Data Source: oci_datascience_model

This data source provides details about a specific Model resource in Oracle Cloud Infrastructure Data Science service.

Gets the specified model’s information.

Example Usage

data "oci_datascience_model" "test_model" {
	#Required
	model_id =oci_datascience_model.test_model.id
}

Argument Reference

The following arguments are supported:

• model_id - (Required) The OCID of the model.

Attributes Reference

The following attributes are exported:

• compartment_id - The OCID of the model’s compartment.

• created_by - The OCID of the user who created the model.

• custom_metadata_list - An array of custom metadata details for the model.

  • category - Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values “Performance,Training Profile,Training and Validation Datasets,Training Environment,other”.

  • description - Description of model metadata

  • key - Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults

  • value - Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

• defined_metadata_list - An array of defined metadata details for the model.

  • category - Category of model metadata which should be null for defined metadata.For custom metadata is should be one of the following values “Performance,Training Profile,Training and Validation Datasets,Training Environment,other”.

  • description - Description of model metadata

  • key - Key of the model Metadata. The key can either be user defined or Oracle Cloud Infrastructure defined. List of Oracle Cloud Infrastructure defined keys:

    • useCaseType
    • libraryName
    • libraryVersion
    • estimatorClass
    • hyperParameters
    • testartifactresults

  • value - Allowed values for useCaseType: binary_classification, regression, multinomial_classification, clustering, recommender, dimensionality_reduction/representation, time_series_forecasting, anomaly_detection, topic_modeling, ner, sentiment_analysis, image_classification, object_localization, other

    Allowed values for libraryName: scikit-learn, xgboost, tensorflow, pytorch, mxnet, keras, lightGBM, pymc3, pyOD, spacy, prophet, sktime, statsmodels, cuml, oracle_automl, h2o, transformers, nltk, emcee, pystan, bert, gensim, flair, word2vec, ensemble, other

• defined_tags - Defined tags for this resource. Each key is predefined and scoped to a namespace. See Resource Tags. Example: {"Operations.CostCenter": "42"}

• description - A short description of the model.

• display_name - A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information.

• 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 model.

• input_schema - Input schema file content in String format

• output_schema - Output schema file content in String format

• project_id - The OCID of the project associated with the model.

• state - The state of the model.

• time_created - The date and time the resource was created in the timestamp format defined by RFC3339. Example: 2019-08-25T21:10:29.41Z