Oops, need to pass the transformer args - otherwise --use_bert withou…

…t the model name is not correctly testing the dev/test sets

stanza/utils/training/run_ner.py

@@ -48,7 +48,7 @@ def add_ner_args(parser):
     parser.add_argument('--use_bert', default=False, action="store_true", help='Use the default transformer for this language')
 
 
-def build_pretrain_args(language, dataset, charlm="default", extra_args=None, model_dir=DEFAULT_MODEL_DIR):
+def build_pretrain_args(language, dataset, charlm="default", command_args=None, extra_args=None, model_dir=DEFAULT_MODEL_DIR):
     """
     Returns one list with the args for this language & dataset's charlm and pretrained embedding
     """
@@ -61,7 +61,9 @@ def build_pretrain_args(language, dataset, charlm="default", extra_args=None, mo
         wordvec_pretrain = find_wordvec_pretrain(language, default_pretrains, ner_pretrains, dataset, model_dir=model_dir)
         wordvec_args = ['--wordvec_pretrain_file', wordvec_pretrain]
 
-    return charlm_args + wordvec_args
+    bert_args = common.choose_transformer(language, command_args, extra_args, warn=False)
+
+    return charlm_args + wordvec_args + bert_args
 
 
 # TODO: refactor?  tagger and depparse should be pretty similar
@@ -70,14 +72,13 @@ def build_model_filename(paths, short_name, command_args, extra_args):
 
     # TODO: can avoid downloading the charlm at this point, since we
     # might not even be training
-    pretrain_args = build_pretrain_args(short_language, dataset, command_args.charlm, extra_args)
-    bert_args = common.choose_transformer(short_language, command_args, extra_args, warn=False)
+    pretrain_args = build_pretrain_args(short_language, dataset, command_args.charlm, command_args, extra_args)
 
     dataset_args = DATASET_EXTRA_ARGS.get(short_name, [])
 
     train_args = ["--shorthand", short_name,
                   "--mode", "train"]
-    train_args = train_args + pretrain_args + bert_args + dataset_args + extra_args
+    train_args = train_args + pretrain_args + dataset_args + extra_args
     if command_args.save_name is not None:
         train_args.extend(["--save_name", command_args.save_name])
     if command_args.save_dir is not None:
@@ -111,7 +112,7 @@ def run_treebank(mode, paths, treebank, short_name,
         except Exception as e:
             raise FileNotFoundError(f"An exception occurred while trying to build the data for {treebank}  At least one portion of the data was missing: {missing_file}  Please correctly build these files and then try again.") from e
 
-    pretrain_args = build_pretrain_args(language, dataset, command_args.charlm, extra_args)
+    pretrain_args = build_pretrain_args(language, dataset, command_args.charlm, command_args, extra_args)
 
     if mode == Mode.TRAIN:
         # VI example arguments:
@@ -124,13 +125,12 @@ def run_treebank(mode, paths, treebank, short_name,
         #   --charlm --charlm_shorthand vi_conll17
         #   --dropout 0.6 --word_dropout 0.1 --locked_dropout 0.1 --char_dropout 0.1
         dataset_args = DATASET_EXTRA_ARGS.get(short_name, [])
-        bert_args = common.choose_transformer(language, command_args, extra_args)
 
         train_args = ['--train_file', train_file,
                       '--eval_file', dev_file,
                       '--shorthand', short_name,
                       '--mode', 'train']
-        train_args = train_args + pretrain_args + bert_args + dataset_args + extra_args
+        train_args = train_args + pretrain_args + dataset_args + extra_args
         logger.info("Running train step with args: {}".format(train_args))
         ner_tagger.main(train_args)