目前我正在 GKE 上设置Kubeflow 管道。目标是在 ML Engine 上启动一个训练作业,然后在 GKE 上提供它。
训练作业在 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 容器通过以下答案中的建议通过服务帐户获取凭据。
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"]
错误出现在我提交训练作业的 train.sh 中:
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 应用程序凭据:
os.environ[
"GOOGLE_APPLICATION_CREDENTIALS"] = '/workdir/ml6-sandbox-cdc8cb4bcae2.json'
Train.sh 独立工作。