Key |
Returned |
Description |
resources
complex
|
always |
List of resources
|
|
autoScaling
complex
|
success |
Automatically scale the number of nodes used to serve the model in response to increases and decreases in traffic. Care should be taken to ramp up traffic according to the model's ability to scale or you will start seeing increases in latency and 429 response codes.
|
|
|
minNodes
integer
|
success |
The minimum number of nodes to allocate for this mode.
|
|
createTime
string
|
success |
The time the version was created.
|
|
deploymentUri
string
|
success |
The Cloud Storage location of the trained model used to create the version.
|
|
description
string
|
success |
The description specified for the version when it was created.
|
|
errorMessage
string
|
success |
The details of a failure or cancellation.
|
|
framework
string
|
success |
The machine learning framework AI Platform uses to train this version of the model.
|
|
isDefault
boolean
|
success |
If true, this version will be used to handle prediction requests that do not specify a version.
|
|
labels
dictionary
|
success |
One or more labels that you can add, to organize your model versions.
|
|
lastUseTime
string
|
success |
The time the version was last used for prediction.
|
|
machineType
string
|
success |
The type of machine on which to serve the model. Currently only applies to online prediction service.
|
|
manualScaling
complex
|
success |
Manually select the number of nodes to use for serving the model. You should generally use autoScaling with an appropriate minNodes instead, but this option is available if you want more predictable billing. Beware that latency and error rates will increase if the traffic exceeds that capability of the system to serve it based on the selected number of nodes.
|
|
|
nodes
integer
|
success |
The number of nodes to allocate for this model. These nodes are always up, starting from the time the model is deployed.
|
|
model
dictionary
|
success |
The model that this version belongs to.
|
|
name
string
|
success |
The name specified for the version when it was created.
The version name must be unique within the model it is created in.
|
|
packageUris
list
/ elements=string
|
success |
Cloud Storage paths (gs://…) of packages for custom prediction routines or scikit-learn pipelines with custom code.
|
|
predictionClass
string
|
success |
The fully qualified name (module_name.class_name) of a class that implements the Predictor interface described in this reference field. The module containing this class should be included in a package provided to the packageUris field.
|
|
pythonVersion
string
|
success |
The version of Python used in prediction. If not set, the default version is '2.7'. Python '3.5' is available when runtimeVersion is set to '1.4' and above. Python '2.7' works with all supported runtime versions.
|
|
runtimeVersion
string
|
success |
The AI Platform runtime version to use for this deployment.
|
|
serviceAccount
string
|
success |
Specifies the service account for resource access control.
|
|
state
string
|
success |
The state of a version.
|