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).__i
本文深入探讨Autoformer模型在时间序列预测中的应用,通过提供完整的代码和数据,帮助读者理解并实战该模型。项目视频详细讲解了Autoformer的运作原理,并附带哔哩哔哩平台上的演示链接,同时提供了优快云下载源代码和数据的地址。
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