深度学习实战矩阵的相关内容

文章 2023-12-19 来自：开发者社区

PyTorch深度学习基础之Tensor对象及其应用的讲解及实战（附源码简单易懂包括分段映射矩阵乘法随机数等等）

觉得有帮助请点赞关注收藏有问题可评论区留言~~~Tensor对象是一个维度任意的矩阵，但是一个Tensor中所有元素的数据类型必须一致。torch包含的数据类型和普遍编程语言的数据类型类似，包含浮点型，有符号整型和无符号整形，这些类型既可以定义在CPU上，也可以定义在GPU上。在使用Tensor数据类型时，可以通过dtype属性指定它的数据类型，device指定它的设备（CPU或者GPU）1：....

文章 2023-08-04 来自：开发者社区

[深度学习实战]基于PyTorch的深度学习实战(中)[线性回归、numpy矩阵的保存、模型的保存和导入、卷积层、池化层]（二）

5.2 Conv1d conv1d 是一维卷积，它和 conv2d 的区别在于只对宽度进行卷积，对高度不卷积。5.2.1 函数定义torch.nn.functional.conv1d(input, weight, bias=None, stride=1, padding=0, dilation=5.2.2 参数说明 input：输入的Tensor数据，格式为 (batc....

文章 2023-08-04 来自：开发者社区

[深度学习实战]基于PyTorch的深度学习实战(中)[线性回归、numpy矩阵的保存、模型的保存和导入、卷积层、池化层]（一）

一、前言本想着一篇博文直接写完基于PyTorch的深度学习实战，可写着写着发现字数都上万了。考虑到读者可能花了大力气对这么一篇博文看到失去了对PyTorch神经网络的耐心，同时也为了我个人对文章排版的整理，还是分成了分卷阅读。这里贴一下上篇博文：[深度学习实战]基于PyTorch的深度学习实战(上)[变量、求导、损失函数、优化器]二、线性回归线性回归也叫....

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