength] (note that ifb currently doesn't support non-packed
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// inputs)
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TensorPtr tasks;
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TensorPtr vocabSize; // [1], on gpu
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std::vector<bool>
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promptTuningEnabled; // [batchSize] vector of bool that indicates which requests in a batch have ptuning enabled
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};
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class PromptTuningParams : public GenericPromptTuningParams<ITensor::SharedPtr>
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{
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public:
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using TensorPtr = ITensor::SharedPtr;
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using SizeType32 = GenericPromptTuningParams::SizeType32;
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explicit PromptTuningParams(
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TensorPtr embeddingTable = nullptr, TensorPtr tasks = nullptr, TensorPtr vocabSize = nullptr)
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: GenericPromptTuningParams(std::move(embeddingTable), std::move(tasks), std::move(vocabSize))
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{
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}
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// Fill the tasks tensor for the batch using the provided tasksHost
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// Function assumes that the first numContextRequests requests in the batch are context requests
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void fillTasksTensor(TensorPtr tasksHost, SizeType32 batchSize, SizeType32 numContextRequests,
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std::vector<SizeType32> const& reqBeamWidths, std::vector<SizeType32> const& reqPromptLengths,
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BufferManager const& manager, bool packedInput);
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};
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} // namespace tensorrt_llm::runtime
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