在docker容器中设置活动的gcloud帐户

问题描述 投票:0回答:1

目前我正在GKE上设置Kubeflow Pipeline。目标是在ML引擎上启动trainingjob,然后在GKE上提供它。

trainingjob在Docker容器中启动。 (管道中的每一步都必须是一个容器。)

运行容器时出现以下错误:

ERROR: (gcloud.ml-engine.jobs.submit.training) You do not currently have an active account selected.
Please run:

  $ gcloud auth login

to obtain new credentials, or if you have already logged in with a
different account:

  $ gcloud config set account ACCOUNT

to select an already authenticated account to use.

docker容器通过following answer中建议的服务帐户获取凭据。

FROM tensorflow/tensorflow:1.8.0-devel-gpu-py3

RUN apt-get update -y && apt-get install --no-install-recommends -y -q ca-certificates python-dev python-setuptools wget unzip git


# Components to run ML Engine job on cluster
RUN cd / && \
    wget -nv https://dl.google.com/dl/cloudsdk/release/google-cloud-sdk.zip && \
    unzip -qq google-cloud-sdk.zip -d tools && \
    rm google-cloud-sdk.zip && \
    tools/google-cloud-sdk/install.sh --usage-reporting=false \
        --path-update=false --bash-completion=false \
        --disable-installation-options && \
    tools/google-cloud-sdk/bin/gcloud -q components update \
        gcloud core gsutil && \
    tools/google-cloud-sdk/bin/gcloud config set component_manager/disable_update_check true && \
    touch /tools/google-cloud-sdk/lib/third_party/google.py

ENV PATH $PATH:/tools/node/bin:/tools/google-cloud-sdk/bin

RUN mkdir /workdir

COPY . /workdir

RUN export GOOGLE_APPLICATION_CREDENTIALS=/workdir/ml6-sandbox-cdc8cb4bcae2.json

ENTRYPOINT ["bash", "/workdir/ml-engine/train.sh"]

错误发现在train.sh中,我提交了一个trainingjob:

gcloud ml-engine jobs submit training $JOB_NAME \
    --job-dir $JOB_DIR \
    --runtime-version 1.8 \
    --python-version 3.5 \
    --module-name trainer.run_train \
    --package-path ./trainer \
    --region $REGION \
    --config=trainer/config.yaml \
    --stream-logs \
    -- \
    --data-dir $DATA_DIR \
    --version $VERSION

在我的run_train.py中,我获得了以下Google Application Credentials:

os.environ[
        "GOOGLE_APPLICATION_CREDENTIALS"] = '/workdir/ml6-sandbox-cdc8cb4bcae2.json'

Train.sh独立工作。

docker google-cloud-platform dockerfile google-cloud-ml kubeflow
1个回答
1
投票

你只需要在GOOGLE_APPLICATION_CREDENTIALS时设置using the client libraries env变量。

当您使用gcloud CLI更改此行时:

RUN export GOOGLE_APPLICATION_CREDENTIALS=/workdir/ml6-sandbox-cdc8cb4bcae2.json

gcloud auth activate-service-account yourServiceAccount --key-file=/workdir/ml6-sandbox-cdc8cb4bcae2.json

这会将您的服务帐户记录为gcloud使用的有效帐户。

此外,此服务帐户需要使用适当的roles授予。

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