fix pipline yaml

paddlex/pipelines/OCR.yaml

@@ -9,5 +9,4 @@ Pipeline:
   det_model: PP-OCRv4_mobile_det
   rec_model: PP-OCRv4_mobile_rec
   batch_size: 1
-  device: "gpu"
-######################################## Support ########################################
+  device: "gpu:0"

paddlex/pipelines/anomaly_detection.yaml

@@ -8,4 +8,4 @@ Global:
 Pipeline:
   model: STFPM
   batch_size: 1
-  device: "gpu"
+  device: "gpu:0"

paddlex/pipelines/instance_segmentation.yaml

@@ -8,7 +8,7 @@ Global:
 Pipeline:
   model: Mask-RT-DETR-S
   batch_size: 1
-  device: "gpu"
+  device: "gpu:0"
 ######################################## Support ########################################
 NOTE:
   device: 

paddlex/pipelines/multi_label_image_classification.yaml

@@ -0,0 +1,11 @@
+Global:
+  pipeline_name: multi_label_image_classification
+  input: https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_image_classification_001.jpg
+  
+######################################## Setting ########################################
+# Please select the model from bellow `Support`
+
+Pipeline:
+  model: PP-LCNet_x1_0_ML
+  batch_size: 1
+  device: "gpu:0"

paddlex/pipelines/object_detection.yaml

@@ -8,7 +8,7 @@ Global:
 Pipeline:
   model: PicoDet-S
   batch_size: 1
-  device: "gpu"
+  device: "gpu:0"
 ######################################## Support ########################################
 NOTE:
   device: 

paddlex/pipelines/semantic_segmentation.yaml

@@ -1,6 +1,6 @@
 Global:
   pipeline_name: semantic_segmentation
-  input: https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/general_image_classification_001.jpg
+  input: https://paddle-model-ecology.bj.bcebos.com/paddlex/PaddleX3.0/application/semantic_segmentation/makassaridn-road_demo.png
   
 ######################################## Setting ########################################
 # Please select the model from bellow `Support`
@@ -8,7 +8,7 @@ Global:
 Pipeline:
   model: PP-LiteSeg-T
   batch_size: 1
-  device: "gpu"
+  device: "gpu:0"
 ######################################## Support ########################################
 NOTE:
   device: 

paddlex/pipelines/small_object_detection.yaml

@@ -8,4 +8,4 @@ Global:
 Pipeline:
   model: PP-YOLOE_plus_SOD-L
   batch_size: 1
-  device: "gpu"
+  device: "gpu:0"

paddlex/pipelines/table_recognition.yaml

@@ -11,6 +11,6 @@ Pipeline:
   text_det_model: PP-OCRv4_mobile_det
   text_rec_model: PP-OCRv4_mobile_rec
   batch_size: 1
-  device: "gpu"
+  device: "gpu:0"
 
 ######################################## Support ########################################

paddlex/pipelines/ts_ad.yaml

@@ -0,0 +1,11 @@
+Global:
+  pipeline_name: ts_ad
+  input: https://paddle-model-ecology.bj.bcebos.com/paddlex/ts/demo_ts/ts_ad.csv
+  
+######################################## Setting ########################################
+# Please select the model from bellow `Support`
+
+Pipeline:
+  model: DLinear_ad
+  batch_size: 1
+  device: "gpu:0"

paddlex/pipelines/ts_cls.yaml

@@ -0,0 +1,11 @@
+Global:
+  pipeline_name: ts_cls
+  input: https://paddle-model-ecology.bj.bcebos.com/paddlex/ts/demo_ts/ts_cls.csv
+  
+######################################## Setting ########################################
+# Please select the model from bellow `Support`
+
+Pipeline:
+  model: TimesNet_cls
+  batch_size: 1
+  device: "gpu:0"

paddlex/pipelines/ts_fc.yaml

@@ -0,0 +1,11 @@
+Global:
+  pipeline_name: ts_fc
+  input: https://paddle-model-ecology.bj.bcebos.com/paddlex/ts/demo_ts/ts_fc.csv
+  
+######################################## Setting ########################################
+# Please select the model from bellow `Support`
+
+Pipeline:
+  model: DLinear
+  batch_size: 1
+  device: "gpu:0"

paddlex/repo_apis/PaddleClas_api/cls/runner.py

@@ -198,12 +198,14 @@ def _extract_eval_metrics(stdout: str) -> dict:
         r"\[Eval\]\[Epoch 0\]\[Avg\].*MultiLabelMAP\(integral\): (_dp)".replace(
             "_dp", _DP
         ),
+        r"\[Eval\]\[Epoch 0\]\[Avg\].*evalres:\ ma: (_dp)".replace("_dp", _DP),
     ]
     keys = [
         ["val.top1"],
         ["val.top1", "val.top5"],
         ["recall1", "recall5", "mAP"],
         ["MultiLabelMAP"],
+        ["evalres: ma"],
     ]
 
     metric_dict = dict()