Collection: projects.models.versions

Resource: Version

Represents a version of the model.

Each version is a trained model deployed in the cloud, ready to handle prediction requests. A model can have multiple versions. You can get information about all of the versions of a given model by calling projects.models.versions.list.

JSON representation
{
  "name": string,
  "description": string,
  "isDefault": boolean,
  "deploymentUri": string,
  "createTime": string,
  "lastUseTime": string,
  "runtimeVersion": string,
  "manualScaling": {
    object(ManualScaling)
  },
}
Fields
name

string

Required.The name specified for the version when it was created.

The version name must be unique within the model it is created in.

description

string

Optional. The description specified for the version when it was created.

isDefault

boolean

Output only. If true, this version will be used to handle prediction requests that do not specify a version.

You can change the default version by calling projects.methods.versions.setDefault.

deploymentUri

string

Required. The Google Cloud Storage location of the trained model used to create the version. See the overview of model deployment for more informaiton.

When passing Version to projects.models.versions.create the model service uses the specified location as the source of the model. Once deployed, the model version is hosted by the prediction service, so this location is useful only as a historical record.

createTime

string (Timestamp format)

Output only. The time the version was created.

A timestamp in RFC3339 UTC "Zulu" format, accurate to nanoseconds. Example: "2014-10-02T15:01:23.045123456Z".

lastUseTime

string (Timestamp format)

Output only. The time the version was last used for prediction.

A timestamp in RFC3339 UTC "Zulu" format, accurate to nanoseconds. Example: "2014-10-02T15:01:23.045123456Z".

runtimeVersion

string

Optional. The Google Cloud ML runtime version to use for this deployment. If not set, Google Cloud ML will choose a version.

manualScaling

object(ManualScaling)

Optional. Manually select the number of nodes to use for serving the model. If unset (i.e., by default), the number of nodes used to serve the model automatically scales with traffic. However, care should be taken to ramp up traffic according to the model's ability to scale. If your model needs to handle bursts of traffic beyond it's ability to scale, it is recommended you set this field appropriately.

Methods

create

Creates a new version of a model from a trained TensorFlow model.

delete

Deletes a model version.

get

Gets information about a model version.

list

Gets basic information about all the versions of a model.

setDefault

Designates a version to be the default for the model.

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Cloud Machine Learning Engine (Cloud ML Engine)