main custom on ISA data

model_custom.py

@@ -101,7 +101,6 @@ class Model_Common_Transformer(nn.Module):
                                                 d_model=self.embedding_dim)
 
     def forward(self, seq, charge):
-        print(seq.shape)
         meta_ohe = torch.nn.functional.one_hot(charge - 1, self.charge_max).float()
         seq_emb = torch.nn.functional.one_hot(seq, self.nb_aa).float()
         emb = self.pos_embedding(self.emb(seq_emb))