oracle.oci.oci_ai_vision_model – Manage a Model resource in Oracle Cloud Infrastructure¶
Note
This plugin is part of the oracle.oci collection (version 5.3.0).
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 oracle.oci
.
To use it in a playbook, specify: oracle.oci.oci_ai_vision_model
.
New in version 2.9.0: of oracle.oci
Synopsis¶
This module allows the user to create, update and delete a Model resource in Oracle Cloud Infrastructure
For state=present, create a new model.
This resource has the following action operations in the oracle.oci.oci_ai_vision_model_actions module: change_compartment.
Requirements¶
The below requirements are needed on the host that executes this module.
python >= 3.6
Python SDK for Oracle Cloud Infrastructure https://oracle-cloud-infrastructure-python-sdk.readthedocs.io
Parameters¶
Parameter | Choices/Defaults | Comments | |
---|---|---|---|
api_user
string
|
The OCID of the user, on whose behalf, OCI APIs are invoked. If not set, then the value of the OCI_USER_ID environment variable, if any, is used. This option is required if the user is not specified through a configuration file (See
config_file_location ). To get the user's OCID, please refer https://docs.us-phoenix-1.oraclecloud.com/Content/API/Concepts/apisigningkey.htm. |
||
api_user_fingerprint
string
|
Fingerprint for the key pair being used. If not set, then the value of the OCI_USER_FINGERPRINT environment variable, if any, is used. This option is required if the key fingerprint is not specified through a configuration file (See
config_file_location ). To get the key pair's fingerprint value please refer https://docs.us-phoenix-1.oraclecloud.com/Content/API/Concepts/apisigningkey.htm. |
||
api_user_key_file
string
|
Full path and filename of the private key (in PEM format). If not set, then the value of the OCI_USER_KEY_FILE variable, if any, is used. This option is required if the private key is not specified through a configuration file (See
config_file_location ). If the key is encrypted with a pass-phrase, the api_user_key_pass_phrase option must also be provided. |
||
api_user_key_pass_phrase
string
|
Passphrase used by the key referenced in
api_user_key_file , if it is encrypted. If not set, then the value of the OCI_USER_KEY_PASS_PHRASE variable, if any, is used. This option is required if the key passphrase is not specified through a configuration file (See config_file_location ). |
||
auth_purpose
string
|
|
The auth purpose which can be used in conjunction with 'auth_type=instance_principal'. The default auth_purpose for instance_principal is None.
|
|
auth_type
string
|
|
The type of authentication to use for making API requests. By default
auth_type="api_key" based authentication is performed and the API key (see api_user_key_file) in your config file will be used. If this 'auth_type' module option is not specified, the value of the OCI_ANSIBLE_AUTH_TYPE, if any, is used. Use auth_type="instance_principal" to use instance principal based authentication when running ansible playbooks within an OCI compute instance. |
|
cert_bundle
string
|
The full path to a CA certificate bundle to be used for SSL verification. This will override the default CA certificate bundle. If not set, then the value of the OCI_ANSIBLE_CERT_BUNDLE variable, if any, is used.
|
||
compartment_id
string
|
The compartment identifier.
Required for create using state=present.
|
||
config_file_location
string
|
Path to configuration file. If not set then the value of the OCI_CONFIG_FILE environment variable, if any, is used. Otherwise, defaults to ~/.oci/config.
|
||
config_profile_name
string
|
The profile to load from the config file referenced by
config_file_location . If not set, then the value of the OCI_CONFIG_PROFILE environment variable, if any, is used. Otherwise, defaults to the "DEFAULT" profile in config_file_location . |
||
defined_tags
dictionary
|
Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: `{"foo-namespace": {"bar-key": "value"}}`
This parameter is updatable.
|
||
description
string
|
An optional description of the model.
This parameter is updatable.
|
||
display_name
string
|
A human-friendly name for the model, which can be changed.
Required for create, update, delete when environment variable
OCI_USE_NAME_AS_IDENTIFIER is set.This parameter is updatable when
OCI_USE_NAME_AS_IDENTIFIER is not set.aliases: name |
||
force_create
boolean
|
|
Whether to attempt non-idempotent creation of a resource. By default, create resource is an idempotent operation, and doesn't create the resource if it already exists. Setting this option to true, forcefully creates a copy of the resource, even if it already exists.This option is mutually exclusive with key_by.
|
|
freeform_tags
dictionary
|
A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: `{"bar-key": "value"}`
This parameter is updatable.
|
||
is_quick_mode
boolean
|
|
Set to true when experimenting with a new model type or dataset, so the model training is quick, with a predefined low number of passes through the training data.
|
|
key_by
list
/ elements=string
|
The list of attributes of this resource which should be used to uniquely identify an instance of the resource. By default, all the attributes of a resource are used to uniquely identify a resource.
|
||
max_training_duration_in_hours
float
|
The maximum model training duration in hours, expressed as a decimal fraction.
|
||
model_id
string
|
A unique model identifier.
Required for update using state=present when environment variable
OCI_USE_NAME_AS_IDENTIFIER is not set.Required for delete using state=absent when environment variable
OCI_USE_NAME_AS_IDENTIFIER is not set.aliases: id |
||
model_type
string
|
Which type of Vision model this is.
Required for create using state=present.
|
||
model_version
string
|
The model version
|
||
project_id
string
|
The OCID of the project that contains the model.
Required for create using state=present.
|
||
realm_specific_endpoint_template_enabled
boolean
|
|
Enable/Disable realm specific endpoint template for service client. By Default, realm specific endpoint template is disabled. If not set, then the value of the OCI_REALM_SPECIFIC_SERVICE_ENDPOINT_TEMPLATE_ENABLED variable, if any, is used.
|
|
region
string
|
The Oracle Cloud Infrastructure region to use for all OCI API requests. If not set, then the value of the OCI_REGION variable, if any, is used. This option is required if the region is not specified through a configuration file (See
config_file_location ). Please refer to https://docs.us-phoenix-1.oraclecloud.com/Content/General/Concepts/regions.htm for more information on OCI regions. |
||
state
string
|
|
The state of the Model.
Use state=present to create or update a Model.
Use state=absent to delete a Model.
|
|
tenancy
string
|
OCID of your tenancy. If not set, then the value of the OCI_TENANCY variable, if any, is used. This option is required if the tenancy OCID is not specified through a configuration file (See
config_file_location ). To get the tenancy OCID, please refer https://docs.us-phoenix-1.oraclecloud.com/Content/API/Concepts/apisigningkey.htm |
||
testing_dataset
dictionary
|
|||
bucket_name
string
|
The name of the Object Storage bucket that contains the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
dataset_id
string
|
OCID of the Data Labeling dataset.
Applicable when dataset_type is 'DATA_SCIENCE_LABELING'
|
||
dataset_type
string
/ required
|
|
The dataset type, based on where it is stored.
|
|
namespace_name
string
|
The namespace name of the Object Storage bucket that contains the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
object_name
string
|
The object name of the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
training_dataset
dictionary
|
Required for create using state=present.
|
||
bucket_name
string
|
The name of the Object Storage bucket that contains the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
dataset_id
string
|
OCID of the Data Labeling dataset.
Applicable when dataset_type is 'DATA_SCIENCE_LABELING'
|
||
dataset_type
string
/ required
|
|
The dataset type, based on where it is stored.
|
|
namespace_name
string
|
The namespace name of the Object Storage bucket that contains the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
object_name
string
|
The object name of the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
validation_dataset
dictionary
|
|||
bucket_name
string
|
The name of the Object Storage bucket that contains the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
dataset_id
string
|
OCID of the Data Labeling dataset.
Applicable when dataset_type is 'DATA_SCIENCE_LABELING'
|
||
dataset_type
string
/ required
|
|
The dataset type, based on where it is stored.
|
|
namespace_name
string
|
The namespace name of the Object Storage bucket that contains the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
object_name
string
|
The object name of the input data file.
Applicable when dataset_type is 'OBJECT_STORAGE'
|
||
wait
boolean
|
|
Whether to wait for create or delete operation to complete.
|
|
wait_timeout
integer
|
Time, in seconds, to wait when wait=yes. Defaults to 1200 for most of the services but some services might have a longer wait timeout.
|
Notes¶
Note
For OCI python sdk configuration, please refer to https://oracle-cloud-infrastructure-python-sdk.readthedocs.io/en/latest/configuration.html
Examples¶
- name: Create model
oci_ai_vision_model:
# required
model_type: model_type_example
compartment_id: "ocid1.compartment.oc1..xxxxxxEXAMPLExxxxxx"
training_dataset:
# required
dataset_type: DATA_SCIENCE_LABELING
# optional
dataset_id: "ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx"
project_id: "ocid1.project.oc1..xxxxxxEXAMPLExxxxxx"
# optional
model_version: model_version_example
is_quick_mode: true
max_training_duration_in_hours: 3.4
testing_dataset:
# required
dataset_type: DATA_SCIENCE_LABELING
# optional
dataset_id: "ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx"
validation_dataset:
# required
dataset_type: DATA_SCIENCE_LABELING
# optional
dataset_id: "ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx"
display_name: display_name_example
description: description_example
freeform_tags: {'Department': 'Finance'}
defined_tags: {'Operations': {'CostCenter': 'US'}}
- name: Update model
oci_ai_vision_model:
# required
model_id: "ocid1.model.oc1..xxxxxxEXAMPLExxxxxx"
# optional
display_name: display_name_example
description: description_example
freeform_tags: {'Department': 'Finance'}
defined_tags: {'Operations': {'CostCenter': 'US'}}
- name: Update model using name (when environment variable OCI_USE_NAME_AS_IDENTIFIER is set)
oci_ai_vision_model:
# required
display_name: display_name_example
# optional
description: description_example
freeform_tags: {'Department': 'Finance'}
defined_tags: {'Operations': {'CostCenter': 'US'}}
- name: Delete model
oci_ai_vision_model:
# required
model_id: "ocid1.model.oc1..xxxxxxEXAMPLExxxxxx"
state: absent
- name: Delete model using name (when environment variable OCI_USE_NAME_AS_IDENTIFIER is set)
oci_ai_vision_model:
# required
display_name: display_name_example
state: absent
Return Values¶
Common return values are documented here, the following are the fields unique to this module:
Key | Returned | Description | ||
---|---|---|---|---|
model
complex
|
on success |
Details of the Model resource acted upon by the current operation
Sample:
{'average_precision': 3.4, 'compartment_id': 'ocid1.compartment.oc1..xxxxxxEXAMPLExxxxxx', 'confidence_threshold': 3.4, 'defined_tags': {'Operations': {'CostCenter': 'US'}}, 'description': 'description_example', 'display_name': 'display_name_example', 'freeform_tags': {'Department': 'Finance'}, 'id': 'ocid1.resource.oc1..xxxxxxEXAMPLExxxxxx', 'is_quick_mode': True, 'lifecycle_details': 'lifecycle_details_example', 'lifecycle_state': 'CREATING', 'max_training_duration_in_hours': 1.2, 'metrics': 'metrics_example', 'model_type': 'IMAGE_CLASSIFICATION', 'model_version': 'model_version_example', 'precision': 3.4, 'project_id': 'ocid1.project.oc1..xxxxxxEXAMPLExxxxxx', 'recall': 3.4, 'system_tags': {}, 'test_image_count': 56, 'testing_dataset': {'bucket_name': 'bucket_name_example', 'dataset_id': 'ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx', 'dataset_type': 'DATA_SCIENCE_LABELING', 'namespace_name': 'namespace_name_example', 'object_name': 'object_name_example'}, 'time_created': '2013-10-20T19:20:30+01:00', 'time_updated': '2013-10-20T19:20:30+01:00', 'total_image_count': 56, 'trained_duration_in_hours': 1.2, 'training_dataset': {'bucket_name': 'bucket_name_example', 'dataset_id': 'ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx', 'dataset_type': 'DATA_SCIENCE_LABELING', 'namespace_name': 'namespace_name_example', 'object_name': 'object_name_example'}, 'validation_dataset': {'bucket_name': 'bucket_name_example', 'dataset_id': 'ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx', 'dataset_type': 'DATA_SCIENCE_LABELING', 'namespace_name': 'namespace_name_example', 'object_name': 'object_name_example'}}
|
||
average_precision
float
|
on success |
The mean average precision of the trained model.
Sample:
3.4
|
||
compartment_id
string
|
on success |
The compartment identifier.
Sample:
ocid1.compartment.oc1..xxxxxxEXAMPLExxxxxx
|
||
confidence_threshold
float
|
on success |
The intersection over the union threshold used for calculating precision and recall.
Sample:
3.4
|
||
defined_tags
dictionary
|
on success |
Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: `{"foo-namespace": {"bar-key": "value"}}`
Sample:
{'Operations': {'CostCenter': 'US'}}
|
||
description
string
|
on success |
An optional description of the model.
Sample:
description_example
|
||
display_name
string
|
on success |
A human-friendly name for the model, which can be changed.
Sample:
display_name_example
|
||
freeform_tags
dictionary
|
on success |
A simple key-value pair that is applied without any predefined name, type, or scope. It exists for cross-compatibility only. For example: `{"bar-key": "value"}`
Sample:
{'Department': 'Finance'}
|
||
id
string
|
on success |
A unique identifier that is immutable after creation.
Sample:
ocid1.resource.oc1..xxxxxxEXAMPLExxxxxx
|
||
is_quick_mode
boolean
|
on success |
Set to true when experimenting with a new model type or dataset, so model training is quick, with a predefined low number of passes through the training data.
Sample:
True
|
||
lifecycle_details
string
|
on success |
A message describing the current state in more detail, that can provide actionable information if training failed.
Sample:
lifecycle_details_example
|
||
lifecycle_state
string
|
on success |
The current state of the model.
Sample:
CREATING
|
||
max_training_duration_in_hours
float
|
on success |
The maximum model training duration in hours, expressed as a decimal fraction.
Sample:
1.2
|
||
metrics
string
|
on success |
The complete set of per-label metrics for successfully trained models.
Sample:
metrics_example
|
||
model_type
string
|
on success |
What type of Vision model this is.
Sample:
IMAGE_CLASSIFICATION
|
||
model_version
string
|
on success |
The version of the model.
Sample:
model_version_example
|
||
precision
float
|
on success |
The precision of the trained model.
Sample:
3.4
|
||
project_id
string
|
on success |
The OCID of the project that contains the model.
Sample:
ocid1.project.oc1..xxxxxxEXAMPLExxxxxx
|
||
recall
float
|
on success |
Recall of the trained model.
Sample:
3.4
|
||
system_tags
dictionary
|
on success |
Usage of system tag keys. These predefined keys are scoped to namespaces. For example: `{"orcl-cloud": {"free-tier-retained": "true"}}`
|
||
test_image_count
integer
|
on success |
The number of images set aside for evaluating model performance metrics after training.
Sample:
56
|
||
testing_dataset
complex
|
on success |
|
||
bucket_name
string
|
on success |
The name of the Object Storage bucket that contains the input data file.
Sample:
bucket_name_example
|
||
dataset_id
string
|
on success |
OCID of the Data Labeling dataset.
Sample:
ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx
|
||
dataset_type
string
|
on success |
The dataset type, based on where it is stored.
Sample:
DATA_SCIENCE_LABELING
|
||
namespace_name
string
|
on success |
The namespace name of the Object Storage bucket that contains the input data file.
Sample:
namespace_name_example
|
||
object_name
string
|
on success |
The object name of the input data file.
Sample:
object_name_example
|
||
time_created
string
|
on success |
When the model was created, as an RFC3339 datetime string.
Sample:
2013-10-20T19:20:30+01:00
|
||
time_updated
string
|
on success |
When the model was updated, as an RFC3339 datetime string.
Sample:
2013-10-20T19:20:30+01:00
|
||
total_image_count
integer
|
on success |
The number of images in the dataset used to train, validate, and test the model.
Sample:
56
|
||
trained_duration_in_hours
float
|
on success |
The total hours actually used for model training.
Sample:
1.2
|
||
training_dataset
complex
|
on success |
|
||
bucket_name
string
|
on success |
The name of the Object Storage bucket that contains the input data file.
Sample:
bucket_name_example
|
||
dataset_id
string
|
on success |
OCID of the Data Labeling dataset.
Sample:
ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx
|
||
dataset_type
string
|
on success |
The dataset type, based on where it is stored.
Sample:
DATA_SCIENCE_LABELING
|
||
namespace_name
string
|
on success |
The namespace name of the Object Storage bucket that contains the input data file.
Sample:
namespace_name_example
|
||
object_name
string
|
on success |
The object name of the input data file.
Sample:
object_name_example
|
||
validation_dataset
complex
|
on success |
|
||
bucket_name
string
|
on success |
The name of the Object Storage bucket that contains the input data file.
Sample:
bucket_name_example
|
||
dataset_id
string
|
on success |
OCID of the Data Labeling dataset.
Sample:
ocid1.dataset.oc1..xxxxxxEXAMPLExxxxxx
|
||
dataset_type
string
|
on success |
The dataset type, based on where it is stored.
Sample:
DATA_SCIENCE_LABELING
|
||
namespace_name
string
|
on success |
The namespace name of the Object Storage bucket that contains the input data file.
Sample:
namespace_name_example
|
||
object_name
string
|
on success |
The object name of the input data file.
Sample:
object_name_example
|
Authors¶
Oracle (@oracle)