oci_datascience_model

This resource provides the Model resource in Oracle Cloud Infrastructure Data Science service.

Creates a new model.

Example Usage

resource "oci_datascience_model" "test_model" {
	#Required
	compartment_id = var.compartment_id
	project_id = oci_datascience_project.test_project.id

	#Optional
	custom_metadata_list {

		#Optional
		category = var.model_custom_metadata_list_category
		description = var.model_custom_metadata_list_description
		key = var.model_custom_metadata_list_key
		value = var.model_custom_metadata_list_value
	}
	defined_metadata_list {

		#Optional
		category = var.model_defined_metadata_list_category
		description = var.model_defined_metadata_list_description
		key = var.model_defined_metadata_list_key
		value = var.model_defined_metadata_list_value
	}
	defined_tags = {"Operations.CostCenter"= "42"}
	description = var.model_description
	display_name = var.model_display_name
	freeform_tags = {"Department"= "Finance"}
	input_schema = var.model_input_schema
	output_schema = var.model_output_schema
}

Argument Reference

The following arguments are supported:

• compartment_id - (Required) (Updatable) The OCID of the compartment to create the model in.

• custom_metadata_list - (Optional) (Updatable) An array of custom metadata details for the model.

  • category - (Optional) (Updatable) 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 - (Optional) (Updatable) Description of model metadata

  • key - (Optional) (Updatable) 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 - (Optional) (Updatable) 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 - (Optional) (Updatable) An array of defined metadata details for the model.

  • category - (Optional) (Updatable) 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 - (Optional) (Updatable) Description of model metadata

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

• description - (Optional) (Updatable) A short description of the model.

• display_name - (Optional) (Updatable) A user-friendly display name for the resource. It does not have to be unique and can be modified. Avoid entering confidential information. Example: My Model

• freeform_tags - (Optional) (Updatable) 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"}

• input_schema - (Optional) Input schema file content in String format

• output_schema - (Optional) Output schema file content in String format

• project_id - (Required) The OCID of the project to associate with the model.

• model_artifact - (Optional) The model artifact to upload. It is a ZIP archive of the files necessary to run the model. This can be done in a separate step or using cli/sdk. The Model will remain in “Creating” state until its artifact is uploaded.

• artifact_content_disposition - (Optional) This allows to specify a filename during upload. This file name is used to dispose of the file contents while downloading the file. Example: attachment; filename=model-artifact.zip

• artifact_content_length - (Optional, Required if model_artifact is set) The content length of the model_artifact.

** IMPORTANT ** Any change to a property that does not support update will force the destruction and recreation of the resource with the new property values

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

Timeouts

The timeouts block allows you to specify timeouts for certain operations: * create - (Defaults to 20 minutes), when creating the Model * update - (Defaults to 20 minutes), when updating the Model * delete - (Defaults to 20 minutes), when destroying the Model

Import

Models can be imported using the id, e.g.

$ terraform import oci_datascience_model.test_model "id"