runtime_version 与 cloudml-samples/flowers/sample.sh 中的运行时版本
runtime_version versus runtime-version in cloudml-samples/flowers/sample.sh
在 Google 的示例代码 cloudml-samples/flowers/sample.sh 中,第 52 行和第 64 行之间的参数是 "runtime_version":
# Training on CloudML is quick after preprocessing. If you ran the above
# commands asynchronously, make sure they have completed before calling this one.
gcloud ml-engine jobs submit training "$JOB_ID" \
--stream-logs \
--module-name trainer.task \
--package-path trainer \
--staging-bucket "$BUCKET" \
--region us-central1 \
--runtime_version=1.0 \
-- \
--output_path "${GCS_PATH}/training" \
--eval_data_paths "${GCS_PATH}/preproc/eval*" \
--train_data_paths "${GCS_PATH}/preproc/train*"
不应该将 "runtime_version" 替换为 "runtime-version" 以避免错误吗?
是的。我已经提交了一个PR(以后一定要自己提交)
在 Google 的示例代码 cloudml-samples/flowers/sample.sh 中,第 52 行和第 64 行之间的参数是 "runtime_version":
# Training on CloudML is quick after preprocessing. If you ran the above
# commands asynchronously, make sure they have completed before calling this one.
gcloud ml-engine jobs submit training "$JOB_ID" \
--stream-logs \
--module-name trainer.task \
--package-path trainer \
--staging-bucket "$BUCKET" \
--region us-central1 \
--runtime_version=1.0 \
-- \
--output_path "${GCS_PATH}/training" \
--eval_data_paths "${GCS_PATH}/preproc/eval*" \
--train_data_paths "${GCS_PATH}/preproc/train*"
不应该将 "runtime_version" 替换为 "runtime-version" 以避免错误吗?
是的。我已经提交了一个PR(以后一定要自己提交)