resnet101 网络结构代码
时间: 2023-07-09 13:51:04 浏览: 148
以下是ResNet101网络结构的代码,使用PyTorch实现:
```python
import torch.nn as nn
class Bottleneck(nn.Module):
expansion = 4
def __init__(self, in_planes, planes, stride=1):
super(Bottleneck, self).__init__()
self.conv1 = nn.Conv2d(in_planes, planes, kernel_size=1, bias=False)
self.bn1 = nn.BatchNorm2d(planes)
self.conv2 = nn.Conv2d(planes, planes, kernel_size=3, stride=stride, padding=1, bias=False)
self.bn2 = nn.BatchNorm2d(planes)
self.conv3 = nn.Conv2d(planes, planes * self.expansion, kernel_size=1, bias=False)
self.bn3 = nn.BatchNorm2d(planes * self.expansion)
self.shortcut = nn.Sequential()
if stride != 1 or in_planes != planes * self.expansion:
self.shortcut = nn.Sequential(
nn.Conv2d(in_planes, planes * self.expansion, kernel_size=1, stride=stride, bias=False),
nn.BatchNorm2d(planes * self.expansion)
)
def forward(self, x):
out = nn.ReLU()(self.bn1(self.conv1(x)))
out = nn.ReLU()(self.bn2(self.conv2(out)))
out = self.bn3(self.conv3(out))
out += self.shortcut(x)
out = nn.ReLU()(out)
return out
class ResNet(nn.Module):
def __init__(self, block, num_blocks, num_classes=1000):
super(ResNet, self).__init__()
self.in_planes = 64
self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=2, padding=3, bias=False)
self.bn1 = nn.BatchNorm2d(64)
self.layer1 = self._make_layer(block, 64, num_blocks[0], stride=1)
self.layer2 = self._make_layer(block, 128, num_blocks[1], stride=2)
self.layer3 = self._make_layer(block, 256, num_blocks[2], stride=2)
self.layer4 = self._make_layer(block, 512, num_blocks[3], stride=2)
self.linear = nn.Linear(512 * block.expansion, num_classes)
def _make_layer(self, block, planes, num_blocks, stride):
strides = [stride] + [1] * (num_blocks - 1)
layers = []
for stride in strides:
layers.append(block(self.in_planes, planes, stride))
self.in_planes = planes * block.expansion
return nn.Sequential(*layers)
def forward(self, x):
out = nn.ReLU()(self.bn1(self.conv1(x)))
out = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)(out)
out = self.layer1(out)
out = self.layer2(out)
out = self.layer3(out)
out = self.layer4(out)
out = nn.AvgPool2d(kernel_size=7, stride=1)(out)
out = out.view(out.size(0), -1)
out = self.linear(out)
return out
def ResNet101():
return ResNet(Bottleneck, [3, 4, 23, 3])
```
这个代码实现了ResNet101的网络结构。其中Bottleneck类定义了ResNet中的一个基本块,ResNet类定义了整个网络结构,包括多个Bottleneck块和全连接层。最后的ResNet101函数用于创建ResNet101网络。
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