diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/.gitignore b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..26d33521af10bcc7fd8cea344038eaaeb78d0ef5
--- /dev/null
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/.gitignore
@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/YOLOv5_ID1719_for_TensorFlow2.X.iml b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/YOLOv5_ID1719_for_TensorFlow2.X.iml
new file mode 100644
index 0000000000000000000000000000000000000000..8e5446ac9594d6e198c2a2923123566d13b94bf9
--- /dev/null
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/YOLOv5_ID1719_for_TensorFlow2.X.iml
@@ -0,0 +1,14 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/venv" />
+    </content>
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="PyDocumentationSettings">
+    <option name="format" value="PLAIN" />
+    <option name="myDocStringFormat" value="Plain" />
+  </component>
+</module>
\ No newline at end of file
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/inspectionProfiles/profiles_settings.xml b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000000000000000000000000000000000000..105ce2da2d6447d11dfe32bfb846c3d5b199fc99
--- /dev/null
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>
\ No newline at end of file
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/misc.xml b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/misc.xml
new file mode 100644
index 0000000000000000000000000000000000000000..c456a360d0a3da01f06efa38811b6106fd900e56
--- /dev/null
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/misc.xml
@@ -0,0 +1,4 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (YOLOv5_ID1719_for_TensorFlow2.X)" project-jdk-type="Python SDK" />
+</project>
\ No newline at end of file
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/modules.xml b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/modules.xml
new file mode 100644
index 0000000000000000000000000000000000000000..ee76a2b335f986f7d0460c5b6524094fc9804def
--- /dev/null
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/.idea/modules.xml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/YOLOv5_ID1719_for_TensorFlow2.X.iml" filepath="$PROJECT_DIR$/.idea/YOLOv5_ID1719_for_TensorFlow2.X.iml" />
+    </modules>
+  </component>
+</project>
\ No newline at end of file
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/core/dataset.py b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/core/dataset.py
index e7f0ad5784f820e1cfdab7f8106d5094341be8d4..c8348d839403e115a8ed22766a18f3af4a274acd 100644
--- a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/core/dataset.py
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/core/dataset.py
@@ -63,7 +63,7 @@ class Dataset(object):
         self.anchor_per_scale = cfg.YOLO.ANCHOR_PER_SCALE
         self.max_bbox_per_scale = 450
 
-        self.annotations = self.load_annotations()
+        self.annotations = self.load_annotations(FLAGS)
         self.num_samples = len(self.annotations)
         self.num_batchs = int(np.ceil(self.num_samples / self.batch_size))
         self.batch_count = 0
@@ -71,7 +71,7 @@ class Dataset(object):
 
         self._data_buff = dict()
 
-    def load_annotations(self):
+    def load_annotations(self,FLAGS):
         with open(self.annot_path, "r") as f:
             txt = f.readlines()
             if self.dataset_type == "converted_coco":
@@ -106,6 +106,12 @@ class Dataset(object):
                         annotations.append(image_path + string)
 
         np.random.shuffle(annotations)
+
+        # shard
+        if FLAGS.rank_size > 1:
+            len_annotations = len(annotations)
+            annotations = annotations[int(len_annotations//int(FLAGS.rank_size))*FLAGS.rank:int(len_annotations//int(FLAGS.rank_size))*(FLAGS.rank+1)]
+
         return annotations
 
     def __iter__(self):
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/set_ranktable.py b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/set_ranktable.py
new file mode 100644
index 0000000000000000000000000000000000000000..641b0b8b5157989ca002a150c68fb418075a7b51
--- /dev/null
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/set_ranktable.py
@@ -0,0 +1,1733 @@
+import argparse
+parser = argparse.ArgumentParser()
+parser.add_argument('-n', '--npu_nums', type=int, default='2', help='nums of npu')
+parser.add_argument('-c', '--conf_path', type=str, default='./', help='the path of server_info')
+FLAGS = parser.parse_args()
+
+import json
+import os
+server = []
+server_conf = []
+server_list = ["0", "1", "2", "3", "4", "5", "6", "7"]
+if os.path.isdir(FLAGS.conf_path):
+	for f in os.listdir(FLAGS.conf_path):
+		if (f.split("_")[-1]).split(".")[0] in server_list and (f.split("_")[-1]).split(".")[1] == 'info' and f.split("_")[0] == 'server':
+			server_conf.append(f)
+			
+
+
+
+
+
+rank_address = []
+for i in range(FLAGS.npu_nums):
+	for x in server_conf:
+		if (x.split("_")[-1]).split(".")[0] == str(i):
+			server.append(x.split("_")[1])
+			l = FLAGS.conf_path + "/" + x
+			with open(l, "r") as a:
+				s = a.readlines()
+				for s_ in s:
+					if 'address_0' in s_:
+						rank_address.append(s_.split("=")[-1][:-1])
+				for s_ in s:
+					if 'address_1' in s_:
+						rank_address.append(s_.split("=")[-1][:-1])
+				for s_ in s:
+					if 'address_2' in s_:
+						rank_address.append(s_.split("=")[-1][:-1])
+				for s_ in s:
+					if 'address_3' in s_:
+						rank_address.append(s_.split("=")[-1][:-1])
+				for s_ in s:
+					if 'address_4' in s_:
+						rank_address.append(s_.split("=")[-1][:-1])
+				for s_ in s:
+					if 'address_5' in s_:
+						rank_address.append(s_.split("=")[-1][:-1])
+				for s_ in s:
+					if 'address_6' in s_:
+						rank_address.append(s_.split("=")[-1][:-1])
+				for s_ in s:
+					if 'address_7' in s_:
+						rank_address.append(s_.split("=")[-1][:-1])
+			
+if FLAGS.npu_nums == 1:
+	rank = {
+		"server_count":"1",
+		"server_list":[
+			{
+				"server_id":server[0],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[0],
+						"rank_id":"0"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[1],
+						"rank_id":"1"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[2],
+						"rank_id":"2"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[3],
+						"rank_id":"3"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[4],
+						"rank_id":"4"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[5],
+						"rank_id":"5"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[6],
+						"rank_id":"6"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[7],
+						"rank_id":"7"
+					}
+				]}],
+		"status":"completed",
+		"version":"1.0"
+	}
+elif FLAGS.npu_nums == 2:
+	rank = {
+		"server_count":"2",
+		"server_list":[
+			{
+				"server_id":server[0],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[0],
+						"rank_id":"0"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[1],
+						"rank_id":"1"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[2],
+						"rank_id":"2"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[3],
+						"rank_id":"3"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[4],
+						"rank_id":"4"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[5],
+						"rank_id":"5"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[6],
+						"rank_id":"6"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[7],
+						"rank_id":"7"
+					}
+				]},
+				
+				
+				{
+				"server_id":server[1],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[8],
+						"rank_id":"8"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[9],
+						"rank_id":"9"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[10],
+						"rank_id":"10"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[11],
+						"rank_id":"11"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[12],
+						"rank_id":"12"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[13],
+						"rank_id":"13"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[14],
+						"rank_id":"14"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[15],
+						"rank_id":"15"
+					}
+				]}
+				],
+		
+		"status":"completed",
+		"version":"1.0"
+	}
+	
+	
+elif FLAGS.npu_nums == 3:
+	rank = {
+		"server_count":"3",
+		"server_list":[
+			{
+				"server_id":server[0],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[0],
+						"rank_id":"0"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[1],
+						"rank_id":"1"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[2],
+						"rank_id":"2"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[3],
+						"rank_id":"3"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[4],
+						"rank_id":"4"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[5],
+						"rank_id":"5"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[6],
+						"rank_id":"6"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[7],
+						"rank_id":"7"
+					}
+				]},
+				
+				
+				{
+				"server_id":server[1],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[8],
+						"rank_id":"8"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[9],
+						"rank_id":"9"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[10],
+						"rank_id":"10"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[11],
+						"rank_id":"11"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[12],
+						"rank_id":"12"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[13],
+						"rank_id":"13"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[14],
+						"rank_id":"14"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[15],
+						"rank_id":"15"
+					}
+				]},
+				
+				{
+				"server_id":server[2],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[16],
+						"rank_id":"16"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[17],
+						"rank_id":"17"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[18],
+						"rank_id":"18"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[19],
+						"rank_id":"19"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[20],
+						"rank_id":"20"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[21],
+						"rank_id":"21"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[22],
+						"rank_id":"22"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[23],
+						"rank_id":"23"
+					}
+				]}
+				],
+		"status":"completed",
+		"version":"1.0"
+	}
+elif FLAGS.npu_nums == 4:
+	rank = {
+		"server_count":"4",
+		"server_list":[
+			{
+				"server_id":server[0],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[0],
+						"rank_id":"0"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[1],
+						"rank_id":"1"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[2],
+						"rank_id":"2"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[3],
+						"rank_id":"3"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[4],
+						"rank_id":"4"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[5],
+						"rank_id":"5"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[6],
+						"rank_id":"6"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[7],
+						"rank_id":"7"
+					}
+				]},
+				
+				
+				{
+				"server_id":server[1],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[8],
+						"rank_id":"8"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[9],
+						"rank_id":"9"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[10],
+						"rank_id":"10"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[11],
+						"rank_id":"11"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[12],
+						"rank_id":"12"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[13],
+						"rank_id":"13"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[14],
+						"rank_id":"14"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[15],
+						"rank_id":"15"
+					}
+				]},
+				{
+				"server_id":server[2],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[16],
+						"rank_id":"16"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[17],
+						"rank_id":"17"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[18],
+						"rank_id":"18"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[19],
+						"rank_id":"19"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[20],
+						"rank_id":"20"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[21],
+						"rank_id":"21"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[22],
+						"rank_id":"22"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[23],
+						"rank_id":"23"
+					}
+				]},
+				{
+				"server_id":server[3],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[24],
+						"rank_id":"24"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[25],
+						"rank_id":"25"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[26],
+						"rank_id":"26"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[27],
+						"rank_id":"27"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[28],
+						"rank_id":"28"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[29],
+						"rank_id":"29"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[30],
+						"rank_id":"30"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[31],
+						"rank_id":"31"
+					}
+				]}
+				],
+		"status":"completed",
+		"version":"1.0"
+	}
+elif FLAGS.npu_nums == 5:
+	rank = {
+		"server_count":"5",
+		"server_list":[
+			{
+				"server_id":server[0],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[0],
+						"rank_id":"0"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[1],
+						"rank_id":"1"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[2],
+						"rank_id":"2"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[3],
+						"rank_id":"3"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[4],
+						"rank_id":"4"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[5],
+						"rank_id":"5"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[6],
+						"rank_id":"6"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[7],
+						"rank_id":"7"
+					}
+				]},
+				
+				
+				{
+				"server_id":server[1],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[8],
+						"rank_id":"8"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[9],
+						"rank_id":"9"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[10],
+						"rank_id":"10"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[11],
+						"rank_id":"11"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[12],
+						"rank_id":"12"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[13],
+						"rank_id":"13"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[14],
+						"rank_id":"14"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[15],
+						"rank_id":"15"
+					}
+				]},
+				{
+				"server_id":server[2],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[16],
+						"rank_id":"16"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[17],
+						"rank_id":"17"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[18],
+						"rank_id":"18"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[19],
+						"rank_id":"19"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[20],
+						"rank_id":"20"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[21],
+						"rank_id":"21"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[22],
+						"rank_id":"22"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[23],
+						"rank_id":"23"
+					}
+				]},
+				{
+				"server_id":server[3],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[24],
+						"rank_id":"24"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[25],
+						"rank_id":"25"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[26],
+						"rank_id":"26"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[27],
+						"rank_id":"27"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[28],
+						"rank_id":"28"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[29],
+						"rank_id":"29"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[30],
+						"rank_id":"30"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[31],
+						"rank_id":"31"
+					}
+				]},
+				{
+				"server_id":server[4],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[32],
+						"rank_id":"32"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[33],
+						"rank_id":"33"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[34],
+						"rank_id":"34"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[35],
+						"rank_id":"35"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[36],
+						"rank_id":"36"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[37],
+						"rank_id":"37"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[38],
+						"rank_id":"38"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[39],
+						"rank_id":"39"
+					}
+				]}
+				],
+		"status":"completed",
+		"version":"1.0"
+	}
+
+
+
+elif FLAGS.npu_nums == 6:
+	rank = {
+		"server_count":"6",
+		"server_list":[
+			{
+				"server_id":server[0],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[0],
+						"rank_id":"0"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[1],
+						"rank_id":"1"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[2],
+						"rank_id":"2"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[3],
+						"rank_id":"3"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[4],
+						"rank_id":"4"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[5],
+						"rank_id":"5"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[6],
+						"rank_id":"6"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[7],
+						"rank_id":"7"
+					}
+				]},
+				
+				
+				{
+				"server_id":server[1],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[8],
+						"rank_id":"8"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[9],
+						"rank_id":"9"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[10],
+						"rank_id":"10"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[11],
+						"rank_id":"11"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[12],
+						"rank_id":"12"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[13],
+						"rank_id":"13"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[14],
+						"rank_id":"14"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[15],
+						"rank_id":"15"
+					}
+				]},
+				{
+				"server_id":server[2],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[16],
+						"rank_id":"16"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[17],
+						"rank_id":"17"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[18],
+						"rank_id":"18"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[19],
+						"rank_id":"19"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[20],
+						"rank_id":"20"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[21],
+						"rank_id":"21"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[22],
+						"rank_id":"22"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[23],
+						"rank_id":"23"
+					}
+				]},
+				{
+				"server_id":server[3],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[24],
+						"rank_id":"24"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[25],
+						"rank_id":"25"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[26],
+						"rank_id":"26"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[27],
+						"rank_id":"27"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[28],
+						"rank_id":"28"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[29],
+						"rank_id":"29"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[30],
+						"rank_id":"30"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[31],
+						"rank_id":"31"
+					}
+				]},
+				{
+				"server_id":server[4],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[32],
+						"rank_id":"32"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[33],
+						"rank_id":"33"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[34],
+						"rank_id":"34"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[35],
+						"rank_id":"35"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[36],
+						"rank_id":"36"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[37],
+						"rank_id":"37"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[38],
+						"rank_id":"38"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[39],
+						"rank_id":"39"
+					}
+				]},
+				{
+				"server_id":server[5],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[40],
+						"rank_id":"40"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[41],
+						"rank_id":"41"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[42],
+						"rank_id":"42"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[43],
+						"rank_id":"43"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[44],
+						"rank_id":"44"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[45],
+						"rank_id":"45"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[46],
+						"rank_id":"46"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[47],
+						"rank_id":"47"
+					}
+				]}
+				],
+		"status":"completed",
+		"version":"1.0"
+	}
+	
+	
+elif FLAGS.npu_nums == 7:
+	rank = {
+		"server_count":"7",
+		"server_list":[
+			{
+				"server_id":server[0],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[0],
+						"rank_id":"0"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[1],
+						"rank_id":"1"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[2],
+						"rank_id":"2"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[3],
+						"rank_id":"3"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[4],
+						"rank_id":"4"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[5],
+						"rank_id":"5"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[6],
+						"rank_id":"6"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[7],
+						"rank_id":"7"
+					}
+				]},
+				
+				
+				{
+				"server_id":server[1],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[8],
+						"rank_id":"8"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[9],
+						"rank_id":"9"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[10],
+						"rank_id":"10"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[11],
+						"rank_id":"11"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[12],
+						"rank_id":"12"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[13],
+						"rank_id":"13"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[14],
+						"rank_id":"14"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[15],
+						"rank_id":"15"
+					}
+				]},
+				{
+				"server_id":server[2],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[16],
+						"rank_id":"16"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[17],
+						"rank_id":"17"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[18],
+						"rank_id":"18"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[19],
+						"rank_id":"19"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[20],
+						"rank_id":"20"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[21],
+						"rank_id":"21"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[22],
+						"rank_id":"22"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[23],
+						"rank_id":"23"
+					}
+				]},
+				{
+				"server_id":server[3],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[24],
+						"rank_id":"24"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[25],
+						"rank_id":"25"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[26],
+						"rank_id":"26"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[27],
+						"rank_id":"27"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[28],
+						"rank_id":"28"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[29],
+						"rank_id":"29"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[30],
+						"rank_id":"30"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[31],
+						"rank_id":"31"
+					}
+				]},
+				{
+				"server_id":server[4],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[32],
+						"rank_id":"32"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[33],
+						"rank_id":"33"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[34],
+						"rank_id":"34"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[35],
+						"rank_id":"35"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[36],
+						"rank_id":"36"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[37],
+						"rank_id":"37"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[38],
+						"rank_id":"38"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[39],
+						"rank_id":"39"
+					}
+				]},
+				{
+				"server_id":server[5],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[40],
+						"rank_id":"40"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[41],
+						"rank_id":"41"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[42],
+						"rank_id":"42"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[43],
+						"rank_id":"43"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[44],
+						"rank_id":"44"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[45],
+						"rank_id":"45"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[46],
+						"rank_id":"46"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[47],
+						"rank_id":"47"
+					}
+				]},
+				{
+				"server_id":server[6],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[48],
+						"rank_id":"48"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[49],
+						"rank_id":"49"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[50],
+						"rank_id":"50"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[51],
+						"rank_id":"51"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[52],
+						"rank_id":"52"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[53],
+						"rank_id":"53"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[54],
+						"rank_id":"54"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[55],
+						"rank_id":"55"
+					}
+				]}
+				],
+		"status":"completed",
+		"version":"1.0"
+	}
+	
+	
+	
+	
+elif FLAGS.npu_nums == 8:
+	rank = {
+		"server_count":"8",
+		"server_list":[
+			{
+				"server_id":server[0],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[0],
+						"rank_id":"0"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[1],
+						"rank_id":"1"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[2],
+						"rank_id":"2"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[3],
+						"rank_id":"3"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[4],
+						"rank_id":"4"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[5],
+						"rank_id":"5"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[6],
+						"rank_id":"6"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[7],
+						"rank_id":"7"
+					}
+				]},
+				
+				
+				{
+				"server_id":server[1],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[8],
+						"rank_id":"8"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[9],
+						"rank_id":"9"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[10],
+						"rank_id":"10"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[11],
+						"rank_id":"11"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[12],
+						"rank_id":"12"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[13],
+						"rank_id":"13"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[14],
+						"rank_id":"14"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[15],
+						"rank_id":"15"
+					}
+				]},
+				{
+				"server_id":server[2],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[16],
+						"rank_id":"16"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[17],
+						"rank_id":"17"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[18],
+						"rank_id":"18"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[19],
+						"rank_id":"19"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[20],
+						"rank_id":"20"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[21],
+						"rank_id":"21"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[22],
+						"rank_id":"22"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[23],
+						"rank_id":"23"
+					}
+				]},
+				{
+				"server_id":server[3],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[24],
+						"rank_id":"24"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[25],
+						"rank_id":"25"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[26],
+						"rank_id":"26"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[27],
+						"rank_id":"27"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[28],
+						"rank_id":"28"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[29],
+						"rank_id":"29"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[30],
+						"rank_id":"30"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[31],
+						"rank_id":"31"
+					}
+				]},
+				{
+				"server_id":server[4],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[32],
+						"rank_id":"32"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[33],
+						"rank_id":"33"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[34],
+						"rank_id":"34"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[35],
+						"rank_id":"35"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[36],
+						"rank_id":"36"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[37],
+						"rank_id":"37"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[38],
+						"rank_id":"38"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[39],
+						"rank_id":"39"
+					}
+				]},
+				{
+				"server_id":server[5],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[40],
+						"rank_id":"40"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[41],
+						"rank_id":"41"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[42],
+						"rank_id":"42"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[43],
+						"rank_id":"43"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[44],
+						"rank_id":"44"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[45],
+						"rank_id":"45"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[46],
+						"rank_id":"46"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[47],
+						"rank_id":"47"
+					}
+				]},
+				{
+				"server_id":server[6],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[48],
+						"rank_id":"48"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[49],
+						"rank_id":"49"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[50],
+						"rank_id":"50"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[51],
+						"rank_id":"51"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[52],
+						"rank_id":"52"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[53],
+						"rank_id":"53"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[54],
+						"rank_id":"54"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[55],
+						"rank_id":"55"
+					}
+				]},
+				{
+				"server_id":server[7],
+				"device":[
+					{
+						"device_id":"0",
+						"device_ip":rank_address[56],
+						"rank_id":"56"
+					},
+					{
+						"device_id":"1",
+						"device_ip":rank_address[57],
+						"rank_id":"57"
+					},
+					{
+						"device_id":"2",
+						"device_ip":rank_address[58],
+						"rank_id":"58"
+					},
+					{
+						"device_id":"3",
+						"device_ip":rank_address[59],
+						"rank_id":"59"
+					},
+					{
+						"device_id":"4",
+						"device_ip":rank_address[60],
+						"rank_id":"60"
+					},
+					{
+						"device_id":"5",
+						"device_ip":rank_address[61],
+						"rank_id":"61"
+					},
+					{
+						"device_id":"6",
+						"device_ip":rank_address[62],
+						"rank_id":"62"
+					},
+					{
+						"device_id":"7",
+						"device_ip":rank_address[63],
+						"rank_id":"63"
+					}
+				]}
+				],
+		"status":"completed",
+		"version":"1.0"
+	}
+
+
+with open('rank_table.json','w') as f:
+    json.dump(rank,f)
+
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_16p.sh b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_16p.sh
new file mode 100644
index 0000000000000000000000000000000000000000..d2221c8d32cc1cd04290bed70be4c27198c4d7a2
--- /dev/null
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_16p.sh
@@ -0,0 +1,225 @@
+#!/bin/bash
+
+#当前路径,不需要修改
+cur_path=`pwd`
+
+export PYTHONWARNINGS='ignore:semaphore_tracker:UserWarning'
+
+# 帮助信息，不需要修改
+if [[ $1 == --help || $1 == -h ]];then
+    echo"usage:./train_performance_1p.sh <args>"
+    echo " "
+    echo "parameter explain:
+    --precision_mode         precision mode(allow_fp32_to_fp16/force_fp16/must_keep_origin_dtype/allow_mix_precision)
+    -h/--help		         show help message
+    "
+    exit 1
+fi
+
+#参数校验，不需要修改
+for para in $*
+do
+    if [[ $para == --precision_mode* ]];then
+        precision_mode=`echo ${para#*=}`
+    elif [[ $para == --over_dump* ]];then
+        over_dump=`echo ${para#*=}`
+        over_dump_path=${cur_path}/output/overflow_dump
+        mkdir -p ${over_dump_path}
+    elif [[ $para == --data_dump_flag* ]];then
+        data_dump_flag=`echo ${para#*=}`
+        data_dump_path=${cur_path}/output/data_dump
+        mkdir -p ${data_dump_path}
+    elif [[ $para == --data_dump_step* ]];then
+        data_dump_step=`echo ${para#*=}`
+    elif [[ $para == --profiling* ]];then
+        profiling=`echo ${para#*=}`
+        profiling_dump_path=${cur_path}/output/profiling
+        mkdir -p ${profiling_dump_path}
+    elif [[ $para == --autotune* ]];then
+        autotune=`echo ${para#*=}`
+        mv $install_path/fwkacllib/data/rl/Ascend910/custom $install_path/fwkacllib/data/rl/Ascend910/custom_bak
+        mv $install_path/fwkacllib/data/tiling/Ascend910/custom $install_path/fwkacllib/data/tiling/Ascend910/custom_bak
+        autotune_dump_path=${cur_path}/output/autotune_dump
+        mkdir -p ${autotune_dump_path}/GA
+        mkdir -p ${autotune_dump_path}/rl
+        cp -rf $install_path/fwkacllib/data/tiling/Ascend910/custom ${autotune_dump_path}/GA/
+        cp -rf $install_path/fwkacllib/data/rl/Ascend910/custom ${autotune_dump_path}/RL/
+    elif [[ $para == --data_path* ]];then
+        data_path=`echo ${para#*=}`
+    elif [[ $para == --bind_core* ]];then
+        bind_core=`echo ${para#*=}`
+        name_bind="_bindcore"
+    elif [[ $para == --server_index* ]];then
+        server_index=`echo ${para#*=}`
+    elif [[ $para == --conf_path* ]];then
+        conf_path=`echo ${para#*=}`
+    fi
+done
+
+#export ASCEND_SLOG_PRINT_TO_STDOUT=1
+export RANK_SIZE=16
+export JOB_ID=10087
+rank_size=8
+nohup python3 $cur_path/set_ranktable.py --npu_nums=$((RANK_SIZE/rank_size)) --conf_path=$conf_path
+export RANK_TABLE_FILE=${cur_path}/rank_table.json
+export HCCL_CONNECT_TIMEOUT=600
+RANK_ID_START=0
+RANK_SIZE=16
+# 数据集路径,保持为空,不需要修改
+data_path="/npu/traindata/COCO2017"
+
+anno_converted='/npu/traindata/COCO2017/val2017.txt'
+gt_anno_path='/npu/traindata/COCO2017/annotations/instances_val2017.json'
+
+#屏蔽TF2.4升级到TF2.6图差异带来的性能下降
+export NPU_EXECUTE_OP_BY_ACL=false
+
+#设置默认日志级别,不需要修改
+export ASCEND_GLOBAL_LOG_LEVEL_ETP=3
+
+#基础参数 需要模型审视修改
+#网络名称，同目录名称
+Network="YOLOv5_ID1719_for_TensorFlow2.X"
+
+# 训练epoch
+stage1_epoch=0
+stage2_epoch=1
+
+# 训练batchsize
+batch_size=8
+
+train_worker_num=8
+
+# TF2.X独有，不需要修改
+export NPU_LOOPSIZE=1
+
+# 精度模式
+precision_mode='allow_mix_precision'
+#维持参数，不需要修改
+over_dump=False
+over_dump_path=''
+data_dump_flag=False
+data_dump_path=''
+data_dump_step="1"
+profiling=False
+autotune=False
+perf=20
+
+
+#校验是否传入data_path,不需要修改
+if [[ $data_path == "" ]];then
+    echo "[Error] para \"data_path\" must be specified"
+    exit 1
+fi
+
+#训练开始时间，不需要修改
+start_time=$(date +%s)
+bind_core=1
+#进入训练脚本目录，需要模型审视修改
+#for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
+for((RANK_ID=$((rank_size*server_index));RANK_ID<$((((server_index+1))*rank_size));RANK_ID++));
+do
+    #设置环境变量，不需要修改
+    echo "Device ID: $RANK_ID"
+    export RANK_ID=$RANK_ID
+    export ASCEND_DEVICE_ID=`expr ${RANK_ID} - $((rank_size*server_index))`
+    ASCEND_DEVICE_ID=`expr ${RANK_ID} - $((rank_size*server_index))`
+    export DEVICE_ID=${ASCEND_DEVICE_ID}
+    #echo 'DEVICE_ID: '$ASCEND_DEVICE_ID
+    RANK_ID_core=$RANK_ID
+
+    #创建DeviceID输出目录，不需要修改
+    if [ -d ${cur_path}/output/$ASCEND_DEVICE_ID ];then
+        rm -rf ${cur_path}/output/$ASCEND_DEVICE_ID
+        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
+    else
+        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
+    fi
+    cd ${cur_path}/output/$ASCEND_DEVICE_ID/
+    #执行训练脚本，需要模型审视修改
+    if [ ${RANK_ID_core} -gt 7 ];then
+        RANK_ID_core=$((RANK_ID_core-8))
+    fi
+
+    #echo 'RANK_ID_core is: '$RANK_ID_core
+
+    # 执行训练脚本，需要模型审视修改
+    corenum=`cat /proc/cpuinfo |grep 'processor' |wc -l`
+    let a=RANK_ID_core*${corenum}/8
+    let b=RANK_ID_core+1
+    let c=b*${corenum}/8-1
+    if [ "x${bind_core}" != x ];then
+        bind_core="taskset -c $a-$c"
+    fi
+    #${bind_core} python3 ../../../train.py --weights='' \
+    nohup ${bind_core} python3 ../../../train.py --weights='' \
+              --perf=$perf \
+              --model=yolov5m \
+              --rank=${RANK_ID} \
+              --rank_size=${RANK_SIZE} \
+              --train_worker_num=${train_worker_num} \
+              --data_path=${data_path} \
+              --anno_converted=${anno_converted} \
+              --gt_anno_path=${gt_anno_path} \
+              --batch_size=${batch_size} \
+              --precision_mode=${precision_mode} \
+              --stage1_epoch=${stage1_epoch} \
+              --stage2_epoch=${stage2_epoch} \
+              --over_dump=${over_dump} \
+              --over_dump_path=${over_dump_path} \
+              --data_dump_flag=${data_dump_flag} \
+              --data_dump_step=${data_dump_step} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+done
+wait
+
+#训练结束时间，不需要修改
+end_time=$(date +%s)
+e2e_time=$(( $end_time - $start_time ))
+
+echo "------------------ Final result ------------------"
+#输出性能FPS。需要模型审视修改
+epoch_duration=`grep epoch_duration $cur_path/output/0/train_0.log | awk '{print $2}'`
+first_step=`grep duration: $cur_path/output/0/train_0.log |head -1| awk 'END{print $18}'`
+FPS=`awk 'BEGIN{printf "%.2f\n",('$perf'+'$train_worker_num'-2)/('$epoch_duration'-'$first_step')*'$batch_size'*16}'`
+echo "Final Performance imgs/sec : $FPS"
+
+#训练精度，需要从train_$ASCEND_DEVICE_ID.log里，通过关键字获取。需要模型审视修改
+# li=`cat $cur_path/output/0/train_0.log | wc -l`
+# num=$(($li - 1))
+# train_accuracy=`sed -n "${num}p" $cur_path/output/0/train_0.log | awk '{print $3}'`
+# echo "Final Train Accuracy : ${train_accuracy}"
+#E2E训练端到端时长，直接计算，不需要修改
+echo "E2E training Duration sec: $e2e_time"
+
+#训练用例信息，不需要修改
+DeviceType=`uname -m`
+CaseName=${Network}${name_bind}_bs${batch_size}_${RANK_SIZE}'p'_'perf'
+
+##获取性能数据，不需要修改
+#吞吐量
+ActualFPS=${FPS}
+#单迭代训练时长
+TrainingTime=`awk 'BEGIN{printf "%.2f\n",('$epoch_duration'-'$first_step')/('$perf'+'$train_worker_num'-2)}'`
+
+##获取Loss，通过train_*.log中关键字，需要根据模型审视
+grep loss $cur_path/output/0/train_0.log|awk '{print $13}' > $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
+
+#最后一个迭代loss值，不需要修改
+ActualLoss=`grep total_loss: $cur_path/output/0/train_0.log | awk 'END{print $13}'`
+
+#关键信息打印到${CaseName}.log中，不需要修改
+echo "Network = ${Network}" > $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "RankSize = ${RANK_SIZE}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "BatchSize = ${batch_size}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DeviceType = ${DeviceType}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+# echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "E2ETrainingTime= ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+
+for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
+do
+    sed -i "/AttributeError/d" $cur_path/output/${RANK_ID}/train_${RANK_ID}.log
+done
\ No newline at end of file
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_1p.sh b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_1p.sh
new file mode 100644
index 0000000000000000000000000000000000000000..c55b4030a46f8b78d10e2b27e1d9f8fb3324b609
--- /dev/null
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_1p.sh
@@ -0,0 +1,204 @@
+#!/bin/bash
+
+#当前路径,不需要修改
+cur_path=`pwd`
+
+export PYTHONWARNINGS='ignore:semaphore_tracker:UserWarning'
+
+#集合通信参数,不需要修改
+#保证rank table file 文件rank_table_8p.json存放在和test同级的configs目录下
+export RANK_SIZE=1
+#export RANK_TABLE_FILE=${cur_path}/../configs/rank_table_8p.json
+export JOB_ID=10087
+RANK_ID_START=0
+RANK_SIZE=1
+
+# 数据集路径,保持为空,不需要修改
+data_path=""
+
+anno_converted='/npu/traindata/COCO2017/val2017.txt'
+gt_anno_path='/npu/traindata/COCO2017/annotations/instances_val2017.json'
+
+#屏蔽TF2.4升级到TF2.6图差异带来的性能下降
+#export NPU_EXECUTE_OP_BY_ACL=false
+
+#设置默认日志级别,不需要修改
+export ASCEND_GLOBAL_LOG_LEVEL_ETP=3
+
+#基础参数 需要模型审视修改
+#网络名称，同目录名称
+Network="YOLOv5_ID1719_for_TensorFlow2.X"
+
+# 训练epoch
+stage1_epoch=0
+stage2_epoch=1
+
+# 训练batchsize
+batch_size=8
+
+train_worker_num=8
+
+# TF2.X独有，不需要修改
+export NPU_LOOPSIZE=1
+
+# 精度模式
+precision_mode='allow_mix_precision'
+#维持参数，不需要修改
+over_dump=False
+over_dump_path=''
+data_dump_flag=False
+data_dump_path=''
+data_dump_step="1"
+profiling=False
+autotune=False
+perf=20
+
+# 帮助信息，不需要修改
+if [[ $1 == --help || $1 == -h ]];then
+    echo"usage:./train_full_8p.sh <args>"
+    echo " "
+    echo "parameter explain:
+    --precision_mode           precision mode(allow_fp32_to_fp16/force_fp16/must_keep_origin_dtype/allow_mix_precision)
+    --over_dump		           if or not over detection, default is False
+    --data_dump_flag		   data dump flag, default is 0
+    --data_dump_step		   data dump step, default is 10
+    --profiling		           if or not profiling for performance debug, default is False
+    --data_path		           source data of training
+    -h/--help		           show help message
+    "
+    exit 1
+fi
+
+#参数校验，不需要修改
+for para in $*
+do
+    if [[ $para == --precision_mode* ]];then
+        precision_mode=`echo ${para#*=}`
+    elif [[ $para == --over_dump* ]];then
+        over_dump=`echo ${para#*=}`
+        over_dump_path=${cur_path}/output/overflow_dump
+        mkdir -p ${over_dump_path}
+    elif [[ $para == --data_dump_flag* ]];then
+        data_dump_flag=`echo ${para#*=}`
+        data_dump_path=${cur_path}/output/data_dump
+        mkdir -p ${data_dump_path}
+    elif [[ $para == --data_dump_step* ]];then
+        data_dump_step=`echo ${para#*=}`
+    elif [[ $para == --profiling* ]];then
+        profiling=`echo ${para#*=}`
+        profiling_dump_path=${cur_path}/output/profiling
+        mkdir -p ${profiling_dump_path}
+    elif [[ $para == --data_path* ]];then
+        data_path=`echo ${para#*=}`
+    elif [[ $para == --bind_core* ]]; then
+        bind_core=`echo ${para#*=}`
+        name_bind="_bindcore"
+    fi
+done
+
+#校验是否传入data_path,不需要修改
+if [[ $data_path == "" ]];then
+    echo "[Error] para \"data_path\" must be specified"
+    exit 1
+fi
+
+#训练开始时间，不需要修改
+start_time=$(date +%s)
+bind_core=1
+#进入训练脚本目录，需要模型审视修改
+for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
+do
+    #设置环境变量，不需要修改
+    echo "Device ID: $RANK_ID"
+    export RANK_ID=$RANK_ID
+    export ASCEND_DEVICE_ID=$RANK_ID
+    ASCEND_DEVICE_ID=$RANK_ID
+
+    #创建DeviceID输出目录，不需要修改
+    if [ -d ${cur_path}/output/$ASCEND_DEVICE_ID ];then
+        rm -rf ${cur_path}/output/$ASCEND_DEVICE_ID
+        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
+    else
+        mkdir -p ${cur_path}/output/$ASCEND_DEVICE_ID/ckpt
+    fi
+    cd ${cur_path}/output/$ASCEND_DEVICE_ID/
+    #执行训练脚本，需要模型审视修改
+    corenum=`cat /proc/cpuinfo |grep 'processor' |wc -l`
+    let a=RANK_ID*${corenum}/8
+    let b=RANK_ID+1
+    let c=b*${corenum}/8-1
+    if [ "x${bind_core}" != x ];then
+        bind_core="taskset -c $a-$c"
+    fi
+    #${bind_core} python3 ../../../train.py --weights='' \
+    nohup ${bind_core} python3 ../../../train.py --weights='' \
+              --perf=$perf \
+              --model=yolov5m \
+              --rank=${RANK_ID} \
+              --rank_size=${RANK_SIZE} \
+              --train_worker_num=${train_worker_num} \
+              --data_path=${data_path} \
+              --anno_converted=${anno_converted} \
+              --gt_anno_path=${gt_anno_path} \
+              --batch_size=${batch_size} \
+              --precision_mode=${precision_mode} \
+              --stage1_epoch=${stage1_epoch} \
+              --stage2_epoch=${stage2_epoch} \
+              --over_dump=${over_dump} \
+              --over_dump_path=${over_dump_path} \
+              --data_dump_flag=${data_dump_flag} \
+              --data_dump_step=${data_dump_step} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+done
+wait
+
+#训练结束时间，不需要修改
+end_time=$(date +%s)
+e2e_time=$(( $end_time - $start_time ))
+
+echo "------------------ Final result ------------------"
+#输出性能FPS。需要模型审视修改
+epoch_duration=`grep epoch_duration $cur_path/output/0/train_0.log | awk '{print $2}'`
+first_step=`grep duration: $cur_path/output/0/train_0.log |head -1| awk 'END{print $17}'`
+FPS=`awk 'BEGIN{printf "%.2f\n",('$perf'+'$train_worker_num'-2)/('$epoch_duration'-'$first_step')*'$batch_size'*1}'`
+echo "Final Performance imgs/sec : $FPS"
+
+#训练精度，需要从train_$ASCEND_DEVICE_ID.log里，通过关键字获取。需要模型审视修改
+# li=`cat $cur_path/output/0/train_0.log | wc -l`
+# num=$(($li - 1))
+# train_accuracy=`sed -n "${num}p" $cur_path/output/0/train_0.log | awk '{print $3}'`
+# echo "Final Train Accuracy : ${train_accuracy}"
+#E2E训练端到端时长，直接计算，不需要修改
+echo "E2E training Duration sec: $e2e_time"
+
+#训练用例信息，不需要修改
+DeviceType=`uname -m`
+CaseName=${Network}${name_bind}_bs${batch_size}_${RANK_SIZE}'p'_'perf'
+
+##获取性能数据，不需要修改
+#吞吐量
+ActualFPS=${FPS}
+#单迭代训练时长
+TrainingTime=`awk 'BEGIN{printf "%.2f\n",('$epoch_duration'-'$first_step')/('$perf'+'$train_worker_num'-2)}'`
+
+##获取Loss，通过train_*.log中关键字，需要根据模型审视
+grep loss $cur_path/output/0/train_0.log|awk '{print $13}' > $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
+
+#最后一个迭代loss值，不需要修改
+ActualLoss=`grep total_loss: $cur_path/output/0/train_0.log | awk 'END{print $13}'`
+
+#关键信息打印到${CaseName}.log中，不需要修改
+echo "Network = ${Network}" > $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "RankSize = ${RANK_SIZE}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "BatchSize = ${batch_size}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "DeviceType = ${DeviceType}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "CaseName = ${CaseName}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "ActualFPS = ${ActualFPS}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "TrainingTime = ${TrainingTime}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+# echo "TrainAccuracy = ${train_accuracy}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "ActualLoss = ${ActualLoss}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+echo "E2ETrainingTime= ${e2e_time}" >> $cur_path/output/$ASCEND_DEVICE_ID/${CaseName}.log
+
+for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
+do
+    sed -i "/AttributeError/d" $cur_path/output/${RANK_ID}/train_${RANK_ID}.log
+done
\ No newline at end of file
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_8p.sh b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_8p.sh
index 744bdd6505d098848a7384dfdacf4d93bc2ae255..6f24266d5bf266bfd778043d527358be8ab81edf 100644
--- a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_8p.sh
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/test/train_performance_8p.sh
@@ -11,7 +11,7 @@ export RANK_SIZE=8
 export RANK_TABLE_FILE=${cur_path}/../configs/rank_table_8p.json
 export JOB_ID=10087
 RANK_ID_START=0
-
+RANK_SIZE=8
 # 数据集路径,保持为空,不需要修改
 data_path=""
 
@@ -22,7 +22,7 @@ gt_anno_path='/npu/traindata/COCO2017/annotations/instances_val2017.json'
 export NPU_EXECUTE_OP_BY_ACL=false
 
 #设置默认日志级别,不需要修改
-export ASCEND_GLOBAL_LOG_LEVEL=3
+export ASCEND_GLOBAL_LOG_LEVEL_ETP=3
 
 #基础参数 需要模型审视修改
 #网络名称，同目录名称
@@ -103,7 +103,7 @@ fi
 
 #训练开始时间，不需要修改
 start_time=$(date +%s)
-
+bind_core=1
 #进入训练脚本目录，需要模型审视修改
 for((RANK_ID=$RANK_ID_START;RANK_ID<$((RANK_SIZE+RANK_ID_START));RANK_ID++));
 do
@@ -129,22 +129,24 @@ do
     if [ "x${bind_core}" != x ];then
         bind_core="taskset -c $a-$c"
     fi
-	${bind_core} python3 ../../../train.py --weights='' \
-            --perf=$perf \
-            --model=yolov5m \
-            --rank=${RANK_ID} \
-            --train_worker_num=${train_worker_num} \
-            --data_path=${data_path} \
-            --anno_converted=${anno_converted} \
-            --gt_anno_path=${gt_anno_path} \
-            --batch_size=${batch_size} \
-            --precision_mode=${precision_mode} \
-            --stage1_epoch=${stage1_epoch} \
-            --stage2_epoch=${stage2_epoch} \
-            --over_dump=${over_dump} \
-            --over_dump_path=${over_dump_path} \
-            --data_dump_flag=${data_dump_flag} \
-            --data_dump_step=${data_dump_step} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
+    #${bind_core} python3 ../../../train.py --weights='' \
+    nohup ${bind_core} python3 ../../../train.py --weights='' \
+              --perf=$perf \
+              --model=yolov5m \
+              --rank=${RANK_ID} \
+              --rank_size=${RANK_SIZE} \
+              --train_worker_num=${train_worker_num} \
+              --data_path=${data_path} \
+              --anno_converted=${anno_converted} \
+              --gt_anno_path=${gt_anno_path} \
+              --batch_size=${batch_size} \
+              --precision_mode=${precision_mode} \
+              --stage1_epoch=${stage1_epoch} \
+              --stage2_epoch=${stage2_epoch} \
+              --over_dump=${over_dump} \
+              --over_dump_path=${over_dump_path} \
+              --data_dump_flag=${data_dump_flag} \
+              --data_dump_step=${data_dump_step} > ${cur_path}/output/${ASCEND_DEVICE_ID}/train_${ASCEND_DEVICE_ID}.log 2>&1 &
 done
 wait
 
@@ -178,7 +180,7 @@ ActualFPS=${FPS}
 TrainingTime=`awk 'BEGIN{printf "%.2f\n",('$epoch_duration'-'$first_step')/('$perf'+'$train_worker_num'-2)}'`
 
 ##获取Loss，通过train_*.log中关键字，需要根据模型审视
-grep loss $cur_path/output/0/train_0.log|awk '{print $13}' >> $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
+grep loss $cur_path/output/0/train_0.log|awk '{print $13}' > $cur_path/output/$ASCEND_DEVICE_ID/train_${CaseName}_loss.txt
 
 #最后一个迭代loss值，不需要修改
 ActualLoss=`grep total_loss: $cur_path/output/0/train_0.log | awk 'END{print $13}'`
diff --git a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/train.py b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/train.py
index 9bb4994f498812b9b4f7440e8dd0d86f4ded8ad3..d17bc0cc806951471ebe9f14c236a55ae8a5c223 100644
--- a/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/train.py
+++ b/TensorFlow2/built-in/cv/detection/YOLOv5_ID1719_for_TensorFlow2.X/train.py
@@ -65,6 +65,7 @@ flags.DEFINE_integer('train_worker_num', 8, 'train worker num')
 flags.DEFINE_boolean('eval_only', False, 'skip train process')
 flags.DEFINE_boolean('mosaic', True, 'activate mosaic data augmentation')
 flags.DEFINE_integer('rank', 0, 'rank of current device')
+flags.DEFINE_integer('rank_size', 1, 'rank size of current device')
 flags.DEFINE_integer('perf', 0, 'run steps for perf')
 tic = 0
 e_tic = 0
@@ -169,8 +170,8 @@ def main(_argv):
             lr = cfg.TRAIN.LR_END + 0.5 * (cfg.TRAIN.LR_INIT - cfg.TRAIN.LR_END) * ((1 + tf.cos((global_steps - warmup_steps) / (total_steps - warmup_steps) * np.pi)))
         optimizer.lr.assign(lr.numpy())
         ciou_loss, conf_loss, prob_loss, total_loss = train_execute(image_data, target)
-        if FLAGS.rank == 0:
-            print("=> STEP %4d/%4d   lr: %.6f   ciou_loss: %4.2f   conf_loss: %4.2f   prob_loss: %4.2f   total_loss: %4.2f" % (global_steps, total_steps, optimizer.lr.numpy(), ciou_loss, conf_loss, prob_loss, total_loss), end='', flush=True)
+        # if FLAGS.rank == 0:
+        print("=> STEP %4d/%4d   lr: %.6f   ciou_loss: %4.2f   conf_loss: %4.2f   prob_loss: %4.2f   total_loss: %4.2f" % (global_steps, total_steps, optimizer.lr.numpy(), ciou_loss, conf_loss, prob_loss, total_loss), end='', flush=True)
         global_steps.assign_add(1)
 
     if not FLAGS.eval_only:
@@ -204,13 +205,13 @@ def main(_argv):
                             break
                     image_data, target, _, _, _, _ = fetcher.process_annotations(annotations)
                     with mutex_sess_run:
-                        if FLAGS.rank == 0:
-                            rstart = time.time()
+                        # if FLAGS.rank == 0:
+                        rstart = time.time()
                         train_step(image_data, target)
-                        if FLAGS.rank == 0:
-                            duration = time.time() - tic
-                            print(' ,global_step/sec: %.2f ,duration: %.2f'%((1 / duration), duration), flush=True)
-                            tic = time.time()
+                        # if FLAGS.rank == 0:
+                        duration = time.time() - tic
+                        print(' ,global_step/sec: %.2f ,duration: %.2f'%((1 / duration), duration), flush=True)
+                        tic = time.time()
                         if FLAGS.perf and (FLAGS.perf < global_steps.numpy()):
                             break
             threads = []
@@ -222,11 +223,11 @@ def main(_argv):
             for t in threads:
                 t.join()
             
-            if FLAGS.rank == 0:
-                print('epoch_duration: %d'%(time.time() - e_tic), flush=True)
-                e_tic = time.time()
-                print('saving checkpoints', flush=True)
-                checkpoint.save(checkpoint_dir+'/model.ckpt')
+            # if FLAGS.rank == 0:
+            print('epoch_duration: %d'%(time.time() - e_tic), flush=True)
+            e_tic = time.time()
+            # print('saving checkpoints', flush=True)
+            # checkpoint.save(checkpoint_dir+'/model.ckpt')
     if not FLAGS.perf and FLAGS.rank == 0:
         evaluator = COCOevaluator(model, testset, cfg.TRAIN.INPUT_SIZE, NUM_CLASS, FLAGS)
         evaluator.evaluate()