Lesen Sie den tatsächlichen Autoformer-Code und zahlen Sie die vollständigen Codedaten

Erklärung des Projektvideos: Die tatsächlichen Codedaten der Autoformer-Zeitreihe können direkt ausgeführt werden_bilibili_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