DoubleConv函数
时间: 2023-12-28 10:06:08 浏览: 27
DoubleConv函数是一个用于构建UNet网络中的双卷积层的类。它继承自nn.Module类,并实现了两个卷积层、批归一化和ReLU激活函数。具体实现如下:
```python
class DoubleConv(nn.Module):
"""(convolution => \[BN\] => ReLU) * 2"""
def __init__(self, in_channels, out_channels, mid_channels=None):
super().__init__()
if not mid_channels:
mid_channels = out_channels
self.double_conv = nn.Sequential(
nn.Conv2d(in_channels, mid_channels, kernel_size=3, padding=1),
nn.BatchNorm2d(mid_channels),
nn.ReLU(inplace=True),
nn.Conv2d(mid_channels, out_channels, kernel_size=3, padding=1),
nn.BatchNorm2d(out_channels),
nn.ReLU(inplace=True)
)
```
在构造函数中,它接受输入通道数`in_channels`、输出通道数`out_channels`和中间通道数`mid_channels`作为参数。如果没有指定中间通道数,则默认与输出通道数相同。双卷积层的具体实现是通过`nn.Sequential`来组合两个卷积层、批归一化和ReLU激活函数。第一个卷积层将输入通道数转换为中间通道数,第二个卷积层将中间通道数转换为输出通道数。在每个卷积层之后都有一个批归一化层和ReLU激活函数。
#### 引用[.reference_title]
- *1* *2* *3* [window 学习pytorch unet代码之self.inc = DoubleConv(n_channels, 64)](https://blog.csdn.net/guyuezunting/article/details/107299582)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control_2,239^v3^insert_chatgpt"}} ] [.reference_item]
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