fix bug

Author: MAZiqing

exp/exp_main.py

@@ -1,6 +1,6 @@
 from data_provider.data_factory import data_provider
 from exp.exp_basic import Exp_Basic
-from models import Informer, FEDformer, Transformer, Logformer, Reformer,Transformer_sin,Autoformer_sin
+from models import FEDformer, Informer, Autoformer, Transformer # Logformer, Reformer,Transformer_sin,Autoformer_sin
 # from models.reformer_pytorch.reformer_pytorch import Reformer
 from utils.tools import EarlyStopping, adjust_learning_rate, visual
 from utils.metrics import metric
@@ -27,13 +27,14 @@ def __init__(self, args):
 
     def _build_model(self):
         model_dict = {
-            'Autoformer': FEDformer,
+            'FEDformer': FEDformer,
+            'Autoformer': Autoformer,
             'Transformer': Transformer,
             'Informer': Informer,
-            'Reformer': Reformer,
-            'Logformer': Logformer,
-            'Transformer_sin':Transformer_sin,
-            'Autoformer_sin':Autoformer_sin,
+            # 'Reformer': Reformer,
+            # 'Logformer': Logformer,
+            # 'Transformer_sin':Transformer_sin,
+            # 'Autoformer_sin':Autoformer_sin,
         }
         model = model_dict[self.args.model].Model(self.args).float()
 

run.py

@@ -47,8 +47,8 @@
 parser.add_argument('--seq_len', type=int, default=96, help='input sequence length')
 parser.add_argument('--label_len', type=int, default=48, help='start token length')
 parser.add_argument('--pred_len', type=int, default=96, help='prediction sequence length')
-parser.add_argument('--cross_activation', type=str, default='tanh',
-                    help='mwt cross atention activation function tanh or softmax')
+# parser.add_argument('--cross_activation', type=str, default='tanh',
+                    # help='mwt cross atention activation function tanh or softmax')
 
 # model define
 parser.add_argument('--enc_in', type=int, default=7, help='encoder input size')