Data Source: oci_datascience_ml_application_implementation_versions

This data source provides the list of Ml Application Implementation Versions in Oracle Cloud Infrastructure Data Science service.

Returns a list of MlApplicationImplementationVersions.

Example Usage

data "oci_datascience_ml_application_implementation_versions" "test_ml_application_implementation_versions" {
	#Required
	ml_application_implementation_id = oci_datascience_ml_application_implementation.test_ml_application_implementation.id

	#Optional
	state = var.ml_application_implementation_version_state
}

Argument Reference

The following arguments are supported:

• ml_application_implementation_id - (Required) unique MlApplicationImplementation identifier
• state - (Optional) A filter to return only resources matching the given lifecycleState.

Attributes Reference

The following attributes are exported:

• ml_application_implementation_version_collection - The list of ml_application_implementation_version_collection.

MlApplicationImplementationVersion Reference

The following attributes are exported:

• allowed_migration_destinations - List of ML Application Implementation OCIDs for which migration from this implementation is allowed. Migration means that if consumers change implementation for their instances to implementation with OCID from this list, instance components will be updated in place otherwise new instance components are created based on the new implementation and old instance components are removed.
• application_components - List of application components (OCI resources shared for all MlApplicationInstances). These have been created automatically based on their definitions in the ML Application package.
  • application_id - OCID of Data Flow Application
  • component_name - Name of application component
  • id - OCID of the resource
  • job_id - OCID of Data Science Job
  • model_id - OCID of Data Science Model
  • name - Name of referenced resource (generally resources do not have to have any name but most resources have name exposed as ‘name’ or ‘displayName’ field).
  • pipeline_id - OCID of Data Science Pipeline
  • resource_type - Type of the resource
  • type - Type of application component
• configuration_schema - Schema of configuration which needs to be provided for each ML Application Instance. It is defined in the ML Application package descriptor.
  • default_value - The default value for the optional configuration property (it must not be specified for mandatory configuration properties)
  • description - Description of this configuration property
  • is_mandatory - If the value is true this configuration property is mandatory and visa versa. If not specified configuration property is optional.
  • key_name - Name of key (parameter name)
  • sample_value - Sample property value (it must match validationRegexp if it is specified)
  • validation_regexp - A regular expression will be used for the validation of property value.
  • value_type - Type of value
• defined_tags - Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}
• description - Description of ML Application Implementation defined in ML Application package descriptor
• freeform_tags - Free-form tags for this resource. Each tag is a simple key-value pair with no predefined name, type, or namespace. See Resource Tags. Example: {"Department": "Finance"}
• id - The OCID of the MlApplicationImplementationVersion. Unique identifier that is immutable after creation.
• lifecycle_details - A message describing the current state in more detail. For example, can be used to provide actionable information for a resource in Failed state.
• ml_application_id - The OCID of the ML Application implemented by this ML Application Implementation.
• ml_application_implementation_id - The OCID of the MlApplicationImplementation for which this resource keeps the historical state.
• ml_application_name - The name of ML Application (based on mlApplicationId)
• ml_application_package_arguments - List of ML Application package arguments provided during ML Application package upload.
  • arguments - Array of the ML Application package arguments
    • description - short description of the argument
    • is_mandatory - argument is mandatory or not
    • name - Argument name
    • type - type of the argument
    • value - Argument value
• name - ML Application Implementation name which is unique for given ML Application.
• package_version - The version of ML Application Package (e.g. “1.2” or “2.0.4”) defined in ML Application package descriptor. Value is not mandatory only for CREATING state otherwise it must be always presented.
• state - The current state of the MlApplicationImplementationVersion.
• system_tags - Usage of system tag keys. These predefined keys are scoped to namespaces. Example: {"orcl-cloud.free-tier-retained": "true"}
• time_created - Creation time of MlApplicationImplementationVersion in the format defined by RFC 3339.