novel deep learning research works with PaddlePaddle

Overview

Research

发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。

目录

计算机视觉

任务类型 目录 简介 论文链接
图像检索 GNN-Re-Ranking 基于GNN的快速图像检索Re-Ranking。 https://arxiv.org/abs/2012.07620v2
车流统计 VehicleCounting AICITY2020 车流统计竞赛datasetA TOP1 方案。 -
车辆再识别 PaddleReid 给定目标车辆,在检索库中检索同id车辆,支持多种特征子网络。 -
车辆异常检测 AICity2020-Anomaly-Detection 在监控视频中检测车辆异常情况,例如车辆碰撞、失速等。 -
医学图像分析 AGEchallenge 任务:在AS-OCT图像的公共数据集上进行闭角型分类和巩膜突点定位;基线模型:对应以上各任务的基线模型。 -
光流估计 PWCNet 基于金字塔式处理,逐层学习细部光流,设计代价容量函数三原则的CNN模型,用于光流估计。 https://arxiv.org/abs/1709.02371
语义分割 SemSegPaddle 针对多个数据集的图像语义分割模型的实现,包括Cityscapes、Pascal Context和ADE20K。 -
轻量化检测 astar2019 百度之星轻量化检测比赛评测工具。 -
地标检索与识别 landmark 基于检索的地标检索与识别系统,支持地标型与非地标型识别、识别与检索结果相结合的多重识别结果投票和重新排序。 https://arxiv.org/abs/1906.03990
图像分类 webvision2018 模型利用重加权网络(URNet)缓解web数据中偏倚和噪声的影响,进行web图像分类。 https://arxiv.org/abs/1811.00700
图像分类 CLPI 模型利用一个Lesion Generator改善了糖尿病视网膜病变图像分级的模型性能,理论上可用于所有希望实现局部+整体模型分析的场景 -
小样本学习 PaddleFSL 小样本学习工具包,可复现多个常用基线方法在多个图片分类数据集上的汇报效果 -

自然语言处理

任务类型 目录 简介 论文链接
中文词法分析 LAC(Lexical Analysis of Chinese) 百度自主研发中文特色模型词法分析任务,集成了中文分词、词性标注和命名实体识别任务。输入是一个字符串,而输出是句子中的词边界和词性、实体类别。 -
主动对话 DuConv 机器根据给定知识信息主动引领对话进程完成设定的对话目标。 https://www.aclweb.org/anthology/P19-1369/
语义解析 Text2SQL-BASELINE 输入自然语言问题和相应的数据库,生成与问题对应的 SQL 查询语句,通过执行该 SQL 可得到问题的答案。 -
多轮对话 DAM 开放领域多轮对话匹配的深度注意力机制模型,根据多轮对话历史和候选回复内容,排序出最合适的回复。 http://aclweb.org/anthology/P18-1103
阅读理解 DuReader 数据集:大规模、面向真实应用、由人类生成的中文阅读理解数据集,聚焦于真实世界中的不限定领域的问答任务;基线系统:针对DuReader数据集实现的经典BiDAF模型。 https://www.aclweb.org/anthology/W18-2605/
关系抽取 ARNOR 数据集:用于对远程监督关系提取模型进行句子级别的评价;模型:基于注意力正则化识别噪声数据,通过bootstrap方法逐步选择出高质量的标注数据。 https://www.aclweb.org/anthology/P19-1135/
机器翻译 JEMT 模型的输入端包括文字信息及发音信息,嵌入层融合文字信息和发音信息进行翻译。 https://arxiv.org/abs/1810.06729
阅读理解 KTNET 模型将知识库中的知识整合到预先训练好的上下文表示中,利用丰富的知识增强机器阅读理解的预训练语言表示。 https://www.aclweb.org/anthology/P19-1226
对话生成 PLATO 基于隐空间的端到端的预训练对话生成模型,可以灵活支持多种对话,包括闲聊、知识聊天、对话问答等。 http://arxiv.org/abs/1910.07931
阅读理解 DuReader-Robust-BASELINE 数据集:DuReader-robust,中文数据集,用于全面评价机器阅读理解模型的鲁棒性;基线系统:针对该数据集,基于ERNIE实现的阅读理解基线系统。 https://arxiv.org/abs/2004.11142
对话生成 AKGCM 包含知识增强图、知识选择和知识感知响应生成器的聊天机器人。 https://www.aclweb.org/anthology/D19-1187/
机器翻译 MAL 多智能体端到端联合学习框架,通过多个智能体的互相学习提升翻译质量。 https://arxiv.org/abs/1909.01101
对话生成 MMPMS 针对开放域对话中一对多问题,利用多映射机制和后验映射选择模块进行多样性、丰富化的对话生成。 https://arxiv.org/abs/1906.01781
阅读理解 MRQA2019-BASELINE 机器阅读理解任务的基线模型,基于ERNIE预训练模型,支持多GPU微调预测。 -
阅读理解 D-NET 预训练及微调框架,包含多任务学习及多预训练模型的融合,用于阅读理解模型的生成。 https://www.aclweb.org/anthology/D19-5828/
建议挖掘 MPM 利用多视角架构来学习表示和双向transformer编码器进行论坛评论建议挖掘。 https://www.aclweb.org/anthology/S19-2216/
多文档摘要 ACL2020-GraphSum 基于图表示的生成式多文档摘要模型,将显式图结构信息引入到端到端摘要生成过程中。 https://www.aclweb.org/anthology/2020.acl-main.555.pdf
融合多种对话类型的对话式推荐 ACL2020-DuRecDial 提出新任务:融合闲聊、任务型对话、问答和推荐等多种对话类型的对话式推荐,构建DuRecDial数据集,提出具有多对话目标驱动策略机制的对话生成框架。 https://www.aclweb.org/anthology/2020.acl-main.98/
面向推荐的对话 Conversational-Recommendation-BASELINE 融合人机对话系统和个性化推荐系统,定义新一代智能推荐技术,该系统先通过问答或闲聊收集用户兴趣和偏好,然后主动给用户推荐其感兴趣的内容,比如餐厅、美食、电影、新闻等。 -
稠密段落检索 ACL2021-PAIR 基于以段落相似度为中心的相似度关系提升稠密段落检索,基于知识蒸馏进行采样,采用两阶段训练方式。 https://aclanthology.org/2021.findings-acl.191/

知识图谱

任务类型 目录 简介 论文链接
知识图谱表示学习 CoKE 百度自主研发语境化知识图谱表示学习框架CoKE,在知识图谱链接预测和多步查询任务上取得学界领先效果。 https://arxiv.org/abs/1911.02168
关系抽取 DuIE_Baseline 语言与智能技术竞赛关系抽取任务DuIE 2.0基线系统,通过设计结构化标注体系,实现基于ERNIE的端到端SPO抽取模型。 -
事件抽取 DuEE_baseline 语言与智能技术竞赛事件抽取任务DuEE 1.0基线系统,实现基于ERNIE+CRF的Pipeline事件抽取模型。 -
实体链指 DuEL_Baseline 面向中文短文本的实体链指任务(CCKS 2020)的基线系统,实现基于ERNIE和多任务机制的实体链指模型。 -
辅助诊断 SignOrSymptom_Relationship 针对EMR具有无结构化文本和结构化信息并存的特点,结合医疗NLU,以深度学习模型实现EMR的向量化表示、诊断预分类和概率计算。 -
文档级关系抽取 SSAN 引入并建模实体间的依赖结构,在文档级关系抽取任务上取得学界领先效果。 https://arxiv.org/abs/2102.10249

时空数据挖掘

任务类型 目录 简介 论文链接
固定资产价值估计 MONOPOLY 实用的POI商业智能算法,对大量其他的固定资产进行价值估计,包括城市居民对不同公共资产价格评估、私有房价评估偏好的发现与量化分析,以及对评估固定资产价格需考虑的空间范围的确定。 https://dl.acm.org/doi/10.1145/3357384.3357810
兴趣点生成 P3AC 具备个性化的前缀嵌入的POI自动生成。 -
区域生成 P3AC 基于路网进行区域划分的方法, 实现对特定区域基于路网的全划分,区域之间无交叠,无空隙,算法支持对全球的区域划分。 -

许可证书

此向导由PaddlePaddle贡献,受Apache-2.0 license许可认证。

Comments
  • PLATO-LTM中的Persona Extractor一些疑惑

    PLATO-LTM中的Persona Extractor一些疑惑

    非常感谢Baidu的开源~

    有两个问题希望可以解答一下: 1): 关于在PLATO-LTM中的Persona Extractor,在我看来应该有四个作用:PE用来判断一句话是否需要用到角色信息和一句话是否可以作为角色信息,所以PE是否应该是一个四分类的分类器?,即:0-不能作为角色信息、1-可以作为机器人的角色信息、2-可以作为用户的角色信息、3-需要用到Memory中的角色信息**,其中1和2作为Positive sample.

    2):关于开源数据集如何训练PE 开源的数据集似乎不是训练PE的数据集,请问是否有开源计划?

    非常希望得到解答~ 祝520快乐~

    opened by cingtiye 9
  • CoKE on WN18RR

    CoKE on WN18RR

    Hi Team,

    I am learning CoKE released from your team recently. I followed the steps and run the model on WN18RR with specified hyper-parameteres for multiple times, but the model trained locally cannot reproduce the performance denoted in the paper. Here are the hyper-parameters for training (actually they are default settings specified in "wn18rr_job_config.sh"):

    do_train: True ema_decay: 0.9999 epoch: 1000 hidden_act: gelu hidden_dropout_prob: 0.1 hidden_size: 256 in_tokens: False init_checkpoint: None init_pretraining_params: None initializer_range: 0.02 intermediate_size: 512 learning_rate: 0.0005 loss_scaling: 1.0 lr_scheduler: linear_warmup_decay max_position_embeddings: 40 max_seq_len: 3 num_attention_heads: 4 num_hidden_layers: 12 num_iteration_per_drop_scope: 1 num_relations: 11 predict_file: None sen_candli_file: None sen_trivial_file: None skip_steps: 1000 soft_label: 0.15 train_file: ./data/wn18rr/train.coke.txt true_triple_path: ./data/wn18rr/all.txt use_cuda: True use_ema: False use_fast_executor: False use_fp16: False verbose: False vocab_path: ./data/wn18rr/vocab.txt vocab_size: 41054 warmup_proportion: 0.1 weight_decay: 0.01 weight_sharing: True

    The performance are: TASK MRR Hits@1 Hits@3 Hits@10 wn18rr 0.462 0.427 0.475 0.533 (local) instead of wn18rr 0.484 0.450 0.496 0.553 (paper)

    I wonder whether this repository is the up-to-date version, or the best performance use another set of hyper-parameters? Could you please provide some hints for this issue. Thank you.

    Additionally, there is a pretrained model which can be downloaded using "wget_kbc_models.sh" (step 4), but it seems the link is unavailable now. Hopefully this can be fixed.

    Best regards

    opened by ccchobits 3
  • I think parallel.py in PLATO implementation raises attribute error

    I think parallel.py in PLATO implementation raises attribute error

    Hello, It might be a silly question because it's my first time using paddle based codes... I hope your understanding!

    I'm trying to run PLATO fine-tuning code, and I met 'Parameter' object has no attribute '_grad_ivar' error' at apply_collectice_grads function in parallel.py in plato implementation.

    I also noticed that this function is also implemented in paddle/fluid/dygraph/parallel.py, and it was slightly different from the implementation in plato.

    Therefore, I changed the function in plato just like the function in paddle implementaion. As a result, I can run this code, but I still don't know if this method will make sense... I need your help!!

    Thank you.

    
            for param in self._layers.parameters():
                # NOTE(zcd): The grad_ivar maybe no generated.
                #if param.trainable and param._grad_ivar():
                if param.trainable and param._ivar._grad_ivar():
                    g_var = param._grad_ivar()
                    grad_vars.append(g_var)
                    assert g_var not in grad_var_set
                    grad_var_set.add(g_var)
    
    

    at apply_collectice_grads function in Research/NLP/Dialogue-PLATO/plato/modules/parallel.py

    
            for param in self._layers.parameters():
                # NOTE(zcd): The grad_ivar maybe no generated.
                if param.trainable and param._ivar._grad_ivar():
                    g_var = framework.Variable(
                        block=self._helper.main_program.current_block(),
                        name=param._ivar._grad_name(),
                        stop_gradient=True,
                        ivar=param._ivar._grad_ivar())
                    grad_vars.append(g_var)
                    assert g_var not in grad_var_set
                    grad_var_set.add(g_var)
    
    

    at apply_collectice_grads function in paddle/fluid/dygraph/parallel.py

    opened by rokslej 3
  • Bump numpy from 1.20.2 to 1.21.0 in /NLP/UNIMO-2

    Bump numpy from 1.20.2 to 1.21.0 in /NLP/UNIMO-2

    Bumps numpy from 1.20.2 to 1.21.0.

    Release notes

    Sourced from numpy's releases.

    v1.21.0

    NumPy 1.21.0 Release Notes

    The NumPy 1.21.0 release highlights are

    • continued SIMD work covering more functions and platforms,
    • initial work on the new dtype infrastructure and casting,
    • universal2 wheels for Python 3.8 and Python 3.9 on Mac,
    • improved documentation,
    • improved annotations,
    • new PCG64DXSM bitgenerator for random numbers.

    In addition there are the usual large number of bug fixes and other improvements.

    The Python versions supported for this release are 3.7-3.9. Official support for Python 3.10 will be added when it is released.

    :warning: Warning: there are unresolved problems compiling NumPy 1.21.0 with gcc-11.1 .

    • Optimization level -O3 results in many wrong warnings when running the tests.
    • On some hardware NumPy will hang in an infinite loop.

    New functions

    Add PCG64DXSM BitGenerator

    Uses of the PCG64 BitGenerator in a massively-parallel context have been shown to have statistical weaknesses that were not apparent at the first release in numpy 1.17. Most users will never observe this weakness and are safe to continue to use PCG64. We have introduced a new PCG64DXSM BitGenerator that will eventually become the new default BitGenerator implementation used by default_rng in future releases. PCG64DXSM solves the statistical weakness while preserving the performance and the features of PCG64.

    See upgrading-pcg64 for more details.

    (gh-18906)

    Expired deprecations

    • The shape argument numpy.unravel_index cannot be passed as dims keyword argument anymore. (Was deprecated in NumPy 1.16.)

    ... (truncated)

    Commits
    • b235f9e Merge pull request #19283 from charris/prepare-1.21.0-release
    • 34aebc2 MAINT: Update 1.21.0-notes.rst
    • 493b64b MAINT: Update 1.21.0-changelog.rst
    • 07d7e72 MAINT: Remove accidentally created directory.
    • 032fca5 Merge pull request #19280 from charris/backport-19277
    • 7d25b81 BUG: Fix refcount leak in ResultType
    • fa5754e BUG: Add missing DECREF in new path
    • 61127bb Merge pull request #19268 from charris/backport-19264
    • 143d45f Merge pull request #19269 from charris/backport-19228
    • d80e473 BUG: Removed typing for == and != in dtypes
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 2
  • Bump pillow from 8.2.0 to 9.0.1 in /NLP/UNIMO-2

    Bump pillow from 8.2.0 to 9.0.1 in /NLP/UNIMO-2

    Bumps pillow from 8.2.0 to 9.0.1.

    Release notes

    Sourced from pillow's releases.

    9.0.1

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.1.html

    Changes

    • In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [@​radarhere, @​hugovk]
    • Restrict builtins within lambdas for ImageMath.eval. CVE-2022-22817 #6009 [radarhere]

    9.0.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.0.1 (2022-02-03)

    • In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [radarhere, hugovk]

    • Restrict builtins within lambdas for ImageMath.eval. CVE-2022-22817 #6009 [radarhere]

    9.0.0 (2022-01-02)

    • Restrict builtins for ImageMath.eval(). CVE-2022-22817 #5923 [radarhere]

    • Ensure JpegImagePlugin stops at the end of a truncated file #5921 [radarhere]

    • Fixed ImagePath.Path array handling. CVE-2022-22815, CVE-2022-22816 #5920 [radarhere]

    • Remove consecutive duplicate tiles that only differ by their offset #5919 [radarhere]

    • Improved I;16 operations on big endian #5901 [radarhere]

    • Limit quantized palette to number of colors #5879 [radarhere]

    • Fixed palette index for zeroed color in FASTOCTREE quantize #5869 [radarhere]

    • When saving RGBA to GIF, make use of first transparent palette entry #5859 [radarhere]

    • Pass SAMPLEFORMAT to libtiff #5848 [radarhere]

    • Added rounding when converting P and PA #5824 [radarhere]

    • Improved putdata() documentation and data handling #5910 [radarhere]

    • Exclude carriage return in PDF regex to help prevent ReDoS #5912 [hugovk]

    • Fixed freeing pointer in ImageDraw.Outline.transform #5909 [radarhere]

    ... (truncated)

    Commits
    • 6deac9e 9.0.1 version bump
    • c04d812 Update CHANGES.rst [ci skip]
    • 4fabec3 Added release notes for 9.0.1
    • 02affaa Added delay after opening image with xdg-open
    • ca0b585 Updated formatting
    • 427221e In show_file, use os.remove to remove temporary images
    • c930be0 Restrict builtins within lambdas for ImageMath.eval
    • 75b69dd Dont need to pin for GHA
    • cd938a7 Autolink CWE numbers with sphinx-issues
    • 2e9c461 Add CVE IDs
    • Additional commits viewable in compare view

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    dependencies 
    opened by dependabot[bot] 2
  • Bump numpy from 1.14.5 to 1.21.0 in /KG/DuEE_baseline/DuEE-PaddleHub

    Bump numpy from 1.14.5 to 1.21.0 in /KG/DuEE_baseline/DuEE-PaddleHub

    Bumps numpy from 1.14.5 to 1.21.0.

    Release notes

    Sourced from numpy's releases.

    v1.21.0

    NumPy 1.21.0 Release Notes

    The NumPy 1.21.0 release highlights are

    • continued SIMD work covering more functions and platforms,
    • initial work on the new dtype infrastructure and casting,
    • universal2 wheels for Python 3.8 and Python 3.9 on Mac,
    • improved documentation,
    • improved annotations,
    • new PCG64DXSM bitgenerator for random numbers.

    In addition there are the usual large number of bug fixes and other improvements.

    The Python versions supported for this release are 3.7-3.9. Official support for Python 3.10 will be added when it is released.

    :warning: Warning: there are unresolved problems compiling NumPy 1.21.0 with gcc-11.1 .

    • Optimization level -O3 results in many wrong warnings when running the tests.
    • On some hardware NumPy will hang in an infinite loop.

    New functions

    Add PCG64DXSM BitGenerator

    Uses of the PCG64 BitGenerator in a massively-parallel context have been shown to have statistical weaknesses that were not apparent at the first release in numpy 1.17. Most users will never observe this weakness and are safe to continue to use PCG64. We have introduced a new PCG64DXSM BitGenerator that will eventually become the new default BitGenerator implementation used by default_rng in future releases. PCG64DXSM solves the statistical weakness while preserving the performance and the features of PCG64.

    See upgrading-pcg64 for more details.

    (gh-18906)

    Expired deprecations

    • The shape argument numpy.unravel_index cannot be passed as dims keyword argument anymore. (Was deprecated in NumPy 1.16.)

    ... (truncated)

    Commits
    • b235f9e Merge pull request #19283 from charris/prepare-1.21.0-release
    • 34aebc2 MAINT: Update 1.21.0-notes.rst
    • 493b64b MAINT: Update 1.21.0-changelog.rst
    • 07d7e72 MAINT: Remove accidentally created directory.
    • 032fca5 Merge pull request #19280 from charris/backport-19277
    • 7d25b81 BUG: Fix refcount leak in ResultType
    • fa5754e BUG: Add missing DECREF in new path
    • 61127bb Merge pull request #19268 from charris/backport-19264
    • 143d45f Merge pull request #19269 from charris/backport-19228
    • d80e473 BUG: Removed typing for == and != in dtypes
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    dependencies 
    opened by dependabot[bot] 2
  • Bump numpy from 1.16.1 to 1.21.0 in /NLP/Conversational-Recommendation-BASELINE

    Bump numpy from 1.16.1 to 1.21.0 in /NLP/Conversational-Recommendation-BASELINE

    Bumps numpy from 1.16.1 to 1.21.0.

    Release notes

    Sourced from numpy's releases.

    v1.21.0

    NumPy 1.21.0 Release Notes

    The NumPy 1.21.0 release highlights are

    • continued SIMD work covering more functions and platforms,
    • initial work on the new dtype infrastructure and casting,
    • universal2 wheels for Python 3.8 and Python 3.9 on Mac,
    • improved documentation,
    • improved annotations,
    • new PCG64DXSM bitgenerator for random numbers.

    In addition there are the usual large number of bug fixes and other improvements.

    The Python versions supported for this release are 3.7-3.9. Official support for Python 3.10 will be added when it is released.

    :warning: Warning: there are unresolved problems compiling NumPy 1.21.0 with gcc-11.1 .

    • Optimization level -O3 results in many wrong warnings when running the tests.
    • On some hardware NumPy will hang in an infinite loop.

    New functions

    Add PCG64DXSM BitGenerator

    Uses of the PCG64 BitGenerator in a massively-parallel context have been shown to have statistical weaknesses that were not apparent at the first release in numpy 1.17. Most users will never observe this weakness and are safe to continue to use PCG64. We have introduced a new PCG64DXSM BitGenerator that will eventually become the new default BitGenerator implementation used by default_rng in future releases. PCG64DXSM solves the statistical weakness while preserving the performance and the features of PCG64.

    See upgrading-pcg64 for more details.

    (gh-18906)

    Expired deprecations

    • The shape argument numpy.unravel_index cannot be passed as dims keyword argument anymore. (Was deprecated in NumPy 1.16.)

    ... (truncated)

    Commits
    • b235f9e Merge pull request #19283 from charris/prepare-1.21.0-release
    • 34aebc2 MAINT: Update 1.21.0-notes.rst
    • 493b64b MAINT: Update 1.21.0-changelog.rst
    • 07d7e72 MAINT: Remove accidentally created directory.
    • 032fca5 Merge pull request #19280 from charris/backport-19277
    • 7d25b81 BUG: Fix refcount leak in ResultType
    • fa5754e BUG: Add missing DECREF in new path
    • 61127bb Merge pull request #19268 from charris/backport-19264
    • 143d45f Merge pull request #19269 from charris/backport-19228
    • d80e473 BUG: Removed typing for == and != in dtypes
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    dependencies 
    opened by dependabot[bot] 2
  • why are some tokens missed in the decoded output of Graphsum?

    why are some tokens missed in the decoded output of Graphsum?

    Hi, I trained graphsum on new mult-document summarization for comparision. But when I do testing ,I find some tokens are missing in the output, like this "" n " exical " unctional " rammars". It seems that the first token is not decoded. So I guess it may be cause by sentencepiece tokenizer. So I wonder what's the special format of the raw input?

    Thanks. @Weili-NLP

    opened by muguruzawang 2
  • Bump pillow from 6.2.0 to 9.0.1 in /NLP/Conversational-Recommendation-BASELINE

    Bump pillow from 6.2.0 to 9.0.1 in /NLP/Conversational-Recommendation-BASELINE

    Bumps pillow from 6.2.0 to 9.0.1.

    Release notes

    Sourced from pillow's releases.

    9.0.1

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.1.html

    Changes

    • In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [@​radarhere, @​hugovk]
    • Restrict builtins within lambdas for ImageMath.eval. CVE-2022-22817 #6009 [radarhere]

    9.0.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.0.1 (2022-02-03)

    • In show_file, use os.remove to remove temporary images. CVE-2022-24303 #6010 [radarhere, hugovk]

    • Restrict builtins within lambdas for ImageMath.eval. CVE-2022-22817 #6009 [radarhere]

    9.0.0 (2022-01-02)

    • Restrict builtins for ImageMath.eval(). CVE-2022-22817 #5923 [radarhere]

    • Ensure JpegImagePlugin stops at the end of a truncated file #5921 [radarhere]

    • Fixed ImagePath.Path array handling. CVE-2022-22815, CVE-2022-22816 #5920 [radarhere]

    • Remove consecutive duplicate tiles that only differ by their offset #5919 [radarhere]

    • Improved I;16 operations on big endian #5901 [radarhere]

    • Limit quantized palette to number of colors #5879 [radarhere]

    • Fixed palette index for zeroed color in FASTOCTREE quantize #5869 [radarhere]

    • When saving RGBA to GIF, make use of first transparent palette entry #5859 [radarhere]

    • Pass SAMPLEFORMAT to libtiff #5848 [radarhere]

    • Added rounding when converting P and PA #5824 [radarhere]

    • Improved putdata() documentation and data handling #5910 [radarhere]

    • Exclude carriage return in PDF regex to help prevent ReDoS #5912 [hugovk]

    • Fixed freeing pointer in ImageDraw.Outline.transform #5909 [radarhere]

    ... (truncated)

    Commits
    • 6deac9e 9.0.1 version bump
    • c04d812 Update CHANGES.rst [ci skip]
    • 4fabec3 Added release notes for 9.0.1
    • 02affaa Added delay after opening image with xdg-open
    • ca0b585 Updated formatting
    • 427221e In show_file, use os.remove to remove temporary images
    • c930be0 Restrict builtins within lambdas for ImageMath.eval
    • 75b69dd Dont need to pin for GHA
    • cd938a7 Autolink CWE numbers with sphinx-issues
    • 2e9c461 Add CVE IDs
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    dependencies 
    opened by dependabot[bot] 2
  • Bump protobuf from 3.10.0 to 3.15.0 in /NLP/Conversational-Recommendation-BASELINE

    Bump protobuf from 3.10.0 to 3.15.0 in /NLP/Conversational-Recommendation-BASELINE

    Bumps protobuf from 3.10.0 to 3.15.0.

    Release notes

    Sourced from protobuf's releases.

    Protocol Buffers v3.15.0

    Protocol Compiler

    • Optional fields for proto3 are enabled by default, and no longer require the --experimental_allow_proto3_optional flag.

    C++

    • MessageDifferencer: fixed bug when using custom ignore with multiple unknown fields
    • Use init_seg in MSVC to push initialization to an earlier phase.
    • Runtime no longer triggers -Wsign-compare warnings.
    • Fixed -Wtautological-constant-out-of-range-compare warning.
    • DynamicCastToGenerated works for nullptr input for even if RTTI is disabled
    • Arena is refactored and optimized.
    • Clarified/specified that the exact value of Arena::SpaceAllocated() is an implementation detail users must not rely on. It should not be used in unit tests.
    • Change the signature of Any::PackFrom() to return false on error.
    • Add fast reflection getter API for strings.
    • Constant initialize the global message instances
    • Avoid potential for missed wakeup in UnknownFieldSet
    • Now Proto3 Oneof fields have "has" methods for checking their presence in C++.
    • Bugfix for NVCC
    • Return early in _InternalSerialize for empty maps.
    • Adding functionality for outputting map key values in proto path logging output (does not affect comparison logic) and stop printing 'value' in the path. The modified print functionality is in the MessageDifferencer::StreamReporter.
    • Fixed protocolbuffers/protobuf#8129
    • Ensure that null char symbol, package and file names do not result in a crash.
    • Constant initialize the global message instances
    • Pretty print 'max' instead of numeric values in reserved ranges.
    • Removed remaining instances of std::is_pod, which is deprecated in C++20.
    • Changes to reduce code size for unknown field handling by making uncommon cases out of line.
    • Fix std::is_pod deprecated in C++20 (#7180)
    • Fix some -Wunused-parameter warnings (#8053)
    • Fix detecting file as directory on zOS issue #8051 (#8052)
    • Don't include sys/param.h for _BYTE_ORDER (#8106)
    • remove CMAKE_THREAD_LIBS_INIT from pkgconfig CFLAGS (#8154)
    • Fix TextFormatMapTest.DynamicMessage issue#5136 (#8159)
    • Fix for compiler warning issue#8145 (#8160)
    • fix: support deprecated enums for GCC < 6 (#8164)
    • Fix some warning when compiling with Visual Studio 2019 on x64 target (#8125)

    Python

    • Provided an override for the reverse() method that will reverse the internal collection directly instead of using the other methods of the BaseContainer.
    • MessageFactory.CreateProtoype can be overridden to customize class creation.

    ... (truncated)

    Commits
    • ae50d9b Update protobuf version
    • 8260126 Update protobuf version
    • c741c46 Resovled issue in the .pb.cc files
    • eef2764 Resolved an issue where NO_DESTROY and CONSTINIT were in incorrect order
    • 0040102 Updated collect_all_artifacts.sh for Ubuntu Xenial
    • 26cb6a7 Delete root-owned files in Kokoro builds
    • 1e924ef Update port_def.inc
    • 9a80cf1 Update coded_stream.h
    • a97c4f4 Merge pull request #8276 from haberman/php-warning
    • 44cd75d Merge pull request #8282 from haberman/changelog
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    dependencies 
    opened by dependabot[bot] 2
  • Bump pillow from 6.2.0 to 9.0.0 in /NLP/Conversational-Recommendation-BASELINE

    Bump pillow from 6.2.0 to 9.0.0 in /NLP/Conversational-Recommendation-BASELINE

    Bumps pillow from 6.2.0 to 9.0.0.

    Release notes

    Sourced from pillow's releases.

    9.0.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.0.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.0.0 (2022-01-02)

    • Restrict builtins for ImageMath.eval(). CVE-2022-22817 #5923 [radarhere]

    • Ensure JpegImagePlugin stops at the end of a truncated file #5921 [radarhere]

    • Fixed ImagePath.Path array handling. CVE-2022-22815, CVE-2022-22816 #5920 [radarhere]

    • Remove consecutive duplicate tiles that only differ by their offset #5919 [radarhere]

    • Improved I;16 operations on big endian #5901 [radarhere]

    • Limit quantized palette to number of colors #5879 [radarhere]

    • Fixed palette index for zeroed color in FASTOCTREE quantize #5869 [radarhere]

    • When saving RGBA to GIF, make use of first transparent palette entry #5859 [radarhere]

    • Pass SAMPLEFORMAT to libtiff #5848 [radarhere]

    • Added rounding when converting P and PA #5824 [radarhere]

    • Improved putdata() documentation and data handling #5910 [radarhere]

    • Exclude carriage return in PDF regex to help prevent ReDoS #5912 [hugovk]

    • Fixed freeing pointer in ImageDraw.Outline.transform #5909 [radarhere]

    • Added ImageShow support for xdg-open #5897 [m-shinder, radarhere]

    • Support 16-bit grayscale ImageQt conversion #5856 [cmbruns, radarhere]

    • Convert subsequent GIF frames to RGB or RGBA #5857 [radarhere]

    ... (truncated)

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    dependencies 
    opened by dependabot[bot] 2
  • Bump certifi from 2020.12.5 to 2022.12.7 in /NLP/UNIMO-2

    Bump certifi from 2020.12.5 to 2022.12.7 in /NLP/UNIMO-2

    Bumps certifi from 2020.12.5 to 2022.12.7.

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    dependencies 
    opened by dependabot[bot] 1
  • Bump certifi from 2019.9.11 to 2022.12.7 in /NLP/Conversational-Recommendation-BASELINE

    Bump certifi from 2019.9.11 to 2022.12.7 in /NLP/Conversational-Recommendation-BASELINE

    Bumps certifi from 2019.9.11 to 2022.12.7.

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    dependencies 
    opened by dependabot[bot] 1
  • Bump pillow from 8.2.0 to 9.3.0 in /NLP/UNIMO-2

    Bump pillow from 8.2.0 to 9.3.0 in /NLP/UNIMO-2

    Bumps pillow from 8.2.0 to 9.3.0.

    Release notes

    Sourced from pillow's releases.

    9.3.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.3.0 (2022-10-29)

    • Limit SAMPLESPERPIXEL to avoid runtime DOS #6700 [wiredfool]

    • Initialize libtiff buffer when saving #6699 [radarhere]

    • Inline fname2char to fix memory leak #6329 [nulano]

    • Fix memory leaks related to text features #6330 [nulano]

    • Use double quotes for version check on old CPython on Windows #6695 [hugovk]

    • Remove backup implementation of Round for Windows platforms #6693 [cgohlke]

    • Fixed set_variation_by_name offset #6445 [radarhere]

    • Fix malloc in _imagingft.c:font_setvaraxes #6690 [cgohlke]

    • Release Python GIL when converting images using matrix operations #6418 [hmaarrfk]

    • Added ExifTags enums #6630 [radarhere]

    • Do not modify previous frame when calculating delta in PNG #6683 [radarhere]

    • Added support for reading BMP images with RLE4 compression #6674 [npjg, radarhere]

    • Decode JPEG compressed BLP1 data in original mode #6678 [radarhere]

    • Added GPS TIFF tag info #6661 [radarhere]

    • Added conversion between RGB/RGBA/RGBX and LAB #6647 [radarhere]

    • Do not attempt normalization if mode is already normal #6644 [radarhere]

    ... (truncated)

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    dependencies 
    opened by dependabot[bot] 1
  • Bump pillow from 6.2.0 to 9.3.0 in /NLP/Conversational-Recommendation-BASELINE

    Bump pillow from 6.2.0 to 9.3.0 in /NLP/Conversational-Recommendation-BASELINE

    Bumps pillow from 6.2.0 to 9.3.0.

    Release notes

    Sourced from pillow's releases.

    9.3.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html

    Changes

    ... (truncated)

    Changelog

    Sourced from pillow's changelog.

    9.3.0 (2022-10-29)

    • Limit SAMPLESPERPIXEL to avoid runtime DOS #6700 [wiredfool]

    • Initialize libtiff buffer when saving #6699 [radarhere]

    • Inline fname2char to fix memory leak #6329 [nulano]

    • Fix memory leaks related to text features #6330 [nulano]

    • Use double quotes for version check on old CPython on Windows #6695 [hugovk]

    • Remove backup implementation of Round for Windows platforms #6693 [cgohlke]

    • Fixed set_variation_by_name offset #6445 [radarhere]

    • Fix malloc in _imagingft.c:font_setvaraxes #6690 [cgohlke]

    • Release Python GIL when converting images using matrix operations #6418 [hmaarrfk]

    • Added ExifTags enums #6630 [radarhere]

    • Do not modify previous frame when calculating delta in PNG #6683 [radarhere]

    • Added support for reading BMP images with RLE4 compression #6674 [npjg, radarhere]

    • Decode JPEG compressed BLP1 data in original mode #6678 [radarhere]

    • Added GPS TIFF tag info #6661 [radarhere]

    • Added conversion between RGB/RGBA/RGBX and LAB #6647 [radarhere]

    • Do not attempt normalization if mode is already normal #6644 [radarhere]

    ... (truncated)

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    opened by dependabot[bot] 1
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