Introduction to AlexNet

We mentioned AlexNet in the earlier section that introduced Caffe. AlexNet was a seminal network structure because of the large number of layers it employed for the first time, and for showing how such a deep neural network could be trained in a reasonable time by utilizing GPUs.

Figure 4.1 shows the network structure of AlexNet generated by Caffe's network visualization tool, draw_net.py . This tool uses the GraphViz library to render the graph layout:

Figure 4.1: Network structure of AlexNet using the GraphViz layout

In this visualization, layers are drawn as rectangles and data tensors between layers are drawn as elongated octagons. For example, the first layer rectangle after the input layer depicts a convolution layer named conv1. It uses kernels of size , a stride of 4, and a padding of 0.

Examining the AlexNet structure in Figure 4.1 we can...