google.cloud.gcp_mlengine_model – Creates a GCP Model

Note

This plugin is part of the google.cloud collection (version 1.0.2).

You might already have this collection installed if you are using the ansible package. It is not included in ansible-core. To check whether it is installed, run ansible-galaxy collection list.

To install it, use: ansible-galaxy collection install google.cloud.

To use it in a playbook, specify: google.cloud.gcp_mlengine_model.

Synopsis

  • Represents a machine learning solution.

  • A model can have multiple versions, each of which is a deployed, trained model ready to receive prediction requests. The model itself is just a container.

Requirements

The below requirements are needed on the host that executes this module.

  • python >= 2.6

  • requests >= 2.18.4

  • google-auth >= 1.3.0

Parameters

Parameter Choices/Defaults Comments
auth_kind
string / required
    Choices:
  • application
  • machineaccount
  • serviceaccount
The type of credential used.
default_version
dictionary
The default version of the model. This version will be used to handle prediction requests that do not specify a version.
name
string / required
The name specified for the version when it was created.
description
string
The description specified for the model when it was created.
env_type
string
Specifies which Ansible environment you're running this module within.
This should not be set unless you know what you're doing.
This only alters the User Agent string for any API requests.
labels
dictionary
One or more labels that you can add, to organize your models.
name
string / required
The name specified for the model.
online_prediction_console_logging
boolean
    Choices:
  • no
  • yes
If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging.
online_prediction_logging
boolean
    Choices:
  • no
  • yes
If true, online prediction access logs are sent to StackDriver Logging.
project
string
The Google Cloud Platform project to use.
regions
list / elements=string
The list of regions where the model is going to be deployed.
Currently only one region per model is supported .
scopes
list / elements=string
Array of scopes to be used
service_account_contents
jsonarg
The contents of a Service Account JSON file, either in a dictionary or as a JSON string that represents it.
service_account_email
string
An optional service account email address if machineaccount is selected and the user does not wish to use the default email.
service_account_file
path
The path of a Service Account JSON file if serviceaccount is selected as type.
state
string
    Choices:
  • present ←
  • absent
Whether the given object should exist in GCP

Examples

- name: create a model
  google.cloud.gcp_mlengine_model:
    name: "{{ resource_name | replace('-', '_') }}"
    description: My model
    regions:
    - us-central1
    project: test_project
    auth_kind: serviceaccount
    service_account_file: "/tmp/auth.pem"
    state: present

Return Values

Common return values are documented here, the following are the fields unique to this module:

Key Returned Description
defaultVersion
complex
success
The default version of the model. This version will be used to handle prediction requests that do not specify a version.

 
name
string
success
The name specified for the version when it was created.

description
string
success
The description specified for the model when it was created.

labels
dictionary
success
One or more labels that you can add, to organize your models.

name
string
success
The name specified for the model.

onlinePredictionConsoleLogging
boolean
success
If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging.

onlinePredictionLogging
boolean
success
If true, online prediction access logs are sent to StackDriver Logging.

regions
list / elements=string
success
The list of regions where the model is going to be deployed.
Currently only one region per model is supported .



Authors

  • Google Inc. (@googlecloudplatform)