Caffe官网 Tutorial: Nets, Layers, and Blobs caffe模型分解分析
来源:互联网 发布:苹果vip解析软件 编辑:程序博客网 时间:2024/05/16 10:06
http://caffe.berkeleyvision.org/tutorial/net_layer_blob.html 官网地址
总概况:
caffe 计算模型:一层层的框架,从bottom 到 top 从输入数据到loss, 数据和梯度流通过 forward and backward passes 流动。
层的连接信息blobs 。
solver 用于模型配置和优化。
一、
Blob storage and communication
For example, in a 4D blob, the value at index (n, k, h, w) is physically located at index ((n * K + k) * H + h) * W + w.
因为 n 从0 开始,所以要加上 k 等
- Number / N is the batch size of the data. Batch processing achieves better throughput for communication and device processing. For an ImageNet training batch of 256 images N = 256.
- Channel / K is the feature dimension e.g. for RGB images K = 3.
二
Blob 存着 data 和 diff Implementation Details
cpu 和 gpu 之间可以同步
const Dtype* cpu_data() const;Dtype* mutable_cpu_data()
If you want to check out when a Blob will copy data, here is an illustrative example:
// Assuming that data are on the CPU initially, and we have a blob.const Dtype* foo;Dtype* bar;foo = blob.gpu_data(); // data copied cpu->gpu.foo = blob.cpu_data(); // no data copied since both have up-to-date contents.bar = blob.mutable_gpu_data(); // no data copied.// ... some operations ...bar = blob.mutable_gpu_data(); // no data copied when we are still on GPU.foo = blob.cpu_data(); // data copied gpu->cpu, since the gpu side has modified the datafoo = blob.gpu_data(); // no data copied since both have up-to-date contentsbar = blob.mutable_cpu_data(); // still no data copied.bar = blob.mutable_gpu_data(); // data copied cpu->gpu.bar = blob.mutable_cpu_data(); // data copied gpu->cpu.
0 0
- Caffe官网 Tutorial: Nets, Layers, and Blobs caffe模型分解分析
- Caffe学习:Blobs, Layers, and Nets
- 浅读Caffe: Blobs, Layers, and Nets
- Caffe学习:Blobs, Layers, and Nets
- caffe教程笔记《Blobs, Layers, and Nets》
- Caffe学习:Blobs, Layers, and Nets
- Blobs, Layers, and Nets: anatomy of a Caffe model
- Caffe 初学拾遗(三) Blobs, Layers, and Nets
- Caffe学习2--Blobs,Layers与Nets
- Caffe中的Blobs,Layers和Nets
- caffe 相关--Blobs, Layers, and Nets: anatomy of a Caffe model
- Caffe学习笔记2-Caffe的三级结构(Blobs,Layers,Nets)
- Caffe学习笔记2-Caffe的三级结构(Blobs,Layers,Nets)
- Caffe学习笔记——Caffe的三级结构(Blobs,Layers,Nets)
- Caffe学习笔记——Caffe的三级结构(Blobs,Layers,Nets)
- Caffe学习笔记3--caffe的三级结构:Blobs, Layers,Nets
- caffe学习笔记tutorial:Layers
- caffe blobs 共享内存分析
- NMAP 端口扫描工具下载 + 安装
- asp.net中后台c#数组与前台js数组交互
- 选择排序
- java实现排序算法之堆排序
- 公钥私钥加密解密理解
- Caffe官网 Tutorial: Nets, Layers, and Blobs caffe模型分解分析
- Linux常用命令大全 (非常有用)
- Python的WSGI
- CocoaPods安装及使用
- 多校第九场Arithmetic Sequence题解
- Java 程序优化:字符串操作、基本运算方法等优化策略
- 直接插入排序
- Android开发之ExpandableListView扩展
- mybatis中的trim