[cherry-pick] fix unittest

configs/datasets/voc.yml

@@ -3,19 +3,19 @@ map_type: 11point
 num_classes: 20
 
 TrainDataset:
-  !VOCDataSet
-    dataset_dir: dataset/voc
-    anno_path: trainval.txt
-    label_list: label_list.txt
-    data_fields: ['image', 'gt_bbox', 'gt_class', 'difficult']
+  name: VOCDataSet
+  dataset_dir: dataset/voc
+  anno_path: trainval.txt
+  label_list: label_list.txt
+  data_fields: ['image', 'gt_bbox', 'gt_class', 'difficult']
 
 EvalDataset:
-  !VOCDataSet
-    dataset_dir: dataset/voc
-    anno_path: test.txt
-    label_list: label_list.txt
-    data_fields: ['image', 'gt_bbox', 'gt_class', 'difficult']
+  name: VOCDataSet
+  dataset_dir: dataset/voc
+  anno_path: test.txt
+  label_list: label_list.txt
+  data_fields: ['image', 'gt_bbox', 'gt_class', 'difficult']
 
 TestDataset:
-  !ImageFolder
-    anno_path: dataset/voc/label_list.txt
+  name: ImageFolder
+  anno_path: dataset/voc/label_list.txt

configs/runtime.yml

@@ -1,6 +1,7 @@
 use_gpu: true
 use_xpu: false
 use_mlu: false
+use_npu: false
 log_iter: 20
 save_dir: output
 snapshot_epoch: 1

ppdet/core/workspace.py

@@ -67,6 +67,15 @@ def __getattr__(self, key):
             return self[key]
         raise AttributeError("object has no attribute '{}'".format(key))
 
+    def __setattr__(self, key, value):
+        self[key] = value
+
+    def copy(self):
+        new_dict = AttrDict()
+        for k, v in self.items():
+            new_dict.update({k: v})
+        return new_dict
+
 
 global_config = AttrDict()
 
@@ -280,4 +289,4 @@ def create(cls_or_name, **kwargs):
     # prevent modification of global config values of reference types
     # (e.g., list, dict) from within the created module instances
     #kwargs = copy.deepcopy(kwargs)
-    return cls(**cls_kwargs)
+    return cls(**cls_kwargs)

ppdet/engine/trainer.py

@@ -62,7 +62,7 @@
 
 class Trainer(object):
     def __init__(self, cfg, mode='train'):
-        self.cfg = cfg
+        self.cfg = cfg.copy()
         assert mode.lower() in ['train', 'eval', 'test'], \
                 "mode should be 'train', 'eval' or 'test'"
         self.mode = mode.lower()
@@ -99,12 +99,12 @@ def __init__(self, cfg, mode='train'):
                 self.dataset, cfg.worker_num)
 
         if cfg.architecture == 'JDE' and self.mode == 'train':
-            cfg['JDEEmbeddingHead'][
+            self.cfg['JDEEmbeddingHead'][
                 'num_identities'] = self.dataset.num_identities_dict[0]
             # JDE only support single class MOT now.
 
         if cfg.architecture == 'FairMOT' and self.mode == 'train':
-            cfg['FairMOTEmbeddingHead'][
+            self.cfg['FairMOTEmbeddingHead'][
                 'num_identities_dict'] = self.dataset.num_identities_dict
             # FairMOT support single class and multi-class MOT now.
 
@@ -149,7 +149,7 @@ def __init__(self, cfg, mode='train'):
                 reader_name = '{}Reader'.format(self.mode.capitalize())
                 # If metric is VOC, need to be set collate_batch=False.
                 if cfg.metric == 'VOC':
-                    cfg[reader_name]['collate_batch'] = False
+                    self.cfg[reader_name]['collate_batch'] = False
                 self.loader = create(reader_name)(self.dataset, cfg.worker_num,
                                                   self._eval_batch_sampler)
         # TestDataset build after user set images, skip loader creation here