google.cloud.gcp_mlengine_model – Creates a GCP Model

Note

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

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)