Fix even more undefined references

run_pretrained_openfold.py

@@ -71,11 +71,10 @@ def precompute_alignments(tags, seqs, alignment_dir, args):
                 bfd_database_path=args.bfd_database_path,
                 uniclust30_database_path=args.uniclust30_database_path,
                 pdb70_database_path=args.pdb70_database_path,
-                use_small_bfd=use_small_bfd,
                 no_cpus=args.cpus,
             )
             alignment_runner.run(
-                fasta_path, local_alignment_dir
+                tmp_fasta_path, local_alignment_dir
             )
 
         # Remove temporary FASTA file
@@ -133,7 +132,7 @@ def prep_output(out, batch, feature_dict, feature_processor, args):
     remark = ', '.join([
         f"no_recycling={no_recycling}",
         f"max_templates={feature_processor.config.predict.max_templates}",
-        f"config_preset={args.model_name}",
+        f"config_preset={args.config_preset}",
     ])
 
     # For multi-chain FASTAs
@@ -167,16 +166,16 @@ def main(args):
     os.makedirs(args.output_dir, exist_ok=True)
 
     # Prep the model
-    config = model_config(args.model_name)
+    config = model_config(args.config_preset)
     
-    logger.info(f"Using config preset {args.model_name}...")
+    logger.info(f"Using config preset {args.config_preset}...")
 
     model = AlphaFold(config)
     model = model.eval()
 
     if(args.jax_param_path):
         import_jax_weights_(
-            model, args.jax_param_path, version=args.model_name
+            model, args.jax_param_path, version=args.config_preset
         )
         logger.info(
             f"Successfully loaded JAX parameters at {args.jax_param_path}..."
@@ -234,8 +233,6 @@ def main(args):
         obsolete_pdbs_path=args.obsolete_pdbs_path
     )
 
-    use_small_bfd=(args.bfd_database_path is None)
-
     data_processor = data_pipeline.DataPipeline(
         template_featurizer=template_featurizer,
     )
@@ -271,7 +268,7 @@ def main(args):
         # assert len(tags) == len(set(tags)), "All FASTA tags must be unique"
         tag = '-'.join(tags)
 
-        output_name = f'{tag}_{args.model_name}'
+        output_name = f'{tag}_{args.config_preset}'
         if(args.output_postfix is not None):
             output_name = f'{output_name}_{args.output_postfix}'
 
@@ -322,9 +319,9 @@ def main(args):
             out, batch, feature_dict, feature_processor, args
         )
 
-        output_name = f'{tag}_{args.model_name}'
+        output_name = f'{tag}_{args.config_preset}'
         if(args.output_postfix is not None):
-            output_name = f'{output_name}_{args.output_postfix}_{tag_postfix}'
+            output_name = f'{output_name}_{args.output_postfix}'
 
         # Save the unrelaxed PDB.
         unrelaxed_output_path = os.path.join(
@@ -394,7 +391,7 @@ if __name__ == "__main__":
              device name is accepted (e.g. "cpu", "cuda:0")"""
     )
     parser.add_argument(
-        "--model_name", type=str, default="model_1",
+        "--config_preset", type=str, default="model_1",
         help="""Name of a model config. Choose one of model_{1-5} or 
              model_{1-5}_ptm, as defined on the AlphaFold GitHub."""
     )
@@ -441,7 +438,7 @@ if __name__ == "__main__":
     if(args.jax_param_path is None and args.openfold_checkpoint_path is None):
         args.jax_param_path = os.path.join(
             "openfold", "resources", "params", 
-            "params_" + args.model_name + ".npz"
+            "params_" + args.config_preset + ".npz"
         )
 
     if(args.model_device == "cpu" and torch.cuda.is_available()):