如何输出dense层特征
时间: 2023-11-08 20:50:01 浏览: 79
要输出Dense层的特征,可以通过在DenseBlock的forward方法中添加一个输出语句来实现。在每个卷积块的前向传播过程中,将块的输出保存在一个列表中。最后,返回这个列表作为DenseBlock的输出。以下是一个示例代码:
```python
class DenseBlock(nn.Module):
def __init__(self, num_convs, input_channels, num_channels):
super(DenseBlock, self).__init__()
layer = \[\]
for i in range(num_convs):
layer.append(conv_block(num_channels * i + input_channels, num_channels))
self.net = nn.Sequential(*layer)
def forward(self, X):
features = \[\] # 保存每个卷积块的输出
for blk in self.net:
Y = blk(X)
features.append(Y)
X = torch.cat((X, Y), dim=1)
return features
```
通过调用DenseBlock的forward方法,可以得到每个卷积块的输出特征。例如:
```python
blk = DenseBlock(2, 3, 10)
X = torch.randn(4, 3, 8, 8)
features = blk(X)
```
features将是一个列表,其中包含了每个卷积块的输出特征。
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