update rdrop

modelscope/trainers/multi_modal/ofa/ofa_trainer.py

@@ -131,7 +131,7 @@ class OFATrainer(EpochBasedTrainer):
         model.train()
         # model_outputs = model.forward(inputs)
         loss, sample_size, logging_output = self.criterion(model, inputs)
-        train_outputs = {'loss': loss / 100}
+        train_outputs = {'loss': loss}
         # add model output info to log
         if 'log_vars' not in train_outputs:
             default_keys_pattern = ['loss']

modelscope/trainers/multi_modal/ofa/ofa_trainer_utils.py

@@ -144,7 +144,7 @@ class AdjustLabelSmoothedCrossEntropyCriterion(_Loss):
         sample_size = (
             sample['target'].size(0) if self.sentence_avg else ntokens)
         logging_output = {
-            'loss': loss.data / 100,
+            'loss': loss.data,
             'nll_loss': nll_loss.data,
             'ntokens': sample['ntokens'],
             'nsentences': sample['nsentences'],

tests/trainers/test_ofa_trainer.py

@@ -1,7 +1,5 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
-import glob
 import os
-import os.path as osp
 import shutil
 import unittest
 
@@ -98,8 +96,9 @@ class TestOfaTrainer(unittest.TestCase):
         trainer = build_trainer(name=Trainers.ofa, default_args=args)
         trainer.train()
 
-        self.assertIn(ModelFile.TORCH_MODEL_BIN_FILE,
-                      os.listdir(os.path.join(WORKSPACE, 'output')))
+        self.assertIn(
+            ModelFile.TORCH_MODEL_BIN_FILE,
+            os.listdir(os.path.join(WORKSPACE, ModelFile.TRAIN_OUTPUT_DIR)))
         shutil.rmtree(WORKSPACE)