From e76f5a96a3e0a5130ed00b30d827bb92f325a35f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E8=A1=8C=E5=97=94?= <yichang.zyc@alibaba-inc.com>
Date: Wed, 19 Oct 2022 17:34:59 +0800
Subject: [PATCH] fix comments

---
 modelscope/metainfo.py                     |  2 +-
 modelscope/preprocessors/multi_modal.py    |  2 ++
 modelscope/utils/multi_modal/forked_pdb.py | 17 -----------------
 tests/pipelines/test_ofa_tasks.py          |  5 +----
 tests/trainers/test_ofa_trainer.py         | 19 ++++++++++++++-----
 5 files changed, 18 insertions(+), 27 deletions(-)
 delete mode 100644 modelscope/utils/multi_modal/forked_pdb.py

diff --git a/modelscope/metainfo.py b/modelscope/metainfo.py
index 0b4291f0..c3fe5594 100644
--- a/modelscope/metainfo.py
+++ b/modelscope/metainfo.py
@@ -278,7 +278,7 @@ class Trainers(object):
 
     # multi-modal trainers
     clip_multi_modal_embedding = 'clip-multi-modal-embedding'
-    ofa_tasks = 'ofa-tasks-trainer'
+    ofa_tasks = 'ofa'
 
     # cv trainers
     image_instance_segmentation = 'image-instance-segmentation'
diff --git a/modelscope/preprocessors/multi_modal.py b/modelscope/preprocessors/multi_modal.py
index 6d06bbb9..73742c47 100644
--- a/modelscope/preprocessors/multi_modal.py
+++ b/modelscope/preprocessors/multi_modal.py
@@ -83,6 +83,8 @@ class OfaPreprocessor(Preprocessor):
         return data
 
     def _compatible_with_pretrain(self, data):
+        # 预训练的时候使用的image都是经过pil转换的，PIL save的时候一般会进行有损压缩，为了保证和预训练一致
+        # 所以增加了这个逻辑
         if 'image' in data and self.cfg.model.get('type', None) == 'ofa':
             if isinstance(data['image'], str):
                 image = load_image(data['image'])
diff --git a/modelscope/utils/multi_modal/forked_pdb.py b/modelscope/utils/multi_modal/forked_pdb.py
deleted file mode 100644
index 56107d1f..00000000
--- a/modelscope/utils/multi_modal/forked_pdb.py
+++ /dev/null
@@ -1,17 +0,0 @@
-import pdb
-import sys
-
-
-class ForkedPdb(pdb.Pdb):
-    """A Pdb subclass that may be used
-    from a forked multiprocessing child
-
-    """
-
-    def interaction(self, *args, **kwargs):
-        _stdin = sys.stdin
-        try:
-            sys.stdin = open('/dev/stdin')
-            pdb.Pdb.interaction(self, *args, **kwargs)
-        finally:
-            sys.stdin = _stdin
diff --git a/tests/pipelines/test_ofa_tasks.py b/tests/pipelines/test_ofa_tasks.py
index 104c2869..f8366508 100644
--- a/tests/pipelines/test_ofa_tasks.py
+++ b/tests/pipelines/test_ofa_tasks.py
@@ -91,11 +91,8 @@ class OfaTasksTest(unittest.TestCase, DemoCompatibilityCheck):
 
     @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_run_with_text_classification_with_model(self):
-        # model = Model.from_pretrained(
-        #     'damo/ofa_text-classification_mnli_large_en')
         model = Model.from_pretrained(
-            '/apsarapangu/disk2/yichang.zyc/ckpt/MaaS/ofa_text-classification_mnli_large_en'
-        )
+            'damo/ofa_text-classification_mnli_large_en')
         ofa_pipe = pipeline(Tasks.text_classification, model=model)
         text = 'One of our number will carry out your instructions minutely.'
         text2 = 'A member of my team will execute your orders with immense precision.'
diff --git a/tests/trainers/test_ofa_trainer.py b/tests/trainers/test_ofa_trainer.py
index c0704061..8aab3544 100644
--- a/tests/trainers/test_ofa_trainer.py
+++ b/tests/trainers/test_ofa_trainer.py
@@ -1,9 +1,12 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
+import glob
 import os
+import os.path as osp
 import shutil
 import unittest
 
-from modelscope.trainers.multi_modal.ofa import OFATrainer
+from modelscope.metainfo import Trainers
+from modelscope.trainers import build_trainer
 from modelscope.utils.test_utils import test_level
 
 
@@ -11,10 +14,16 @@ class TestOfaTrainer(unittest.TestCase):
 
     @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
     def test_trainer(self):
-        model_id = 'damo/ofa_image-caption_coco_huge_en'
-        self.trainer = OFATrainer(model_id)
-        os.makedirs(self.trainer.work_dir, exist_ok=True)
-        self.trainer.train()
+        os.environ['LOCAL_RANK'] = '0'
+        model_id = 'damo/ofa_text-classification_mnli_large_en'
+        default_args = {'model': model_id}
+        trainer = build_trainer(
+            name=Trainers.ofa_tasks, default_args=default_args)
+        os.makedirs(trainer.work_dir, exist_ok=True)
+        trainer.train()
+        assert len(
+            glob.glob(osp.join(trainer.work_dir,
+                               'best_epoch*_accuracy*.pth'))) == 2
         if os.path.exists(self.trainer.work_dir):
             shutil.rmtree(self.trainer.work_dir)