github-actions[bot]
commented
2 years ago Hello，您可以直接执行该命令：
echo -e 'docker pull zhuyaguang/gcr.io.ml-pipeline.cache-server:1.8.1\ndocker tag zhuyaguang/gcr.io.ml-pipeline.cache-server:1.8.1 gcr.io/ml-pipeline/cache-server:1.8.1\n\ndocker pull zhuyaguang/public.ecr.aws.j1r0q0g6.notebooks.tensorboard-controller:v1.5.0\ndocker tag zhuyaguang/public.ecr.aws.j1r0q0g6.notebooks.tensorboard-controller:v1.5.0 public.ecr.aws/j1r0q0g6/notebooks/tensorboard-controller:v1.5.0\n\ndocker pull zhuyaguang/gcr.io.ml-pipeline.metadata-envoy:1.8.1\ndocker tag zhuyaguang/gcr.io.ml-pipeline.metadata-envoy:1.8.1 gcr.io/ml-pipeline/metadata-envoy:1.8.1\n\n' | bash或是手动执行：
docker pull zhuyaguang/gcr.io.ml-pipeline.cache-server:1.8.1
docker tag zhuyaguang/gcr.io.ml-pipeline.cache-server:1.8.1 gcr.io/ml-pipeline/cache-server:1.8.1
docker pull zhuyaguang/public.ecr.aws.j1r0q0g6.notebooks.tensorboard-controller:v1.5.0
docker tag zhuyaguang/public.ecr.aws.j1r0q0g6.notebooks.tensorboard-controller:v1.5.0 public.ecr.aws/j1r0q0g6/notebooks/tensorboard-controller:v1.5.0
docker pull zhuyaguang/gcr.io.ml-pipeline.metadata-envoy:1.8.1
docker tag zhuyaguang/gcr.io.ml-pipeline.metadata-envoy:1.8.1 gcr.io/ml-pipeline/metadata-envoy:1.8.1
希望可以帮助到您，祝您周二愉快！
{ "hub-mirror": [ "gcr.io/ml-pipeline/cache-server:1.8.1", "gcr.io/ml-pipeline/metadata-envoy:1.8.1", "public.ecr.aws/j1r0q0g6/notebooks/tensorboard-controller:v1.5.0" ] }