（刘二大人）PyTorch深度学习实践-卷积网络（Advance）

1. 1x1的卷积核的作用

1. 在width和height不变的基础上改变通道的数量
2. 减少计算量

2. GoogLeNet中Inception Module的实现 

 2.1 Inception块的代码实现

import torch
import torch.nn.functional as F
 
class InceptinA(torch.nn.Module):
    def __init__(self,channels):
        super(InceptinA, self).__init__()
        self.branch_pool = torch.nn.Conv2d(channels,24,kernel_size=1)
        self.branch1x1 = torch.nn.Conv2d(channels,16,kernel_size=1)
        self.branch5x5_1 = torch.nn.Conv2d(channels,16,kernel_size=1)
        self.branch5x5_2 = torch.nn.Conv2d(16,24,kernel_size=5,padding=2)#使用了5x5的卷积核，为保证w和h不变，使用padding=2
        self.branch3x3_1 = torch.nn.Conv2d(channels,