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https://issues.apache.org/jira/browse/AIRFLOW-3624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16832361#comment-16832361
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ASF subversion and git services commented on AIRFLOW-3624:
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Commit b54051c0d055ed00ccc137de733fa94b5f07ba02 in airflow's branch
refs/heads/v1-10-stable from K.K. POON
[ https://gitbox.apache.org/repos/asf?p=airflow.git;h=b54051c ]
[AIRFLOW-3624] Add masterType parameter to MLEngineTrainingOperator (#4428)
(cherry picked from commit 67d8ab760b372919c1d500bd9901dbae48a4517d)
> Add masterType parameter to MLEngineTrainingOperator
> ----------------------------------------------------
>
> Key: AIRFLOW-3624
> URL: https://issues.apache.org/jira/browse/AIRFLOW-3624
> Project: Apache Airflow
> Issue Type: Improvement
> Components: gcp, operators
> Reporter: K.K. POON
> Priority: Major
> Labels: pull-request-available
> Fix For: 1.10.4
>
>
> Ref to document
> https://cloud.google.com/ml-engine/docs/tensorflow/machine-types
> When the scale_tier is set to CUSTOM, user should specify masterType
> {quote}The CUSTOM tier is not a set tier, but rather enables you to use your
> own cluster specification. When you use this tier, set values to configure
> your processing cluster according to these guidelines:
> {quote} *
> {quote}You must set {{TrainingInput.masterType}} to specify the type of
> machine to use for your master node. This is the only required setting. See
> the [machine
> types|https://cloud.google.com/ml-engine/docs/tensorflow/machine-types#machine_type_table]
> described below.{quote}
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