我想对时间序列数据进行注意力机制,请发给我代码
时间: 2024-05-14 12:19:46 浏览: 20
好的,下面是一个基于PyTorch的时间序列注意力机制的代码示例:
```python
import torch
import torch.nn as nn
class TimeAttention(nn.Module):
def __init__(self, hidden_size):
super(TimeAttention, self).__init__()
self.query = nn.Linear(hidden_size, hidden_size)
self.key = nn.Linear(hidden_size, hidden_size)
def forward(self, hidden_states):
# hidden_states: (batch_size, sequence_length, hidden_size)
query = self.query(hidden_states) # (batch_size, sequence_length, hidden_size)
key = self.key(hidden_states) # (batch_size, sequence_length, hidden_size)
attn_score = torch.matmul(query, key.transpose(1, 2)) # (batch_size, sequence_length, sequence_length)
attn_score = nn.Softmax(dim=-1)(attn_score) # (batch_size, sequence_length, sequence_length)
context_vector = torch.matmul(attn_score, hidden_states) # (batch_size, sequence_length, hidden_size)
return context_vector
```
此代码可以作为一个模块用于你的时间序列模型中。你可以将该模块嵌入到你的模型中,以便在模型中使用一个注意力机制来处理时间序列数据。
相关推荐
![rar](https://img-home.csdnimg.cn/images/20210720083606.png)
![zip](https://img-home.csdnimg.cn/images/20210720083736.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)
![](https://csdnimg.cn/download_wenku/file_type_ask_c1.png)