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Bump paddlepaddle from 2.0.0rc1 to 2.4.0 in /docs #502

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@dependabot dependabot bot commented on behalf of github Nov 30, 2022

Bumps paddlepaddle from 2.0.0rc1 to 2.4.0.

Release notes

Sourced from paddlepaddle's releases.

PaddlePaddle 2.4.0 Release Note

2.4.0 Release Note

1. 重要更新

  • 新动态图架构正式生效:新动态图框架调大幅提升了调度性能,超90%API的调度性能提升超过50%,超50%套件模型性能提升超过5%,功能架构更加清晰,二次开发能力和体验显著增强。

  • 全面提升了飞桨的动静统一能力: 动转静功能提供了更加丰富的Python语法支持,飞桨的Python语法覆盖率达到90%,对语法转写逻辑进行了重点地优化,完备地支持了控制流语法,提供了更加流畅的一键转静态图体验;借助全新升级的静态图执行器,让动转静训练具有更优的加速能力,重点模型测试显示接近静态图最佳水平;提升了动转静的可扩展性,新增支持多函数合并导出和推理,支持用户使用PHI算子库进行二次开发和灵活部署,有效支撑语音领域U2++特色模型的自定义解码。

  • 新增稀疏计算类API: 新增55个稀疏API paddle.sparse.*,支持稀疏计算主流场景,已应用于3D点云目标检测、Sparse Transformers等任务的稀疏训练和推理部署,高稀疏度场景下相比使用DenseTensor提速105.75%,相比同类产品稀疏计算提速4.01%~58.55%;支持多种稀疏Tensor(SparseCoo 和 SparseCsr等)的计算,极致节省显存;同时保持了一致的使用体验,和稠密Tensor的API使用方式一致。

  • 大规模图神经网络GPU训练引擎: 通过SSD、内存、显存的异构层次化存储技术,突破显存瓶颈,支持超大规模图的全GPU存储和训练;实现了游走、采样、训练的全GPU一体化解决方案,相比传统的分布式CPU解决方案,相同成本的情况下训练速度提升10+倍。

  • 环境适配: 新增了适配CUDA11.7 版本的预编译安装包,新增了支持在Ubuntu 22.04及以上版本中运行。

前瞻性预告

  • 飞桨框架将在2.5版本废弃对python 3.6的支持。
  • 飞桨框架将会逐步废弃python端的paddle.fluild命名空间下的API,在2.5版本时,部分该命名空间下的API将会被直接删除。

2. 不兼容升级

  • 取消了适配CUDA10.1 版本的预编译安装包。
  • Tensor.clear_gradient(bool set_to_zero)接口不再接收kwargs传入的值,只能通过args传入set_to_zero的bool变量。
  • 为了提高显存利用效率,动态图默认仅保留前向叶子结点变量的梯度如训练中网络参数的梯度,而不再支持默认保留非叶子结点的梯度。如果需要保留特定Tensor的梯度,可以在反向执行前调用Tensor.retain_grads()接口。
  • paddle.autograd.PyLayer将不再支持输入是tuple的情况,如果输入希望是一组Tensor的情况请传入list of Tensor。

3. 训练框架(含分布式)

(1)新增API和增强API功能

  • 新增稀疏计算类API:paddle.sparse

  • 新增语音领域API: paddle.audio

    • 新增MFCC、Spectrogram、LogMelSpectrogram等特征提取API,支持GPU计算,相比CPU实现处理性能提升 15x 倍以上,可大幅提升语音模型训练GPU利用率。#45424
    • 新增窗函数、离散余弦变换等特征提取基础API,方便用户自定义语音特征提取。#45424
    • 新增语音 IO 模块,提供2种 音频I/O backend,支持6种编解码,便捷地实现语音数据的加载。 #45939
    • 新增TESS,ESC50语音分类数据集,方便用户完成经典语音分类模型。#45939
  • 新增图学习领域API: paddle.geometric

    • 图学习逐渐成为机器学习领域的关键技术,飞桨新增paddle.geometric模块提供更好的图学习建模和训练开发体验。
      • 消息传递:图学习消息传递机制是图建模的基础,因此新增7个图学习消息传递API,更方便完成进行图学习建模。其中,新增的3个消息传递融合算子可大幅减少图模型训练显存占用,稠密图场景下GCN系列模型可节省50%+显存,训练速度可提升20%+。#44848, #44580, #43174, #44970
      • 图采样:图采样是图模型训练的性能瓶颈,此次新增了高性能图采样算子,支持高并发图采样,GraphSage的采样速度可提升32倍以上,模型训练速度可提升12倍以上。#44970
  • 新增视觉领域API

    • paddle.vision新增目标检测领域算子paddle.vision.distribute_fpn_proposals(#43736), paddle.vision.generate_proposals(#43611), paddle.vision.matrix_nms(#44357), paddle.vision.prior_box和paddle.vision.box_coder(#47282)。
  • 增强API功能

    • 增加BatchNorm1D的大batch_size计算功能 #43072
  • 完善集合通信分布式训练API

... (truncated)

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Bumps [paddlepaddle](https://github.com/paddlepaddle/paddle) from 2.0.0rc1 to 2.4.0.
- [Release notes](https://github.com/paddlepaddle/paddle/releases)
- [Changelog](https://github.com/PaddlePaddle/Paddle/blob/develop/RELEASE.md)
- [Commits](PaddlePaddle/Paddle@v2.0.0-rc1...v2.4.0)

---
updated-dependencies:
- dependency-name: paddlepaddle
  dependency-type: direct:production
...

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@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Nov 30, 2022
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