修复部分模板模板

images/web/target-detection/Dockerfile

@@ -32,7 +32,7 @@ RUN pip install Pillow pysnooper opencv-python
 
 RUN pip3 install https://github.com/danielgatis/darknetpy/raw/master/dist/darknetpy-4.1-cp36-cp36m-linux_x86_64.whl
 WORKDIR /app
-#RUN wget https://pengluan-76009.sz.gfp.tencent-cloud.com/github/yolov3.zip && unzip yolov3.zip
+#RUN wget https://pengluan-76009.sz.gfp.tencent-cloud.com/github/yolov3.zip && apt install unzip && unzip yolov3.zip && rm yolov3.zip
 COPY . /app/
 ENTRYPOINT ["python", "server-web.py"]
 # docker run --name darknet --privileged -it --rm -v $PWD:/app -p 8080:8080 --entrypoint='' ai.tencentmusic.com/tme-public/target-detection  bash

images/web/target-detection/server-web.py

@@ -36,11 +36,13 @@ app = Flask(__name__,
 
 UPLOAD_FOLDER = "UPLOAD_FOLDER"
 myfont = ImageFont.truetype('/usr/share/fonts/truetype/wqy/wqy-zenhei.ttc', 20)
-YOLO_BASE_DIR = os.getenv('YOLO_BASE_DIR','yolo')
+YOLO_DATA_PATH = os.getenv('YOLO_DATA_PATH','yolo/coco.data')
+YOLO_CFG_PATH = os.getenv('YOLO_CFG_PATH','yolo/yolov3.cfg')
+YOLO_WEIGHTS_PATH = os.getenv('YOLO_WEIGHTS_PATH','yolo/yolov3.weights')
 
 class ImageDetector(object):
     def __init__(self):
-        self.detector = Detector(YOLO_BASE_DIR+'/coco.data',YOLO_BASE_DIR+'/yolov3.cfg',YOLO_BASE_DIR+'/yolov3.weights')
+        self.detector = Detector(YOLO_DATA_PATH,YOLO_CFG_PATH,YOLO_WEIGHTS_PATH)
 
     # @pysnooper.snoop()
     def classify_image(self, image_path):

job-template/job/deploy-service/Dockerfile

@@ -22,9 +22,7 @@ RUN echo "alias ll='ls -alF'" >> /root/.bashrc && \
 
 RUN pip install kubernetes==12.0.1 pysnooper psutil
 COPY job/deploy-service/* /app/
-#COPY job/pkgs/config/ubuntu-sources.list /etc/apt/sources.list
-#COPY job/pkgs/config/pip.conf /root/.pip/pip.conf
-COPY job/pkgs /app/job/pkgs
+
 WORKDIR /app
 ENV PYTHONPATH=/app:$PYTHONPATH
 

job-template/job/deploy-service/launcher.py

@@ -2,7 +2,6 @@
 import os,sys
 base_dir = os.path.split(os.path.realpath(__file__))[0]
 sys.path.append(base_dir)
-
 import argparse
 import datetime
 import json
@@ -13,14 +12,12 @@ import pysnooper
 import os,sys
 import re
 import requests
-import psutil
 import copy
+import os
 KFJ_CREATOR = os.getenv('KFJ_CREATOR', 'admin')
-host = 'http://kubeflow-dashboard.infra'
-# host = 'http://127.0.0.1:80'
-# host = 'http://9.135.92.226'
-
+KFJ_TASK_PROJECT_NAME = os.getenv('KFJ_TASK_PROJECT_NAME','public')
 
+host = os.getenv('HOST','http://kubeflow-dashboard.infra').strip('/')
 
 @pysnooper.snoop()
 def deploy(**kwargs):

job-template/job/object_detection_on_darknet/launcher.sh

@@ -21,4 +21,4 @@ done
 
 python3 setup_args.py --train_cfg "$train_cfg" --data_cfg "$data_cfg" --weights "$weights"
 
-/app/darknet/darknet detector train /app/darknet/cfg/data.cfg /app/darknet/cfg/train.cfg $weights 2>&1 | tee /mnt/uthermai/tmp/darknet/t.log
+/app/darknet/darknet detector train /app/darknet/cfg/data.cfg /app/darknet/cfg/train.cfg $weights 2>&1

myapp/init-job-template.json

@@ -1404,7 +1404,7 @@
     },
     "object-detection-on-darknet":{
         "project_name":"多媒体类模板",
-        "image_name":"mirrors.tencent.com/uthermai/object_detection_on_darknet:v1",
+        "image_name":"ai.tencentmusic.com/tme-public/object_detection_on_darknet:v1",
         "image_describe":"yolo目标识别",
         "job_template_name":"object-detection-on-darknet",
         "job_template_describe":"yolo目标识别",
@@ -1449,13 +1449,13 @@
                 "--weights": {
                     "type": "str",
                     "item_type": "str",
-                    "label": "权重文件",
+                    "label": "预训练模型权重文件",
                     "require": 1,
                     "choice": [],
                     "range": "",
                     "default": "",
                     "placeholder": "",
-                    "describe": "权重文件",
+                    "describe": "预训练模型权重文件",
                     "editable": 1,
                     "condition": "",
                     "sub_args": {}
@@ -1471,7 +1471,7 @@
         "job_template_describe":"模型部署推理服务",
         "job_template_command":"",
         "job_template_volume":"",
-        "job_template_account":"",
+        "job_template_account":"kubeflow-pipeline",
         "job_template_env":"",
         "job_template_expand":{
             "index":1,
@@ -1553,24 +1553,6 @@
                 }
             },
             "部署信息":{
-                "--project_name":{
-                    "type":"str",
-                    "item_type":"str",
-                    "label":"部署项目名",
-                    "require":1,
-                    "choice":[
-
-                    ],
-                    "range":"",
-                    "default":"public",
-                    "placeholder":"",
-                    "describe":"部署项目名",
-                    "editable":1,
-                    "condition":"",
-                    "sub_args":{
-
-                    }
-                },
                 "--service_type":{
                     "type":"str",
                     "item_type":"str",

myapp/models/model_notebook.py

@@ -75,7 +75,7 @@ class Notebook(Model,AuditMixinNullable,MyappModelBase):
         if SERVICE_EXTERNAL_IP:
             service_ports = 10000 + 10 * self.id
             host = "http://%s:%s"%(SERVICE_EXTERNAL_IP,str(service_ports))
-            url='/#/mnt/%s'%self.created_by.username
+            url = '/notebook/jupyter/%s/lab/tree/mnt/%s'%(self.name,self.created_by.username)
         return Markup(f'<a target=_blank href="{host}{url}">{self.name}</a>')
 
     @property

myapp/views/view_inferenceserving.py

@@ -667,6 +667,8 @@ instance_group [
 
     # @pysnooper.snoop(watch_explode=('item',))
     def pre_update(self, item):
+        if not item.volume_mount:
+            item.volume_mount=item.project.volume_mount
         item.name = item.name.replace("_","-")
         # 修改了名称的话，要把之前的删掉
         self.use_expand(item)

myapp/views/view_notebook.py

@@ -485,6 +485,7 @@ class Notebook_ModelView_Base():
                 k8s_client = py_k8s.K8s(item.cluster.get('KUBECONFIG',''))
                 k8s_client.delete_pods(namespace=item.namespace,pod_name=item.name)
                 k8s_client.delete_service(namespace=item.namespace,name=item.name)
+                k8s_client.delete_service(namespace=item.namespace, name=(item.name + "-external").lower()[:60].strip('-'))
                 crd_info = conf.get("CRD_INFO", {}).get('virtualservice', {})
                 if crd_info:
                     k8s_client.delete_crd(group=crd_info['group'], version=crd_info['version'],

myapp/views/view_pipeline.py

@@ -225,6 +225,7 @@ def dag_to_pipeline(pipeline,dbsession,**kwargs):
         container_envs.append(V1EnvVar("KFJ_TASK_RESOURCE_CPU", str(task.resource_cpu)))
         container_envs.append(V1EnvVar("KFJ_TASK_RESOURCE_MEMORY", str(task.resource_memory)))
         container_envs.append(V1EnvVar("KFJ_TASK_RESOURCE_GPU", str(task.resource_gpu.replace("+",''))))
+        container_envs.append(V1EnvVar("KFJ_TASK_PROJECT_NAME", str(pipeline.project.name)))
         container_envs.append(V1EnvVar("GPU_TYPE", os.environ.get("GPU_TYPE", "NVIDIA")))
         container_envs.append(V1EnvVar("USERNAME", pipeline.created_by.username))
 

myapp/views/view_task.py

@@ -423,6 +423,7 @@ class Task_ModelView_Base():
         task_env += 'KFJ_TASK_RESOURCE_CPU=' + str(task.resource_cpu) + "\n"
         task_env += 'KFJ_TASK_RESOURCE_MEMORY=' + str(task.resource_memory) + "\n"
         task_env += 'KFJ_TASK_RESOURCE_GPU=' + str(task.resource_gpu.replace('+', '')) + "\n"
+        task_env += 'KFJ_TASK_PROJECT_NAME=' + str(task.pipeline.project.name) + "\n"
         task_env += 'KFJ_PIPELINE_ID=' + str(task.pipeline_id) + "\n"
         task_env += 'KFJ_RUN_ID=' + run_id + "\n"
         task_env += 'KFJ_CREATOR=' + str(task.pipeline.created_by.username) + "\n"