Try SpotterGather info for GCP Version
Authors: Google Inc. (@googlecloudplatform)
preview | supported by community
Install with ansible-galaxy collection install delowan.googlecloud:==1.0.2
collections:
- name: delowan.googlecloud
version: 1.0.2Gather info for GCP Version
- name: get info on a version
gcp_mlengine_version_info:
model: "{{ model }}"
project: test_project
auth_kind: serviceaccount
service_account_file: "/tmp/auth.pem"
model:
description:
- The model that this version belongs to.
- 'This field represents a link to a Model resource in GCP. It can be specified in
two ways. First, you can place a dictionary with key ''name'' and value of your
resource''s name Alternatively, you can add `register: name-of-resource` to a gcp_mlengine_model
task and then set this model field to "{{ name-of-resource }}"'
required: true
type: dict
scopes:
description:
- Array of scopes to be used
elements: str
type: list
project:
description:
- The Google Cloud Platform project to use.
type: str
env_type:
description:
- 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.
type: str
auth_kind:
choices:
- application
- machineaccount
- serviceaccount
description:
- The type of credential used.
required: true
type: str
service_account_file:
description:
- The path of a Service Account JSON file if serviceaccount is selected as type.
type: path
service_account_email:
description:
- An optional service account email address if machineaccount is selected and the
user does not wish to use the default email.
type: str
service_account_contents:
description:
- The contents of a Service Account JSON file, either in a dictionary or as a JSON
string that represents it.
type: jsonarg
resources:
contains:
autoScaling:
contains:
minNodes:
description:
- The minimum number of nodes to allocate for this mode.
returned: success
type: int
description:
- 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.
returned: success
type: complex
createTime:
description:
- The time the version was created.
returned: success
type: str
deploymentUri:
description:
- The Cloud Storage location of the trained model used to create the version.
returned: success
type: str
description:
description:
- The description specified for the version when it was created.
returned: success
type: str
errorMessage:
description:
- The details of a failure or cancellation.
returned: success
type: str
framework:
description:
- The machine learning framework AI Platform uses to train this version of the
model.
returned: success
type: str
isDefault:
description:
- If true, this version will be used to handle prediction requests that do not
specify a version.
returned: success
type: bool
labels:
description:
- One or more labels that you can add, to organize your model versions.
returned: success
type: dict
lastUseTime:
description:
- The time the version was last used for prediction.
returned: success
type: str
machineType:
description:
- The type of machine on which to serve the model. Currently only applies to
online prediction service.
returned: success
type: str
manualScaling:
contains:
nodes:
description:
- The number of nodes to allocate for this model. These nodes are always
up, starting from the time the model is deployed.
returned: success
type: int
description:
- 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.
returned: success
type: complex
model:
description:
- The model that this version belongs to.
returned: success
type: dict
name:
description:
- The name specified for the version when it was created.
- The version name must be unique within the model it is created in.
returned: success
type: str
packageUris:
description:
- "Cloud Storage paths (gs://\u2026) of packages for custom prediction routines\
\ or scikit-learn pipelines with custom code."
returned: success
type: list
predictionClass:
description:
- 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.
returned: success
type: str
pythonVersion:
description:
- 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.
returned: success
type: str
runtimeVersion:
description:
- The AI Platform runtime version to use for this deployment.
returned: success
type: str
serviceAccount:
description:
- Specifies the service account for resource access control.
returned: success
type: str
state:
description:
- The state of a version.
returned: success
type: str
description: List of resources
returned: always
type: complex