Enable saving prediction output (#133)

- Added argument and save by default
- Include all tags in output file for multimer preset

inference.py

@@ -241,7 +241,7 @@ def inference_multimer_model(args):
     ][1:]
     tags, seqs = lines[::2], lines[1::2]
 
-
+    output_prefix = "_and_".join(tags)
     for tag, seq in zip(tags, seqs):
         local_alignment_dir = os.path.join(alignment_dir, tag)
         if(args.use_precomputed_alignments is None):
@@ -268,7 +268,6 @@ def inference_multimer_model(args):
     feature_dict = data_processor.process_fasta(
         fasta_path=fasta_path, alignment_dir=local_alignment_dir
     )
-    # feature_dict = pickle.load(open("/home/lcmql/data/features_pdb1o5d.pkl", "rb"))
     
     processed_feature_dict = feature_processor.process_features(
         feature_dict, mode='predict', is_multimer=True,
@@ -282,6 +281,13 @@ def inference_multimer_model(args):
 
     out = result_q.get()
 
+    if args.save_prediction_result:
+        # Save the prediction result .pkl
+        prediction_result_path = os.path.join(args.output_dir,
+            f'{output_prefix}_{args.model_name}.pkl')
+        with open(prediction_result_path, 'wb') as f:
+            pickle.dump(out, f)
+
     # Toss out the recycling dimensions --- we don't need them anymore
     batch = tensor_tree_map(lambda x: np.array(x[..., -1].cpu()), batch)
     
@@ -296,7 +302,7 @@ def inference_multimer_model(args):
 
     # Save the unrelaxed PDB.
     unrelaxed_output_path = os.path.join(args.output_dir,
-                                            f'{tag}_{args.model_name}_unrelaxed.pdb')
+        f'{output_prefix}_{args.model_name}_unrelaxed.pdb')
     with open(unrelaxed_output_path, 'w') as f:
         f.write(protein.to_pdb(unrelaxed_protein))
 
@@ -312,7 +318,7 @@ def inference_multimer_model(args):
 
     # Save the relaxed PDB.
     relaxed_output_path = os.path.join(args.output_dir,
-                                        f'{tag}_{args.model_name}_relaxed.pdb')
+        f'{output_prefix}_{args.model_name}_relaxed.pdb')
     with open(relaxed_output_path, 'w') as f:
         f.write(relaxed_pdb_str)
 
@@ -500,6 +506,9 @@ if __name__ == "__main__":
                         type=str,
                         default='full_dbs',
                         choices=('reduced_dbs', 'full_dbs'))
+    parser.add_argument('--save_prediction_result',
+                        type=bool,
+                        default=True)
     parser.add_argument('--data_random_seed', type=str, default=None)
     parser.add_argument(
         "--model_preset",