File: //proc/self/root/lib/mysqlsh/lib/python3.8/site-packages/oci/ai_vision/models/model.py
# coding: utf-8
# Copyright (c) 2016, 2025, Oracle and/or its affiliates. All rights reserved.
# This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license.
# NOTE: This class is auto generated by OracleSDKGenerator. DO NOT EDIT. API Version: 20220125
from oci.util import formatted_flat_dict, NONE_SENTINEL, value_allowed_none_or_none_sentinel # noqa: F401
from oci.decorators import init_model_state_from_kwargs
@init_model_state_from_kwargs
class Model(object):
"""
Machine-learned Model.
"""
#: A constant which can be used with the model_type property of a Model.
#: This constant has a value of "IMAGE_CLASSIFICATION"
MODEL_TYPE_IMAGE_CLASSIFICATION = "IMAGE_CLASSIFICATION"
#: A constant which can be used with the model_type property of a Model.
#: This constant has a value of "OBJECT_DETECTION"
MODEL_TYPE_OBJECT_DETECTION = "OBJECT_DETECTION"
#: A constant which can be used with the lifecycle_state property of a Model.
#: This constant has a value of "CREATING"
LIFECYCLE_STATE_CREATING = "CREATING"
#: A constant which can be used with the lifecycle_state property of a Model.
#: This constant has a value of "UPDATING"
LIFECYCLE_STATE_UPDATING = "UPDATING"
#: A constant which can be used with the lifecycle_state property of a Model.
#: This constant has a value of "ACTIVE"
LIFECYCLE_STATE_ACTIVE = "ACTIVE"
#: A constant which can be used with the lifecycle_state property of a Model.
#: This constant has a value of "DELETING"
LIFECYCLE_STATE_DELETING = "DELETING"
#: A constant which can be used with the lifecycle_state property of a Model.
#: This constant has a value of "DELETED"
LIFECYCLE_STATE_DELETED = "DELETED"
#: A constant which can be used with the lifecycle_state property of a Model.
#: This constant has a value of "FAILED"
LIFECYCLE_STATE_FAILED = "FAILED"
def __init__(self, **kwargs):
"""
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))
"""
self.swagger_types = {
'id': 'str',
'display_name': 'str',
'description': 'str',
'compartment_id': 'str',
'model_type': 'str',
'is_quick_mode': 'bool',
'max_training_duration_in_hours': 'float',
'trained_duration_in_hours': 'float',
'training_dataset': 'Dataset',
'testing_dataset': 'Dataset',
'validation_dataset': 'Dataset',
'model_version': 'str',
'project_id': 'str',
'time_created': 'datetime',
'time_updated': 'datetime',
'lifecycle_state': 'str',
'lifecycle_details': 'str',
'precision': 'float',
'recall': 'float',
'average_precision': 'float',
'confidence_threshold': 'float',
'total_image_count': 'int',
'test_image_count': 'int',
'metrics': 'str',
'freeform_tags': 'dict(str, str)',
'defined_tags': 'dict(str, dict(str, object))',
'system_tags': 'dict(str, dict(str, object))'
}
self.attribute_map = {
'id': 'id',
'display_name': 'displayName',
'description': 'description',
'compartment_id': 'compartmentId',
'model_type': 'modelType',
'is_quick_mode': 'isQuickMode',
'max_training_duration_in_hours': 'maxTrainingDurationInHours',
'trained_duration_in_hours': 'trainedDurationInHours',
'training_dataset': 'trainingDataset',
'testing_dataset': 'testingDataset',
'validation_dataset': 'validationDataset',
'model_version': 'modelVersion',
'project_id': 'projectId',
'time_created': 'timeCreated',
'time_updated': 'timeUpdated',
'lifecycle_state': 'lifecycleState',
'lifecycle_details': 'lifecycleDetails',
'precision': 'precision',
'recall': 'recall',
'average_precision': 'averagePrecision',
'confidence_threshold': 'confidenceThreshold',
'total_image_count': 'totalImageCount',
'test_image_count': 'testImageCount',
'metrics': 'metrics',
'freeform_tags': 'freeformTags',
'defined_tags': 'definedTags',
'system_tags': 'systemTags'
}
self._id = None
self._display_name = None
self._description = None
self._compartment_id = None
self._model_type = None
self._is_quick_mode = None
self._max_training_duration_in_hours = None
self._trained_duration_in_hours = None
self._training_dataset = None
self._testing_dataset = None
self._validation_dataset = None
self._model_version = None
self._project_id = None
self._time_created = None
self._time_updated = None
self._lifecycle_state = None
self._lifecycle_details = None
self._precision = None
self._recall = None
self._average_precision = None
self._confidence_threshold = None
self._total_image_count = None
self._test_image_count = None
self._metrics = None
self._freeform_tags = None
self._defined_tags = None
self._system_tags = None
@property
def id(self):
"""
**[Required]** Gets the id of this Model.
A unique identifier that is immutable after creation.
:return: The id of this Model.
:rtype: str
"""
return self._id
@id.setter
def id(self, id):
"""
Sets the id of this Model.
A unique identifier that is immutable after creation.
:param id: The id of this Model.
:type: str
"""
self._id = id
@property
def display_name(self):
"""
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
"""
return self._display_name
@display_name.setter
def display_name(self, display_name):
"""
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
"""
self._display_name = display_name
@property
def description(self):
"""
Gets the description of this Model.
An optional description of the model.
:return: The description of this Model.
:rtype: str
"""
return self._description
@description.setter
def description(self, description):
"""
Sets the description of this Model.
An optional description of the model.
:param description: The description of this Model.
:type: str
"""
self._description = description
@property
def compartment_id(self):
"""
**[Required]** Gets the compartment_id of this Model.
The compartment identifier.
:return: The compartment_id of this Model.
:rtype: str
"""
return self._compartment_id
@compartment_id.setter
def compartment_id(self, compartment_id):
"""
Sets the compartment_id of this Model.
The compartment identifier.
:param compartment_id: The compartment_id of this Model.
:type: str
"""
self._compartment_id = compartment_id
@property
def model_type(self):
"""
**[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
"""
return self._model_type
@model_type.setter
def model_type(self, model_type):
"""
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
"""
allowed_values = ["IMAGE_CLASSIFICATION", "OBJECT_DETECTION"]
if not value_allowed_none_or_none_sentinel(model_type, allowed_values):
model_type = 'UNKNOWN_ENUM_VALUE'
self._model_type = model_type
@property
def is_quick_mode(self):
"""
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
"""
return self._is_quick_mode
@is_quick_mode.setter
def is_quick_mode(self, is_quick_mode):
"""
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
"""
self._is_quick_mode = is_quick_mode
@property
def max_training_duration_in_hours(self):
"""
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
"""
return self._max_training_duration_in_hours
@max_training_duration_in_hours.setter
def max_training_duration_in_hours(self, max_training_duration_in_hours):
"""
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
"""
self._max_training_duration_in_hours = max_training_duration_in_hours
@property
def trained_duration_in_hours(self):
"""
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
"""
return self._trained_duration_in_hours
@trained_duration_in_hours.setter
def trained_duration_in_hours(self, trained_duration_in_hours):
"""
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
"""
self._trained_duration_in_hours = trained_duration_in_hours
@property
def training_dataset(self):
"""
**[Required]** Gets the training_dataset of this Model.
:return: The training_dataset of this Model.
:rtype: oci.ai_vision.models.Dataset
"""
return self._training_dataset
@training_dataset.setter
def training_dataset(self, training_dataset):
"""
Sets the training_dataset of this Model.
:param training_dataset: The training_dataset of this Model.
:type: oci.ai_vision.models.Dataset
"""
self._training_dataset = training_dataset
@property
def testing_dataset(self):
"""
Gets the testing_dataset of this Model.
:return: The testing_dataset of this Model.
:rtype: oci.ai_vision.models.Dataset
"""
return self._testing_dataset
@testing_dataset.setter
def testing_dataset(self, testing_dataset):
"""
Sets the testing_dataset of this Model.
:param testing_dataset: The testing_dataset of this Model.
:type: oci.ai_vision.models.Dataset
"""
self._testing_dataset = testing_dataset
@property
def validation_dataset(self):
"""
Gets the validation_dataset of this Model.
:return: The validation_dataset of this Model.
:rtype: oci.ai_vision.models.Dataset
"""
return self._validation_dataset
@validation_dataset.setter
def validation_dataset(self, validation_dataset):
"""
Sets the validation_dataset of this Model.
:param validation_dataset: The validation_dataset of this Model.
:type: oci.ai_vision.models.Dataset
"""
self._validation_dataset = validation_dataset
@property
def model_version(self):
"""
**[Required]** Gets the model_version of this Model.
The version of the model.
:return: The model_version of this Model.
:rtype: str
"""
return self._model_version
@model_version.setter
def model_version(self, model_version):
"""
Sets the model_version of this Model.
The version of the model.
:param model_version: The model_version of this Model.
:type: str
"""
self._model_version = model_version
@property
def project_id(self):
"""
**[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
"""
return self._project_id
@project_id.setter
def project_id(self, project_id):
"""
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
"""
self._project_id = project_id
@property
def time_created(self):
"""
**[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
"""
return self._time_created
@time_created.setter
def time_created(self, time_created):
"""
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
"""
self._time_created = time_created
@property
def time_updated(self):
"""
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
"""
return self._time_updated
@time_updated.setter
def time_updated(self, time_updated):
"""
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
"""
self._time_updated = time_updated
@property
def lifecycle_state(self):
"""
**[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
"""
return self._lifecycle_state
@lifecycle_state.setter
def lifecycle_state(self, lifecycle_state):
"""
Sets the lifecycle_state of this Model.
The current state of the model.
:param lifecycle_state: The lifecycle_state of this Model.
:type: str
"""
allowed_values = ["CREATING", "UPDATING", "ACTIVE", "DELETING", "DELETED", "FAILED"]
if not value_allowed_none_or_none_sentinel(lifecycle_state, allowed_values):
lifecycle_state = 'UNKNOWN_ENUM_VALUE'
self._lifecycle_state = lifecycle_state
@property
def lifecycle_details(self):
"""
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
"""
return self._lifecycle_details
@lifecycle_details.setter
def lifecycle_details(self, lifecycle_details):
"""
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
"""
self._lifecycle_details = lifecycle_details
@property
def precision(self):
"""
Gets the precision of this Model.
The precision of the trained model.
:return: The precision of this Model.
:rtype: float
"""
return self._precision
@precision.setter
def precision(self, precision):
"""
Sets the precision of this Model.
The precision of the trained model.
:param precision: The precision of this Model.
:type: float
"""
self._precision = precision
@property
def recall(self):
"""
Gets the recall of this Model.
Recall of the trained model.
:return: The recall of this Model.
:rtype: float
"""
return self._recall
@recall.setter
def recall(self, recall):
"""
Sets the recall of this Model.
Recall of the trained model.
:param recall: The recall of this Model.
:type: float
"""
self._recall = recall
@property
def average_precision(self):
"""
Gets the average_precision of this Model.
The mean average precision of the trained model.
:return: The average_precision of this Model.
:rtype: float
"""
return self._average_precision
@average_precision.setter
def average_precision(self, average_precision):
"""
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
"""
self._average_precision = average_precision
@property
def confidence_threshold(self):
"""
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
"""
return self._confidence_threshold
@confidence_threshold.setter
def confidence_threshold(self, confidence_threshold):
"""
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
"""
self._confidence_threshold = confidence_threshold
@property
def total_image_count(self):
"""
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
"""
return self._total_image_count
@total_image_count.setter
def total_image_count(self, total_image_count):
"""
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
"""
self._total_image_count = total_image_count
@property
def test_image_count(self):
"""
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
"""
return self._test_image_count
@test_image_count.setter
def test_image_count(self, test_image_count):
"""
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
"""
self._test_image_count = test_image_count
@property
def metrics(self):
"""
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
"""
return self._metrics
@metrics.setter
def metrics(self, metrics):
"""
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
"""
self._metrics = metrics
@property
def freeform_tags(self):
"""
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)
"""
return self._freeform_tags
@freeform_tags.setter
def freeform_tags(self, freeform_tags):
"""
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)
"""
self._freeform_tags = freeform_tags
@property
def defined_tags(self):
"""
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))
"""
return self._defined_tags
@defined_tags.setter
def defined_tags(self, defined_tags):
"""
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))
"""
self._defined_tags = defined_tags
@property
def system_tags(self):
"""
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))
"""
return self._system_tags
@system_tags.setter
def system_tags(self, system_tags):
"""
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))
"""
self._system_tags = system_tags
def __repr__(self):
return formatted_flat_dict(self)
def __eq__(self, other):
if other is None:
return False
return self.__dict__ == other.__dict__
def __ne__(self, other):
return not self == other