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a ���f�r � @ s8 d dl mZmZmZ d dlmZ eG dd� de��ZdS )� )�formatted_flat_dict� NONE_SENTINEL�#value_allowed_none_or_none_sentinel)� init_model_state_from_kwargsc @ s e Zd ZdZdZdZdZdZdZdZ dZ d Z d d � Z e d d � �Zejdd � �Ze dd� �Zejdd� �Ze dd� �Zejdd� �Ze dd� �Zejdd� �Ze dd� �Zejdd� �Ze dd � �Zejd d � �Ze d d � �Zejd d � �Ze d!d"� �Zejd#d"� �Ze d$d%� �Zejd&d%� �Ze d'd(� �Zejd)d(� �Ze d*d+� �Zejd,d+� �Ze d-d.� �Zejd/d.� �Ze d0d1� �Zejd2d1� �Ze d3d4� �Z e jd5d4� �Z e d6d7� �Z e jd8d7� �Z e d9d:� �Z e jd;d:� �Z e d<d=� �Z e jd>d=� �Z e d?d@� �Z e jdAd@� �Z e dBdC� �Z!e!jdDdC� �Z!e dEdF� �Z"e"jdGdF� �Z"e dHdI� �Z#e#jdJdI� �Z#e dKdL� �Z$e$jdMdL� �Z$e dNdO� �Z%e%jdPdO� �Z%e dQdR� �Z&e&jdSdR� �Z&e dTdU� �Z'e'jdVdU� �Z'e dWdX� �Z(e(jdYdX� �Z(e dZd[� �Z)e)jd\d[� �Z)d]d^� Z*d_d`� Z+dadb� Z,dcS )d�Modelz Machine-learned Model. �IMAGE_CLASSIFICATION�OBJECT_DETECTION�CREATING�UPDATING�ACTIVE�DELETING�DELETED�FAILEDc K s" dddddddddddddddddddddddddddd �| _ d d d d ddddddddddddddd d d d d d!d"d#d$d �| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _ d%| _ d%| _ d%| _ d%| _ d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _d%| _ d%S )&aD Initializes a new Model object with values from keyword arguments. The following keyword arguments are supported (corresponding to the getters/setters of this class): :param id: The value to assign to the id property of this Model. :type id: str :param display_name: The value to assign to the display_name property of this Model. :type display_name: str :param description: The value to assign to the description property of this Model. :type description: str :param compartment_id: The value to assign to the compartment_id property of this Model. :type compartment_id: str :param model_type: The value to assign to the model_type property of this Model. Allowed values for this property are: "IMAGE_CLASSIFICATION", "OBJECT_DETECTION", 'UNKNOWN_ENUM_VALUE'. Any unrecognized values returned by a service will be mapped to 'UNKNOWN_ENUM_VALUE'. :type model_type: str :param is_quick_mode: The value to assign to the is_quick_mode property of this Model. :type is_quick_mode: bool :param max_training_duration_in_hours: The value to assign to the max_training_duration_in_hours property of this Model. :type max_training_duration_in_hours: float :param trained_duration_in_hours: The value to assign to the trained_duration_in_hours property of this Model. :type trained_duration_in_hours: float :param training_dataset: The value to assign to the training_dataset property of this Model. :type training_dataset: oci.ai_vision.models.Dataset :param testing_dataset: The value to assign to the testing_dataset property of this Model. :type testing_dataset: oci.ai_vision.models.Dataset :param validation_dataset: The value to assign to the validation_dataset property of this Model. :type validation_dataset: oci.ai_vision.models.Dataset :param model_version: The value to assign to the model_version property of this Model. :type model_version: str :param project_id: The value to assign to the project_id property of this Model. :type project_id: str :param time_created: The value to assign to the time_created property of this Model. :type time_created: datetime :param time_updated: The value to assign to the time_updated property of this Model. :type time_updated: datetime :param lifecycle_state: The value to assign to the lifecycle_state property of this Model. Allowed values for this property are: "CREATING", "UPDATING", "ACTIVE", "DELETING", "DELETED", "FAILED", 'UNKNOWN_ENUM_VALUE'. Any unrecognized values returned by a service will be mapped to 'UNKNOWN_ENUM_VALUE'. :type lifecycle_state: str :param lifecycle_details: The value to assign to the lifecycle_details property of this Model. :type lifecycle_details: str :param precision: The value to assign to the precision property of this Model. :type precision: float :param recall: The value to assign to the recall property of this Model. :type recall: float :param average_precision: The value to assign to the average_precision property of this Model. :type average_precision: float :param confidence_threshold: The value to assign to the confidence_threshold property of this Model. :type confidence_threshold: float :param total_image_count: The value to assign to the total_image_count property of this Model. :type total_image_count: int :param test_image_count: The value to assign to the test_image_count property of this Model. :type test_image_count: int :param metrics: The value to assign to the metrics property of this Model. :type metrics: str :param freeform_tags: The value to assign to the freeform_tags property of this Model. :type freeform_tags: dict(str, str) :param defined_tags: The value to assign to the defined_tags property of this Model. :type defined_tags: dict(str, dict(str, object)) :param system_tags: The value to assign to the system_tags property of this Model. :type system_tags: dict(str, dict(str, object)) �str�bool�floatZDatasetZdatetime�intzdict(str, str)z dict(str, dict(str, object)))�id� display_name� description�compartment_id� model_type� is_quick_mode� max_training_duration_in_hours�trained_duration_in_hours�training_dataset�testing_dataset�validation_dataset� model_version� project_id� time_created� time_updated�lifecycle_state�lifecycle_details� precision�recall�average_precision�confidence_threshold�total_image_count�test_image_count�metrics� freeform_tags� defined_tags� system_tagsr Z displayNamer Z compartmentIdZ modelTypeZ isQuickModeZmaxTrainingDurationInHoursZtrainedDurationInHoursZtrainingDatasetZtestingDatasetZvalidationDatasetZ modelVersionZ projectIdZ timeCreatedZ timeUpdatedZlifecycleStateZlifecycleDetailsr$ r% ZaveragePrecisionZconfidenceThresholdZtotalImageCountZtestImageCountr* Z freeformTagsZ definedTagsZ systemTagsN) Z swagger_typesZ attribute_map�_id� _display_name� _description�_compartment_id� _model_type�_is_quick_mode� _max_training_duration_in_hours�_trained_duration_in_hours�_training_dataset�_testing_dataset�_validation_dataset�_model_version� _project_id� _time_created� _time_updated�_lifecycle_state�_lifecycle_details� _precision�_recall�_average_precision�_confidence_threshold�_total_image_count�_test_image_count�_metrics�_freeform_tags� _defined_tags� _system_tags)�self�kwargs� rK �>/usr/lib/python3.9/site-packages/oci/ai_vision/models/model.py�__init__2 s� w� � zModel.__init__c C s | j S )z� **[Required]** Gets the id of this Model. A unique identifier that is immutable after creation. :return: The id of this Model. :rtype: str �r. �rI rK rK rL r s zModel.idc C s || _ dS )z� Sets the id of this Model. A unique identifier that is immutable after creation. :param id: The id of this Model. :type: str NrN )rI r rK rK rL r s c C s | j S )z� Gets the display_name of this Model. A human-friendly name for the model, which can be changed. :return: The display_name of this Model. :rtype: str �r/ rO rK rK rL r s zModel.display_namec C s || _ dS )z� Sets the display_name of this Model. A human-friendly name for the model, which can be changed. :param display_name: The display_name of this Model. :type: str NrP )rI r rK rK rL r $ s c C s | j S )z� Gets the description of this Model. An optional description of the model. :return: The description of this Model. :rtype: str �r0 rO rK rK rL r 0 s zModel.descriptionc C s || _ dS )z� Sets the description of this Model. An optional description of the model. :param description: The description of this Model. :type: str NrQ )rI r rK rK rL r < s c C s | j S )z� **[Required]** Gets the compartment_id of this Model. The compartment identifier. :return: The compartment_id of this Model. :rtype: str �r1 rO rK rK rL r H s zModel.compartment_idc C s || _ dS )z� Sets the compartment_id of this Model. The compartment identifier. :param compartment_id: The compartment_id of this Model. :type: str NrR )rI r rK rK rL r T s c C s | j S )a� **[Required]** Gets the model_type of this Model. What type of Vision model this is. Allowed values for this property are: "IMAGE_CLASSIFICATION", "OBJECT_DETECTION", 'UNKNOWN_ENUM_VALUE'. Any unrecognized values returned by a service will be mapped to 'UNKNOWN_ENUM_VALUE'. :return: The model_type of this Model. :rtype: str )r2 rO rK rK rL r ` s zModel.model_typec C s ddg}t ||�sd}|| _dS )z� Sets the model_type of this Model. What type of Vision model this is. :param model_type: The model_type of this Model. :type: str r r �UNKNOWN_ENUM_VALUEN)r r2 )rI r �allowed_valuesrK rK rL r o s c C s | j S )a' Gets the is_quick_mode of this Model. 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. :return: The is_quick_mode of this Model. :rtype: bool �r3 rO rK rK rL r ~ s zModel.is_quick_modec C s || _ dS )a3 Sets the is_quick_mode of this Model. 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. :param is_quick_mode: The is_quick_mode of this Model. :type: bool NrU )rI r rK rK rL r � s c C s | j S )z� Gets the max_training_duration_in_hours of this Model. The maximum model training duration in hours, expressed as a decimal fraction. :return: The max_training_duration_in_hours of this Model. :rtype: float �r4 rO rK rK rL r � s z$Model.max_training_duration_in_hoursc C s || _ dS )a Sets the max_training_duration_in_hours of this Model. The maximum model training duration in hours, expressed as a decimal fraction. :param max_training_duration_in_hours: The max_training_duration_in_hours of this Model. :type: float NrV )rI r rK rK rL r � s c C s | j S )z� Gets the trained_duration_in_hours of this Model. The total hours actually used for model training. :return: The trained_duration_in_hours of this Model. :rtype: float �r5 rO rK rK rL r � s z Model.trained_duration_in_hoursc C s || _ dS )z� Sets the trained_duration_in_hours of this Model. The total hours actually used for model training. :param trained_duration_in_hours: The trained_duration_in_hours of this Model. :type: float NrW )rI r rK rK rL r � s c C s | j S )z� **[Required]** Gets the training_dataset of this Model. :return: The training_dataset of this Model. :rtype: oci.ai_vision.models.Dataset �r6 rO rK rK rL r � s zModel.training_datasetc C s || _ dS )z� Sets the training_dataset of this Model. :param training_dataset: The training_dataset of this Model. :type: oci.ai_vision.models.Dataset NrX )rI r rK rK rL r � s c C s | j S )z� Gets the testing_dataset of this Model. :return: The testing_dataset of this Model. :rtype: oci.ai_vision.models.Dataset �r7 rO rK rK rL r � s zModel.testing_datasetc C s || _ dS )z� Sets the testing_dataset of this Model. :param testing_dataset: The testing_dataset of this Model. :type: oci.ai_vision.models.Dataset NrY )rI r rK rK rL r � s c C s | j S )z� Gets the validation_dataset of this Model. :return: The validation_dataset of this Model. :rtype: oci.ai_vision.models.Dataset �r8 rO rK rK rL r � s zModel.validation_datasetc C s || _ dS )z� Sets the validation_dataset of this Model. :param validation_dataset: The validation_dataset of this Model. :type: oci.ai_vision.models.Dataset NrZ )rI r rK rK rL r � s c C s | j S )z� **[Required]** Gets the model_version of this Model. The version of the model. :return: The model_version of this Model. :rtype: str �r9 rO rK rK rL r s zModel.model_versionc C s || _ dS )z� Sets the model_version of this Model. The version of the model. :param model_version: The model_version of this Model. :type: str Nr[ )rI r rK rK rL r s c C s | j S )a **[Required]** Gets the project_id of this Model. The `OCID`__ of the project that contains the model. __ https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm :return: The project_id of this Model. :rtype: str �r: rO rK rK rL r s zModel.project_idc C s || _ dS )a Sets the project_id of this Model. The `OCID`__ of the project that contains the model. __ https://docs.cloud.oracle.com/iaas/Content/General/Concepts/identifiers.htm :param project_id: The project_id of this Model. :type: str Nr\ )rI r rK rK rL r ( s c C s | j S )z� **[Required]** Gets the time_created of this Model. When the model was created, as an RFC3339 datetime string. :return: The time_created of this Model. :rtype: datetime �r; rO rK rK rL r 6 s zModel.time_createdc C s || _ dS )z� Sets the time_created of this Model. When the model was created, as an RFC3339 datetime string. :param time_created: The time_created of this Model. :type: datetime Nr] )rI r rK rK rL r B s c C s | j S )z� Gets the time_updated of this Model. When the model was updated, as an RFC3339 datetime string. :return: The time_updated of this Model. :rtype: datetime �r< rO rK rK rL r! N s zModel.time_updatedc C s || _ dS )z� Sets the time_updated of this Model. When the model was updated, as an RFC3339 datetime string. :param time_updated: The time_updated of this Model. :type: datetime Nr^ )rI r! rK rK rL r! Z s c C s | j S )a� **[Required]** Gets the lifecycle_state of this Model. The current state of the model. Allowed values for this property are: "CREATING", "UPDATING", "ACTIVE", "DELETING", "DELETED", "FAILED", 'UNKNOWN_ENUM_VALUE'. Any unrecognized values returned by a service will be mapped to 'UNKNOWN_ENUM_VALUE'. :return: The lifecycle_state of this Model. :rtype: str )r= rO rK rK rL r" f s zModel.lifecycle_statec C s g d�}t ||�sd}|| _dS )z� Sets the lifecycle_state of this Model. The current state of the model. :param lifecycle_state: The lifecycle_state of this Model. :type: str )r r r r r r rS N)r r= )rI r" rT rK rK rL r" u s c C s | j S )a Gets the lifecycle_details of this Model. A message describing the current state in more detail, that can provide actionable information if training failed. :return: The lifecycle_details of this Model. :rtype: str �r> rO rK rK rL r# � s zModel.lifecycle_detailsc C s || _ dS )a Sets the lifecycle_details of this Model. A message describing the current state in more detail, that can provide actionable information if training failed. :param lifecycle_details: The lifecycle_details of this Model. :type: str Nr_ )rI r# rK rK rL r# � s c C s | j S )z� Gets the precision of this Model. The precision of the trained model. :return: The precision of this Model. :rtype: float �r? rO rK rK rL r$ � s zModel.precisionc C s || _ dS )z� Sets the precision of this Model. The precision of the trained model. :param precision: The precision of this Model. :type: float Nr` )rI r$ rK rK rL r$ � s c C s | j S )z� Gets the recall of this Model. Recall of the trained model. :return: The recall of this Model. :rtype: float �r@ rO rK rK rL r% � s z Model.recallc C s || _ dS )z� Sets the recall of this Model. Recall of the trained model. :param recall: The recall of this Model. :type: float Nra )rI r% rK rK rL r% � s c C s | j S )z� Gets the average_precision of this Model. The mean average precision of the trained model. :return: The average_precision of this Model. :rtype: float �rA rO rK rK rL r& � s zModel.average_precisionc C s || _ dS )z� Sets the average_precision of this Model. The mean average precision of the trained model. :param average_precision: The average_precision of this Model. :type: float Nrb )rI r& rK rK rL r& � s c C s | j S )z� Gets the confidence_threshold of this Model. The intersection over the union threshold used for calculating precision and recall. :return: The confidence_threshold of this Model. :rtype: float �rB rO rK rK rL r' � s zModel.confidence_thresholdc C s || _ dS )z� Sets the confidence_threshold of this Model. The intersection over the union threshold used for calculating precision and recall. :param confidence_threshold: The confidence_threshold of this Model. :type: float Nrc )rI r' rK rK rL r' � s c C s | j S )z� Gets the total_image_count of this Model. The number of images in the dataset used to train, validate, and test the model. :return: The total_image_count of this Model. :rtype: int �rC rO rK rK rL r( � s zModel.total_image_countc C s || _ dS )z� Sets the total_image_count of this Model. The number of images in the dataset used to train, validate, and test the model. :param total_image_count: The total_image_count of this Model. :type: int Nrd )rI r( rK rK rL r( s c C s | j S )z� Gets the test_image_count of this Model. The number of images set aside for evaluating model performance metrics after training. :return: The test_image_count of this Model. :rtype: int �rD rO rK rK rL r) s zModel.test_image_countc C s || _ dS )z� Sets the test_image_count of this Model. The number of images set aside for evaluating model performance metrics after training. :param test_image_count: The test_image_count of this Model. :type: int Nre )rI r) rK rK rL r) s c C s | j S )z� Gets the metrics of this Model. The complete set of per-label metrics for successfully trained models. :return: The metrics of this Model. :rtype: str �rE rO rK rK rL r* , s z Model.metricsc C s || _ dS )z� Sets the metrics of this Model. The complete set of per-label metrics for successfully trained models. :param metrics: The metrics of this Model. :type: str Nrf )rI r* rK rK rL r* 8 s c C s | j S )a; Gets the freeform_tags of this Model. 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"}` :return: The freeform_tags of this Model. :rtype: dict(str, str) �rF rO rK rK rL r+ D s zModel.freeform_tagsc C s || _ dS )aG Sets the freeform_tags of this Model. 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"}` :param freeform_tags: The freeform_tags of this Model. :type: dict(str, str) Nrg )rI r+ rK rK rL r+ Q s c C s | j S )a/ Gets the defined_tags of this Model. Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: `{"foo-namespace": {"bar-key": "value"}}` :return: The defined_tags of this Model. :rtype: dict(str, dict(str, object)) �rG rO rK rK rL r, ^ s zModel.defined_tagsc C s || _ dS )a: Sets the defined_tags of this Model. Defined tags for this resource. Each key is predefined and scoped to a namespace. For example: `{"foo-namespace": {"bar-key": "value"}}` :param defined_tags: The defined_tags of this Model. :type: dict(str, dict(str, object)) Nrh )rI r, rK rK rL r, k s c C s | j S )a, Gets the system_tags of this Model. Usage of system tag keys. These predefined keys are scoped to namespaces. For example: `{"orcl-cloud": {"free-tier-retained": "true"}}` :return: The system_tags of this Model. :rtype: dict(str, dict(str, object)) �rH rO rK rK rL r- x s zModel.system_tagsc C s || _ dS )a6 Sets the system_tags of this Model. Usage of system tag keys. These predefined keys are scoped to namespaces. For example: `{"orcl-cloud": {"free-tier-retained": "true"}}` :param system_tags: The system_tags of this Model. :type: dict(str, dict(str, object)) Nri )rI r- rK rK rL r- � s c C s t | �S �N)r rO rK rK rL �__repr__� s zModel.__repr__c C s |d u r dS | j |j kS )NF)�__dict__�rI �otherrK rK rL �__eq__� s z Model.__eq__c C s | |k S rj rK rm rK rK rL �__ne__� s z Model.__ne__N)-�__name__� __module__� __qualname__�__doc__Z MODEL_TYPE_IMAGE_CLASSIFICATIONZMODEL_TYPE_OBJECT_DETECTIONZLIFECYCLE_STATE_CREATINGZLIFECYCLE_STATE_UPDATINGZLIFECYCLE_STATE_ACTIVEZLIFECYCLE_STATE_DELETINGZLIFECYCLE_STATE_DELETEDZLIFECYCLE_STATE_FAILEDrM �propertyr �setterr r r r r r r r r r r r r r! r" r# r$ r% r& r' r( r) r* r+ r, r- rk ro rp rK rK rK rL r s� O r N)Zoci.utilr r r Zoci.decoratorsr �objectr rK rK rK rL �<module> s
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