Google cloud platform 为什么在执行gcloud ml引擎作业时加速器不足？

我试图在谷歌云上运行机器学习Jon，但它总是告诉我可用的加速器不足，我尝试使用参数

——scale tier=BASIC | BASIC | GPU | STANDARD | PREMIUM | u 1

。也是同样的结果

以下是命令和结果：

gcloud ml-engine jobs submit training object_detection_`date +%s`     --job-dir=gs://${TRAIN_DIR}     --packages dist/object_detection-0.1.tar.gz,slim/dist/slim-0.1.tar.gz     --module-name object_detection.train     --region us-central1     --config ${PATH_TO_LOCAL_YAML_FILE}     --     --train_dir=gs://${TRAIN_DIR}     --pipeline_config_path=gs://${PIPELINE_CONFIG_PATH}
ERROR: (gcloud.ml-engine.jobs.submit.training) RESOURCE_EXHAUSTED: Field: scale_tier Error: Insufficient accelerators are available in region us-central1 to schedule the job which requests 6 K80 accelerators. Please wait and try again or else try submitting your job to a different region.
- '@type': type.googleapis.com/google.rpc.BadRequest
  fieldViolations:
  - description: Insufficient accelerators are available in region us-central1 to
      schedule the job which requests 6 K80 accelerators. Please wait and try again
      or else try submitting your job to a different region.
    field: scale_tier

---

在

us-central1

中，GPU的需求量很大。如果可能的话，我建议在短期内在

us-east1

中运行您的作业，直到有更多GPU可用