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https://github.com/NVIDIA/TensorRT-LLM.git
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* Update TensorRT-LLM --------- Co-authored-by: Kota Tsuyuzaki <bloodeagle40234@gmail.com> Co-authored-by: Pzzzzz <hello-cd.plus@hotmail.com> Co-authored-by: Patrick Reiter Horn <patrick.horn@gmail.com>
138 lines
4.4 KiB
C++
138 lines
4.4 KiB
C++
/*
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* Copyright (c) 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 <gtest/gtest.h>
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#include <list>
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#include "tensorrt_llm/layers/lookaheadDecodingUtils.h"
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#include "tensorrt_llm/runtime/runtimeKernels.h"
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namespace tensorrt_llm::tests::layers
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{
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using namespace tensorrt_llm::runtime;
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using TensorPtr = runtime::ITensor::SharedPtr;
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//! Initialize a tensor with data from string @param str. Shape {str.size} by default.
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TensorPtr initTensor(std::string str, std::optional<ITensor::Shape> shape = std::nullopt);
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//! Convert tokens to logits and vice versa according to a vocabulary.
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class RandomTokenLogits
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{
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public:
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RandomTokenLogits(TensorPtr vocab)
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: mVocabulary(vocab)
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{
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}
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RandomTokenLogits(std::string vocab)
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: mVocabulary(initTensor(vocab))
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{
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}
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TensorPtr tokenToLogits(TokenIdType token) const;
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void tokenToLogits(TensorPtr logits, TokenIdType token) const;
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TokenIdType logitsToToken(TensorPtr logits) const;
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std::list<TensorPtr> stringToLogits(std::string tokens) const;
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void stringToLogits(TensorPtr logits, std::string tokens) const;
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void tensorToLogits(TensorPtr logits, TensorPtr tokens) const;
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std::string logitsToString(std::list<TensorPtr> logits) const;
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std::string logitsToString(TensorPtr logits) const;
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TensorPtr logitsToTensor(TensorPtr logits) const;
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SizeType32 getVocabSize() const;
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//! @return the last token in mVocabulary as invalid token;
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virtual TokenIdType getInvalidToken() const;
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//! @return the second-to-last token in mVocabulary as end token;
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virtual TokenIdType getEndToken() const;
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private:
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TensorPtr const mVocabulary;
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};
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//! vocabulary is ascii table from 0 to 127. tokenId == token.
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class AsciiRandomTokenLogits : public RandomTokenLogits
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{
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public:
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AsciiRandomTokenLogits()
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: RandomTokenLogits(
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[]()
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{
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auto vocab = BufferManager::cpu(ITensor::makeShape({128}), nvinfer1::DataType::kINT32);
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auto vocabRange = BufferRange<TokenIdType>(*vocab);
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TokenIdType token{0};
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std::for_each(vocabRange.begin(), vocabRange.end(), [&token](auto& v) { v = token++; });
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return vocab;
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}())
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{
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}
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virtual TokenIdType getInvalidToken() const
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{
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return static_cast<TokenIdType>('#');
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}
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virtual TokenIdType getEndToken() const
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{
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return static_cast<TokenIdType>('&');
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}
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};
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//! random LLM to simulate functions of a real LLM.
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class RandomLlm
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{
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public:
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RandomLlm(std::shared_ptr<RandomTokenLogits> table, std::string oracle, runtime::SizeType32 id = 0)
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: mTable(table)
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, mOracle(initTensor(oracle))
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, mId(id)
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{
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}
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// simulate forward in a LLM.
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void forward(TensorPtr output, TensorPtr const input, TensorPtr const position) const;
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//! set inout[i] invalid if mask[i]==false;
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void sampleByMask(TensorPtr inout, TensorPtr const mask) const;
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//! @return true when @param script is a sub-string started from @param offset.
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bool verify(SizeType32 const offset, TensorPtr const script) const;
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//! foretell @param output tokens from @param input tokens and @param position ids.
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//! It depends on different algorithms implementations.
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virtual void foretell(TensorPtr output, TensorPtr const input, TensorPtr const position) const = 0;
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protected:
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std::shared_ptr<RandomTokenLogits> mTable;
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TensorPtr mOracle;
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runtime::SizeType32 mId;
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};
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//! a lookahead implementation for RandomLlm.
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class LookaheadRandomLlm : public RandomLlm
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{
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public:
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LookaheadRandomLlm(std::shared_ptr<RandomTokenLogits> table, std::string oracle, runtime::SizeType32 id = 0)
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: RandomLlm(table, oracle, id)
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{
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}
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void foretell(TensorPtr output, TensorPtr const input, TensorPtr const position) const override;
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};
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} // namespace tensorrt_llm::tests::layers
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