能够代替resnet18的一维强化学习代码
时间: 2023-07-03 11:28:34 浏览: 87
人工智能-项目实践-迁移学习-基于resnet18的迁移学习分类网络,用于给bee和ant二分类.zip
对于一维强化学习任务,可以使用一维卷积神经网络代替ResNet18,具体实现可以参考以下代码:
```python
import torch.nn as nn
class DQN(nn.Module):
def __init__(self, input_channels, num_actions):
super(DQN, self).__init__()
self.conv1 = nn.Conv1d(input_channels, 32, kernel_size=8, stride=4)
self.conv2 = nn.Conv1d(32, 64, kernel_size=4, stride=2)
self.conv3 = nn.Conv1d(64, 64, kernel_size=3, stride=1)
self.fc1 = nn.Linear(7 * 64, 512)
self.fc2 = nn.Linear(512, num_actions)
def forward(self, x):
x = nn.functional.relu(self.conv1(x))
x = nn.functional.relu(self.conv2(x))
x = nn.functional.relu(self.conv3(x))
x = x.view(x.size(0), -1)
x = nn.functional.relu(self.fc1(x))
x = self.fc2(x)
return x
```
这里使用了三层卷积层和两层全连接层,可以根据实际任务需要进行修改。
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