update test codes

tests/test_permutation.py

@@ -45,7 +45,7 @@ class TestPermutation(unittest.TestCase):
     def test_dry_run(self):
         n_seq = consts.n_seq
         n_templ = consts.n_templ
-        n_res = consts.n_res +13
+        n_res = consts.n_res +9
         n_extra_seq = consts.n_extra
 
         c = model_config(consts.model, train=True)
@@ -83,12 +83,12 @@ class TestPermutation(unittest.TestCase):
             # Modify asym_id, entity_id and sym_id so that it encodes 
             # 2 chains
             # #
-            asym_id = [1]*9+[2]*13+[3]*13
+            asym_id = [1]*9+[2]*9+[3]*13
             batch["asym_id"] = torch.tensor(asym_id,dtype=torch.float64)
             # batch["entity_id"] = torch.randint(0, 1, size=(n_res,))
-            batch['entity_id'] = torch.tensor([1]*9+[2]*26,dtype=torch.float64)
+            batch['entity_id'] = torch.tensor([1]*18+[2]*13,dtype=torch.float64)
             batch["sym_id"] = torch.tensor(asym_id,dtype=torch.float64)
-            batch["num_sym"] = torch.tensor([1]*9+[2]*26,dtype=torch.int64) # currently there are just 2 chains
+            batch["num_sym"] = torch.tensor([1]*18+[2]*13,dtype=torch.int64) # currently there are just 2 chains
             batch["extra_deletion_matrix"] = torch.randint(0, 2, size=(n_extra_seq, n_res))
         add_recycling_dims = lambda t: (
             t.unsqueeze(-1).expand(*t.shape, c.data.common.max_recycling_iters)