updated the loss config so that the masked msa dim is 22 instead of 23

tests/test_permutation.py

@@ -63,6 +63,8 @@ class TestPermutation:
         n_extra_seq = consts.n_extra
 
         c = model_config(consts.model, train=True)
+        
+        c.loss.masked_msa.num_classes = 22 # somehow need overwrite this part in multimer loss config
         c.model.evoformer_stack.no_blocks = 4  # no need to go overboard here
         c.model.evoformer_stack.blocks_per_ckpt = None  # don't want to set up
         # deepspeed for this test
@@ -88,6 +90,15 @@ class TestPermutation:
         }
         batch['backbone_rigid_tensor'] = self.affine_vector_to_4x4(backbone_dict['backbone_affine_tensor'])
         batch['backbone_rigid_mask'] = backbone_dict['backbone_affine_mask']
+        
+        true_msa_dict ={
+            "true_msa": torch.tensor(np.random.randint(0, 21, (n_res, n_seq))),
+            "bert_mask": torch.tensor(np.random.randint(0, 2, (n_res, n_seq)).astype(
+                np.float32)
+            )
+        }
+        
+        batch.update(true_msa_dict)
 
         batch["msa_feat"] = torch.rand((n_seq, n_res, c.model.input_embedder.msa_dim))
         t_feats = random_template_feats(n_templ, n_res)