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项目视频讲解:Autoformer时间序列实战完整代码数据 可直接运行_哔哩哔哩_bilibili
- import torch
- import torch.nn as nn
- import torch.nn.functional as F
- from layers.Embed import DataEmbedding, DataEmbedding_wo_pos
- from layers.AutoCorrelation import AutoCorrelation, AutoCorrelationLayer
- from layers.Autoformer_EncDec import Encoder, Decoder, EncoderLayer, DecoderLayer, my_Layernorm, series_decomp
- import math
- import numpy as np
-
-
- class Model(nn.Module):
- """
- Autoformer is the first method to achieve the series-wise connection,
- with inherent O(LlogL) complexity
- """
- def __init__(self, configs):
- super(Model, self).__init__()
- self.seq_len = configs.seq_len
- self.label_len = configs.label_len
- self.pred_len = configs.pred_len
- self.output_attention = c
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