| 91 | |
| 92 | |
| 93 | class TimeFeatureEmbedding(nn.Module): |
| 94 | def __init__(self, d_model, embed_type='timeF', freq='h'): |
| 95 | super(TimeFeatureEmbedding, self).__init__() |
| 96 | |
| 97 | freq_map = {'h': 4, 't': 5, 's': 6, 'm': 1, 'a': 1, 'w': 2, 'd': 3, 'b': 3} |
| 98 | d_inp = freq_map[freq] |
| 99 | self.embed = nn.Linear(d_inp, d_model, bias=False) |
| 100 | |
| 101 | def forward(self, x): |
| 102 | return self.embed(x) |
| 103 | |
| 104 | |
| 105 | class DataEmbedding(nn.Module): |