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Apache-2.0

项目简介

完全基于Python实现的深度学习框架,用于学习与交流,未来将用于个人深度学习项目开发。 我们将进行一系列的更新,以使其更加完善。(动态图执行)

项目结构

  • core:核心模块,包括神经网络、优化器、损失函数等
  • datasets:数据集模块,包括MNIST、CIFAR-10等数据集的加载与处理
  • models:模型模块,包括LeNet、ResNet等经典模型的实现
  • utils:工具模块,包括数据预处理、可视化等功能
  • examples:示例模块,包括MNIST分类、CIFAR-10分类等示例代码
  • tests:测试模块,包括单元测试和集成测试
  • docs:文档模块,包括API文档和教程文档
  • quantification 专门为量化预测开发的优化包

开发日志

请以最新的开发日志为准

  • tests
    • day01 当前测试包已经废弃 -- 2024-4-2
  • all 取消部分函数的类型声明,核心输入输出参见下文日志
    • day02 重构整个函数变量传递,输入的是Variable类型,但是输出是np.array类型(在forward函数当中,在call当中进行转换)
    • day02 底层算法修改为支持np.array矩阵类型的计算,Variable将支持高纬度计算
    • day02 底层backward函数,将dfs修改为bfs(加上排序的层次dfs),完成正确的梯度计算顺序,满足偏导法则
    • day02 优化Variable,支持魔法操作,求取梯度
    • day02 逐步完成Variable的__add__、submuldivpownegabsmatmulraddrsubrmulrdivrpow、__rmatmul__魔法操作
    • day02 完成网络模型可视化(输出拓扑图)
      • day02 下可看到输出拓扑结构图
    • day03 完成线性回归测试,框架已经可以正常运行,尝试进入神经网络组件编写
  • all
    • 当前2024-4-3 可用版本为 v0.13-latest
    • v0.14 版本将更新高阶导数实现,test 包下的day03的optimzer_step 废弃。
    • day03 函数重新修改为支持np.array类型,并且支持高纬度计算(矩阵偏导(雅可比行列式进行一阶计算),导导实现二阶)
    • day03 基于cupy开始进行gpu的支持,当前本地开发cuda版本为V10.1,此模块安装较为麻烦。版本更新为 v0.15
    • day03 完成线性回归测试,支持矩阵高阶导数运算的前提下。day03 liner_reg
    • day03 增加线性回归example
  • all
  • 版本更新为0.2.0(0.20)版本,所有代码全部重构,框架暂停更新--!
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