seq_length args

common_dataset.py

@@ -152,8 +152,8 @@ class Common_Dataset(Dataset):
 
 def load_data(path_train, path_val, path_test, batch_size, length, pad=False, convert=False, vocab = 'unmod'):
     print('Loading data')
-    data_train = pd.read_pickle(path_train)
     data_val = pd.read_pickle(path_val)
+    data_train = pd.read_pickle(path_train)
     data_test = pd.read_pickle(path_test)
     train = Common_Dataset(data_train, length, pad, convert, vocab)
     test = Common_Dataset(data_val, length, pad, convert, vocab)

model_custom.py

 import math
 import torch.nn as nn
 import torch
-from tape import TAPETokenizer
 from tape.models.modeling_bert import ProteinBertModel
 
 class PermuteLayer(nn.Module):