New Module: gcp_mlengine_version_facts (#59225)
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lib/ansible/modules/cloud/google/gcp_mlengine_version_facts.py
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lib/ansible/modules/cloud/google/gcp_mlengine_version_facts.py
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#!/usr/bin/python
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# -*- coding: utf-8 -*-
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#
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# Copyright (C) 2017 Google
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# GNU General Public License v3.0+ (see COPYING or https://www.gnu.org/licenses/gpl-3.0.txt)
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# ----------------------------------------------------------------------------
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#
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# *** AUTO GENERATED CODE *** AUTO GENERATED CODE ***
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#
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# ----------------------------------------------------------------------------
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#
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# This file is automatically generated by Magic Modules and manual
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# changes will be clobbered when the file is regenerated.
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#
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# Please read more about how to change this file at
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# https://www.github.com/GoogleCloudPlatform/magic-modules
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#
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# ----------------------------------------------------------------------------
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from __future__ import absolute_import, division, print_function
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__metaclass__ = type
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################################################################################
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# Documentation
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################################################################################
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ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ["preview"], 'supported_by': 'community'}
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DOCUMENTATION = '''
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---
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module: gcp_mlengine_version_facts
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description:
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- Gather facts for GCP Version
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short_description: Gather facts for GCP Version
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version_added: 2.9
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author: Google Inc. (@googlecloudplatform)
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requirements:
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- python >= 2.6
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- requests >= 2.18.4
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- google-auth >= 1.3.0
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options:
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model:
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description:
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- The model that this version belongs to.
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- 'This field represents a link to a Model resource in GCP. It can be specified
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in two ways. First, you can place a dictionary with key ''name'' and value of
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your resource''s name Alternatively, you can add `register: name-of-resource`
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to a gcp_mlengine_model task and then set this model field to "{{ name-of-resource
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}}"'
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required: true
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type: dict
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extends_documentation_fragment: gcp
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'''
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EXAMPLES = '''
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- name: " a version facts"
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gcp_mlengine_version_facts:
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model: "{{ model }}"
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project: test_project
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auth_kind: serviceaccount
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service_account_file: "/tmp/auth.pem"
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state: facts
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'''
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RETURN = '''
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resources:
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description: List of resources
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returned: always
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type: complex
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contains:
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name:
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description:
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- The name specified for the version when it was created.
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- The version name must be unique within the model it is created in.
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returned: success
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type: str
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description:
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description:
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- The description specified for the version when it was created.
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returned: success
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type: str
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isDefault:
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description:
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- If true, this version will be used to handle prediction requests that do not
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specify a version.
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returned: success
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type: bool
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deploymentUri:
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description:
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- The Cloud Storage location of the trained model used to create the version.
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returned: success
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type: str
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createTime:
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description:
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- The time the version was created.
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returned: success
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type: str
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lastUseTime:
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description:
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- The time the version was last used for prediction.
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returned: success
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type: str
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runtimeVersion:
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description:
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- The AI Platform runtime version to use for this deployment.
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returned: success
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type: str
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machineType:
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description:
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- The type of machine on which to serve the model. Currently only applies to
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online prediction service.
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returned: success
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type: str
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state:
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description:
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- The state of a version.
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returned: success
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type: str
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errorMessage:
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description:
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- The details of a failure or cancellation.
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returned: success
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type: str
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packageUris:
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description:
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- Cloud Storage paths (gs://…) of packages for custom prediction routines or
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scikit-learn pipelines with custom code.
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returned: success
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type: list
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labels:
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description:
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- One or more labels that you can add, to organize your model versions.
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returned: success
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type: dict
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framework:
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description:
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- The machine learning framework AI Platform uses to train this version of the
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model.
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returned: success
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type: str
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pythonVersion:
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description:
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- The version of Python used in prediction. If not set, the default version
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is '2.7'. Python '3.5' is available when runtimeVersion is set to '1.4' and
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above. Python '2.7' works with all supported runtime versions.
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returned: success
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type: str
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serviceAccount:
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description:
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- Specifies the service account for resource access control.
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returned: success
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type: str
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autoScaling:
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description:
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- Automatically scale the number of nodes used to serve the model in response
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to increases and decreases in traffic. Care should be taken to ramp up traffic
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according to the model's ability to scale or you will start seeing increases
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in latency and 429 response codes.
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returned: success
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type: complex
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contains:
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minNodes:
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description:
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- The minimum number of nodes to allocate for this mode.
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returned: success
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type: int
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manualScaling:
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description:
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- Manually select the number of nodes to use for serving the model. You should
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generally use autoScaling with an appropriate minNodes instead, but this option
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is available if you want more predictable billing. Beware that latency and
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error rates will increase if the traffic exceeds that capability of the system
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to serve it based on the selected number of nodes.
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returned: success
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type: complex
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contains:
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nodes:
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description:
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- The number of nodes to allocate for this model. These nodes are always
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up, starting from the time the model is deployed.
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returned: success
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type: int
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predictionClass:
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description:
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- The fully qualified name (module_name.class_name) of a class that implements
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the Predictor interface described in this reference field. The module containing
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this class should be included in a package provided to the packageUris field.
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returned: success
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type: str
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model:
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description:
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- The model that this version belongs to.
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returned: success
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type: dict
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'''
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################################################################################
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# Imports
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################################################################################
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from ansible.module_utils.gcp_utils import navigate_hash, GcpSession, GcpModule, GcpRequest, replace_resource_dict
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import json
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################################################################################
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# Main
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################################################################################
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def main():
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module = GcpModule(argument_spec=dict(model=dict(required=True, type='dict')))
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if not module.params['scopes']:
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module.params['scopes'] = ['https://www.googleapis.com/auth/cloud-platform']
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items = fetch_list(module, collection(module))
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if items.get('versions'):
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items = items.get('versions')
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else:
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items = []
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return_value = {'resources': items}
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module.exit_json(**return_value)
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def collection(module):
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res = {'project': module.params['project'], 'model': replace_resource_dict(module.params['model'], 'name')}
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return "https://ml.googleapis.com/v1/projects/{project}/models/{model}/versions".format(**res)
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def fetch_list(module, link):
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auth = GcpSession(module, 'mlengine')
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response = auth.get(link)
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return return_if_object(module, response)
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def return_if_object(module, response):
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# If not found, return nothing.
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if response.status_code == 404:
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return None
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# If no content, return nothing.
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if response.status_code == 204:
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return None
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try:
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module.raise_for_status(response)
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result = response.json()
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except getattr(json.decoder, 'JSONDecodeError', ValueError) as inst:
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module.fail_json(msg="Invalid JSON response with error: %s" % inst)
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if navigate_hash(result, ['error', 'errors']):
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module.fail_json(msg=navigate_hash(result, ['error', 'errors']))
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return result
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if __name__ == "__main__":
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main()
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