| 103 | |
| 104 | |
| 105 | class DataEmbedding(nn.Module): |
| 106 | def __init__(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1): |
| 107 | super(DataEmbedding, self).__init__() |
| 108 | |
| 109 | self.value_embedding = TokenEmbedding(c_in=c_in, d_model=d_model) |
| 110 | self.position_embedding = PositionalEmbedding(d_model=d_model) |
| 111 | self.temporal_embedding = TemporalEmbedding(d_model=d_model, embed_type=embed_type, |
| 112 | freq=freq) if embed_type != 'timeF' else TimeFeatureEmbedding( |
| 113 | d_model=d_model, embed_type=embed_type, freq=freq) |
| 114 | self.dropout = nn.Dropout(p=dropout) |
| 115 | |
| 116 | def forward(self, x, x_mark): |
| 117 | if x_mark==None: |
| 118 | x = self.value_embedding(x) |
| 119 | return self.dropout(x) |
| 120 | |
| 121 | x = self.value_embedding(x) + self.temporal_embedding(x_mark) + self.position_embedding(x) |
| 122 | return self.dropout(x) |
| 123 | |
| 124 | |
| 125 | class DataEmbedding_wo_pos(nn.Module): |