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gcp_mlengine_model – Creates a GCP Model

New in version 2.9.

Synopsis
Requirements
Parameters
Notes
Examples
Return Values
Status

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		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			The list of regions where the model is going to be deployed. Currently only one region per model is supported .
scopes list			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

Notes

Note

for authentication, you can set service_account_file using the c(gcp_service_account_file) env variable.
for authentication, you can set service_account_contents using the c(GCP_SERVICE_ACCOUNT_CONTENTS) env variable.
For authentication, you can set service_account_email using the GCP_SERVICE_ACCOUNT_EMAIL env variable.
For authentication, you can set auth_kind using the GCP_AUTH_KIND env variable.
For authentication, you can set scopes using the GCP_SCOPES env variable.
Environment variables values will only be used if the playbook values are not set.
The service_account_email and service_account_file options are mutually exclusive.

Examples

- name: create a model
  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		success	The list of regions where the model is going to be deployed. Currently only one region per model is supported .

Status

This module is not guaranteed to have a backwards compatible interface. [preview]
This module is maintained by the Ansible Community. [community]

Authors

Google Inc. (@googlecloudplatform)

Hint

If you notice any issues in this documentation, you can edit this document to improve it.

© 2012–2018 Michael DeHaan
© 2018–2019 Red Hat, Inc.
Licensed under the GNU General Public License version 3.
https://docs.ansible.com/ansible/2.9/modules/gcp_mlengine_model_module.html