PyTorch实现ResNet50、ResNet101和ResNet152示例

PyTorch实现实现ResNet50、、ResNet101和和ResNet152示例示例

今天小编就为大家分享一篇PyTorch实现ResNet50、ResNet101和ResNet152示例，具有很好的参考价值，希望对大家

有所帮助。一起跟随小编过来看看吧

PyTorch: https://github.com/shanglianlm0525/PyTorch-Networks

import torch

import torch.nn as nn

import torchvision

import numpy as np

nn.BatchNorm2d(places),

nn.ReLU(inplace=True),

nn.MaxPool2d(kernel_size=3, stride=2, padding=1)

)

class Bottleneck(nn.Module):

def __init__(self,in_places,places, stride=1,downsampling=False, expansion = 4):

super(Bottleneck,self).__init__()

self.expansion = expansion

self.downsampling = downsampling

self.bottleneck = nn.Sequential(

nn.Conv2d(in_channels=places, out_channels=places*self.expansion, kernel_size=1, stride=1, bias=False),

nn.BatchNorm2d(places*self.expansion),

)

if self.downsampling:

self.downsample = nn.Sequential(

nn.Conv2d(in_channels=in_places, out_channels=places*self.expansion, kernel_size=1, stride=stride, bias=False),

nn.BatchNorm2d(places*self.expansion)

)

self.relu = nn.ReLU(inplace=True)

def forward(self, x):