(self, data_path, data_name, predict_length)

(self, data_path, data_name, predict_length, batch_size)

(self, data_path, data_name, predict_length)

(self, data_path, data_name, predict_length, batch_size)

(self, data_path, data_name, predict_length)

(self)

(self, ignore_zero)

(self)

(self, d_model, d_inner, n_head, d_k, d_v, dropout=0.1, normalize_before=True, use_tvm=False, q_k_mask=None, k

(self, d_model, d_inner, n_head, d_k, d_v, dropout=0.1, normalize_before=True)

(self, c_in, window_size)

(self, d_model, window_size, d_inner)

(self, d_model, window_size, d_inner)

(self, d_model, window_size, d_inner)

(self, d_model, window_size, d_inner)

(self, dim, num_types)

(self, opt)

(self, n_head, d_model, d_k, d_v, dropout, normalize_before, q_k_mask, k_q_mask)

(self, d_in, d_hid, dropout=0.1, normalize_before=True)

(self, temperature, attn_dropout=0.2)

(self, opt)

(self, d_model, max_len=5000)

(self, c_in, d_model)

(self, c_in, d_model)

(self, d_model)

(self, c_in, d_model, temporal_size, seq_num, dropout=0.1)

(self, cov_size, num_seq, d_model, input_size, device)

(self, opt)

(self, opt)

(self, channels)

(self, kernel_size, stride)

(self, kernel_size)

(self, attention, d_model, d_ff=None, moving_avg=25, dropout=0.1, activation="relu")

(self, self_attention, cross_attention, d_model, c_out, d_ff=None, moving_avg=25, dropout=0.1

(self, layers, norm_layer=None, projection=None)

(self, d_model, max_len=5000)

(self, c_in, d_model)

(self, c_in, d_model)

(self, d_model, embed_type='fixed', freq='h')

(self, d_model, embed_type='timeF', freq='h')

(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)

(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)

(self, c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)

(self, mask_flag=True, factor=5, scale=None, attention_dropout=0.1, output_attention=False)

(self, attention, d_model, n_heads, d_keys=None, d_values=None)

(self, c_in)

(self, attention, d_model, d_ff=None, dropout=0.1, activation="relu")

(self, self_attention, cross_attention, d_model, d_ff=None, dropout=0.1, activation="relu")

(self, layers, norm_layer=None, projection=None)

(self, correlation, d_model, n_heads, d_keys=None, d_values=None)

(self, args)

(self, args)

(self, args)

(self, root_path, flag='train', size=None, features='S', data_path='ETTh1.csv',

(self, root_path, flag='train', size=None, features='S', data_path='ETTm1.csv',

(self, root_path, flag='train', size=None, features='S', data_path='ETTh1.csv',

(self, root_path, flag='pred', size=None, features='S', data_path='ETTh1.csv',

(self, configs)

(self, configs)

(self,func,args=())

(self, configs)

(self, configs)

(self, configs)

(self, kernel_size, stride)

(self, kernel_size)

(self, configs)

(self, configs)

(self, configs)

(self)

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(seq,pred_len,bt,i)

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(seq,seq_len,pred_len,bt,i)

(self)

(self)

(season,seq,pred_len,bt,i)

(self, input, weights)

(self)