Merge remote-tracking branch 'origin/master' into ofa/finetune

modelscope/pipelines/base.py

@@ -433,6 +433,8 @@ def collate_fn(data, device):
     if isinstance(data, dict) or isinstance(data, Mapping):
         return type(data)({k: collate_fn(v, device) for k, v in data.items()})
     elif isinstance(data, (tuple, list)):
+        if 0 == len(data):
+            return torch.Tensor([])
         if isinstance(data[0], (int, float)):
             return default_collate(data).to(device)
         else:

modelscope/pipelines/cv/body_3d_keypoints_pipeline.py

@@ -143,6 +143,13 @@ class Body3DKeypointsPipeline(Pipeline):
         max_frame = self.keypoint_model_3d.cfg.model.INPUT.MAX_FRAME  # max video frame number to be predicted 3D joints
         for i, frame in enumerate(video_frames):
             kps_2d = self.human_body_2d_kps_detector(frame)
+            if [] == kps_2d.get('boxes'):
+                res = {
+                    'success': False,
+                    'msg': f'fail to detect person at image frame {i}'
+                }
+                return res
+
             box = kps_2d['boxes'][
                 0]  # box: [[[x1, y1], [x2, y2]]], N human boxes per frame, [0] represent using first detected bbox
             pose = kps_2d['keypoints'][0]  # keypoints: [15, 2]
@@ -180,7 +187,15 @@ class Body3DKeypointsPipeline(Pipeline):
         return res
 
     def postprocess(self, input: Dict[str, Any], **kwargs) -> Dict[str, Any]:
-        res = {OutputKeys.KEYPOINTS: [], OutputKeys.TIMESTAMPS: []}
+        output_video_path = kwargs.get('output_video', None)
+        if output_video_path is None:
+            output_video_path = tempfile.NamedTemporaryFile(suffix='.mp4').name
+
+        res = {
+            OutputKeys.KEYPOINTS: [],
+            OutputKeys.TIMESTAMPS: [],
+            OutputKeys.OUTPUT_VIDEO: output_video_path
+        }
 
         if not input['success']:
             pass
@@ -189,10 +204,6 @@ class Body3DKeypointsPipeline(Pipeline):
             pred_3d_pose = poses.data.cpu().numpy()[
                 0]  # [frame_num, joint_num, joint_dim]
 
-            output_video_path = kwargs.get('output_video', None)
-            if output_video_path is None:
-                output_video_path = tempfile.NamedTemporaryFile(
-                    suffix='.mp4').name
             if 'render' in self.keypoint_model_3d.cfg.keys():
                 self.render_prediction(pred_3d_pose, output_video_path)
                 res[OutputKeys.OUTPUT_VIDEO] = output_video_path

modelscope/trainers/hooks/logger/text_logger_hook.py

@@ -51,7 +51,7 @@ class TextLoggerHook(LoggerHook):
         if self.out_dir is None:
             self.out_dir = trainer.work_dir
 
-        if not osp.exists(self.out_dir):
+        if not osp.exists(self.out_dir) and is_master():
             os.makedirs(self.out_dir)
 
         trainer.logger.info('Text logs will be saved to {}'.format(

tests/pipelines/test_text_generation.py

@@ -15,12 +15,17 @@ from modelscope.utils.test_utils import test_level
 class TextGenerationTest(unittest.TestCase, DemoCompatibilityCheck):
 
     def setUp(self) -> None:
-        self.palm_model_id_zh = 'damo/nlp_palm2.0_text-generation_chinese-base'
+        self.palm_model_id_zh_base = 'damo/nlp_palm2.0_text-generation_chinese-base'
+        self.palm_model_id_zh_large = 'damo/nlp_palm2.0_text-generation_chinese-large'
+        self.palm_model_id_zh_commodity = 'damo/nlp_palm2.0_text-generation_commodity_chinese-base'
+        self.palm_model_id_zh_weather = 'damo/nlp_palm2.0_text-generation_weather_chinese-base'
         self.palm_model_id_en = 'damo/nlp_palm2.0_text-generation_english-base'
         self.palm_input_zh = """
         本文总结了十个可穿戴产品的设计原则，而这些原则，同样也是笔者认为是这个行业最吸引人的地方：
         1.为人们解决重复性问题；2.从人开始，而不是从机器开始；3.要引起注意，但不要刻意；4.提升用户能力，而不是取代
         """
+        self.palm_input_commodity = '垃圾桶，双层，可拆卸，加高，加高双层，把手，垃圾桶，内附，万向轮'
+        self.palm_input_weather = "今日天气类型='浮尘'&空气质量等级='重度污染'&紫外线强度指数='中等'"
         self.palm_input_en = """
         The Director of Public Prosecutions who let off Lord Janner over alleged child sex abuse started
         her career at a legal chambers when the disgraced Labour peer was a top QC there . Alison Saunders ,
@@ -51,8 +56,8 @@ class TextGenerationTest(unittest.TestCase, DemoCompatibilityCheck):
         print(pipeline_ins(input))
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
-    def test_palm_zh_with_model_name(self):
-        self.run_pipeline_with_model_id(self.palm_model_id_zh,
+    def test_palm_zh_base_with_model_name(self):
+        self.run_pipeline_with_model_id(self.palm_model_id_zh_base,
                                         self.palm_input_zh)
 
     @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
@@ -71,10 +76,40 @@ class TextGenerationTest(unittest.TestCase, DemoCompatibilityCheck):
                                         self.gpt3_input)
 
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
-    def test_palm_zh_with_model_instance(self):
-        self.run_pipeline_with_model_instance(self.palm_model_id_zh,
+    def test_palm_zh_large_with_model_name(self):
+        self.run_pipeline_with_model_id(self.palm_model_id_zh_large,
+                                        self.palm_input_zh)
+
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
+    def test_palm_zh_commodity_with_model_name(self):
+        self.run_pipeline_with_model_id(self.palm_model_id_zh_commodity,
+                                        self.palm_input_commodity)
+
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
+    def test_palm_zh_weather_with_model_name(self):
+        self.run_pipeline_with_model_id(self.palm_model_id_zh_weather,
+                                        self.palm_input_weather)
+
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
+    def test_palm_zh_base_with_model_instance(self):
+        self.run_pipeline_with_model_instance(self.palm_model_id_zh_base,
                                               self.palm_input_zh)
 
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
+    def test_palm_zh_large_with_model_instance(self):
+        self.run_pipeline_with_model_instance(self.palm_model_id_zh_large,
+                                              self.palm_input_zh)
+
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
+    def test_palm_zh_commodity_with_model_instance(self):
+        self.run_pipeline_with_model_instance(self.palm_model_id_zh_commodity,
+                                              self.palm_input_commodity)
+
+    @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
+    def test_palm_zh_weather_with_model_instance(self):
+        self.run_pipeline_with_model_instance(self.palm_model_id_zh_weather,
+                                              self.palm_input_weather)
+
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_palm_en_with_model_instance(self):
         self.run_pipeline_with_model_instance(self.palm_model_id_en,
@@ -92,8 +127,9 @@ class TextGenerationTest(unittest.TestCase, DemoCompatibilityCheck):
 
     @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
     def test_run_palm(self):
-        for model_id, input in ((self.palm_model_id_zh, self.palm_input_zh),
-                                (self.palm_model_id_en, self.palm_input_en)):
+        for model_id, input in ((self.palm_model_id_zh_base,
+                                 self.palm_input_zh), (self.palm_model_id_en,
+                                                       self.palm_input_en)):
             cache_path = snapshot_download(model_id)
             model = PalmForTextGeneration.from_pretrained(cache_path)
             preprocessor = TextGenerationPreprocessor(