diff options
Diffstat (limited to '.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets')
19 files changed, 2694 insertions, 0 deletions
diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/__init__.py new file mode 100644 index 00000000..5ee0f971 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/__init__.py @@ -0,0 +1,17 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +__path__ = __import__("pkgutil").extend_path(__path__, __name__) + + +from ._artifacts.artifact import Artifact +from ._artifacts.code import Code +from ._artifacts.data import Data +from ._artifacts.index import Index +from ._artifacts.model import Model +from .environment import Environment +from ._artifacts._package.model_package import ModelPackage +from .workspace_asset_reference import WorkspaceAssetReference + +__all__ = ["Artifact", "Model", "Code", "Data", "Index", "Environment", "WorkspaceAssetReference", "ModelPackage"] diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/__init__.py new file mode 100644 index 00000000..fdf8caba --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/__init__.py @@ -0,0 +1,5 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +__path__ = __import__("pkgutil").extend_path(__path__, __name__) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/__init__.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/__init__.py new file mode 100644 index 00000000..fdf8caba --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/__init__.py @@ -0,0 +1,5 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +__path__ = __import__("pkgutil").extend_path(__path__, __name__) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/base_environment_source.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/base_environment_source.py new file mode 100644 index 00000000..1be67144 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/base_environment_source.py @@ -0,0 +1,48 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +# pylint: disable=redefined-builtin + +from typing import Dict, Optional + +from azure.ai.ml._restclient.v2023_08_01_preview.models import BaseEnvironmentId as RestBaseEnvironmentId +from azure.ai.ml._schema.assets.package.base_environment_source import BaseEnvironmentSourceSchema +from azure.ai.ml._utils._experimental import experimental +from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY + + +@experimental +class BaseEnvironment: + """Base environment type. + + All required parameters must be populated in order to send to Azure. + + :param type: The type of the base environment. + :type type: str + :param resource_id: The resource id of the base environment. e.g. azureml:name:version + :type resource_id: str + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START base_env_entity_create] + :end-before: [END base_env_entity_create] + :language: python + :dedent: 8 + :caption: Create a Base Environment object. + """ + + def __init__(self, type: str, resource_id: Optional[str] = None): + self.type = type + self.resource_id = resource_id + + @classmethod + def _from_rest_object(cls, rest_obj: RestBaseEnvironmentId) -> "RestBaseEnvironmentId": + return BaseEnvironment(type=rest_obj.base_environment_source_type, resource_id=rest_obj.resource_id) + + def _to_dict(self) -> Dict: + return dict(BaseEnvironmentSourceSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self)) + + def _to_rest_object(self) -> RestBaseEnvironmentId: + return RestBaseEnvironmentId(base_environment_source_type=self.type, resource_id=self.resource_id) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/inferencing_server.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/inferencing_server.py new file mode 100644 index 00000000..6e685244 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/inferencing_server.py @@ -0,0 +1,216 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +# pylint: disable=protected-access,unused-argument + +from typing import Any, Optional + +from azure.ai.ml._restclient.v2023_02_01_preview.models import ( + AzureMLOnlineInferencingServer as RestAzureMLOnlineInferencingServer, +) +from azure.ai.ml._restclient.v2023_02_01_preview.models import CustomInferencingServer as RestCustomInferencingServer +from azure.ai.ml._restclient.v2023_02_01_preview.models import ( + OnlineInferenceConfiguration as RestOnlineInferenceConfiguration, +) +from azure.ai.ml._restclient.v2023_02_01_preview.models import Route as RestRoute +from azure.ai.ml._restclient.v2023_02_01_preview.models import TritonInferencingServer as RestTritonInferencingServer +from azure.ai.ml._restclient.v2023_08_01_preview.models import ( + AzureMLBatchInferencingServer as RestAzureMLBatchInferencingServer, +) +from azure.ai.ml._restclient.v2023_08_01_preview.models import ( + AzureMLOnlineInferencingServer as RestAzureMLOnlineInferencingServer, +) +from azure.ai.ml._utils._experimental import experimental + +from ...._deployment.code_configuration import CodeConfiguration + + +@experimental +class AzureMLOnlineInferencingServer: + """Azure ML online inferencing configurations. + + :param code_configuration: The code configuration of the inferencing server. + :type code_configuration: str + :ivar type: The type of the inferencing server. + """ + + def __init__(self, *, code_configuration: Optional[CodeConfiguration] = None, **kwargs: Any): + self.type = "azureml_online" + self.code_configuration = code_configuration + + @classmethod + def _from_rest_object(cls, rest_obj: RestAzureMLOnlineInferencingServer) -> "RestAzureMLOnlineInferencingServer": + return AzureMLOnlineInferencingServer(type=rest_obj.server_type, code_configuration=rest_obj.code_configuration) + + def _to_rest_object(self) -> RestAzureMLOnlineInferencingServer: + return RestAzureMLOnlineInferencingServer(server_type=self.type, code_configuration=self.code_configuration) + + +@experimental +class AzureMLBatchInferencingServer: + """Azure ML batch inferencing configurations. + + :param code_configuration: The code configuration of the inferencing server. + :type code_configuration: azure.ai.ml.entities.CodeConfiguration + :ivar type: The type of the inferencing server. + """ + + def __init__(self, *, code_configuration: Optional[CodeConfiguration] = None, **kwargs: Any): + self.type = "azureml_batch" + self.code_configuration = code_configuration + + @classmethod + def _from_rest_object(cls, rest_obj: RestAzureMLBatchInferencingServer) -> "RestAzureMLBatchInferencingServer": + return AzureMLBatchInferencingServer(code_configuration=rest_obj.code_configuration) + + def _to_rest_object(self) -> RestAzureMLBatchInferencingServer: + return RestAzureMLBatchInferencingServer(server_type=self.type, code_configuration=self.code_configuration) + + +@experimental +class TritonInferencingServer: + """Azure ML triton inferencing configurations. + + :param inference_configuration: The inference configuration of the inferencing server. + :type inference_configuration: azure.ai.ml.entities.CodeConfiguration + :ivar type: The type of the inferencing server. + """ + + def __init__(self, *, inference_configuration: Optional[CodeConfiguration] = None, **kwargs: Any): + self.type = "triton" + self.inference_configuration = inference_configuration + + @classmethod + def _from_rest_object(cls, rest_obj: RestTritonInferencingServer) -> "RestTritonInferencingServer": + return CustomInferencingServer( + type=rest_obj.server_type, inference_configuration=rest_obj.inference_configuration + ) + + def _to_rest_object(self) -> RestTritonInferencingServer: + return RestCustomInferencingServer(server_type=self.type, inference_configuration=self.inference_configuration) + + +@experimental +class Route: + """Route. + + :param port: The port of the route. + :type port: str + :param path: The path of the route. + :type path: str + """ + + def __init__(self, *, port: Optional[str] = None, path: Optional[str] = None): + self.port = port + self.path = path + + @classmethod + def _from_rest_object(cls, rest_obj: RestRoute) -> "RestRoute": + return Route(port=rest_obj.port, path=rest_obj.path) + + def _to_rest_object(self) -> Optional[RestRoute]: + return RestRoute(port=self.port, path=self.path) + + +@experimental +class OnlineInferenceConfiguration: + """Online inference configurations. + + :param liveness_route: The liveness route of the online inference configuration. + :type liveness_route: Route + :param readiness_route: The readiness route of the online inference configuration. + :type readiness_route: Route + :param scoring_route: The scoring route of the online inference configuration. + :type scoring_route: Route + :param entry_script: The entry script of the online inference configuration. + :type entry_script: str + :param configuration: The configuration of the online inference configuration. + :type configuration: dict + """ + + def __init__( + self, + liveness_route: Optional[Route] = None, + readiness_route: Optional[Route] = None, + scoring_route: Optional[Route] = None, + entry_script: Optional[str] = None, + configuration: Optional[dict] = None, + ): + self.liveness_route = liveness_route + self.readiness_route = readiness_route + self.scoring_route = scoring_route + self.entry_script = entry_script + self.configuration = configuration + + @classmethod + def _from_rest_object(cls, rest_obj: RestOnlineInferenceConfiguration) -> "RestOnlineInferenceConfiguration": + return OnlineInferenceConfiguration( + liveness_route=Route._from_rest_object(rest_obj.liveness_route), + readiness_route=Route._from_rest_object(rest_obj.readiness_route), + scoring_route=Route._from_rest_object(rest_obj.scoring_route), + entry_script=rest_obj.entry_script, + configuration=rest_obj.configuration, + ) + + def _to_rest_object(self) -> RestOnlineInferenceConfiguration: + if self.liveness_route is not None and self.readiness_route is not None and self.scoring_route is not None: + return RestOnlineInferenceConfiguration( + liveness_route=self.liveness_route._to_rest_object(), + readiness_route=self.readiness_route._to_rest_object(), + scoring_route=self.scoring_route._to_rest_object(), + entry_script=self.entry_script, + configuration=self.configuration, + ) + + if self.liveness_route is None: + return RestOnlineInferenceConfiguration( + readiness_route=self.readiness_route._to_rest_object() if self.readiness_route is not None else None, + scoring_route=self.scoring_route._to_rest_object() if self.scoring_route is not None else None, + entry_script=self.entry_script, + configuration=self.configuration, + ) + + if self.readiness_route is None: + return RestOnlineInferenceConfiguration( + liveness_route=self.liveness_route._to_rest_object(), + scoring_route=self.scoring_route._to_rest_object() if self.scoring_route is not None else None, + entry_script=self.entry_script, + configuration=self.configuration, + ) + + if self.scoring_route is None: + return RestOnlineInferenceConfiguration( + liveness_route=self.liveness_route._to_rest_object(), + readiness_route=self.readiness_route._to_rest_object(), + entry_script=self.entry_script, + configuration=self.configuration, + ) + + return RestOnlineInferenceConfiguration( + entry_script=self.entry_script, + configuration=self.configuration, + ) + + +@experimental +class CustomInferencingServer: + """Custom inferencing configurations. + + :param inference_configuration: The inference configuration of the inferencing server. + :type inference_configuration: OnlineInferenceConfiguration + :ivar type: The type of the inferencing server. + """ + + def __init__(self, *, inference_configuration: Optional[OnlineInferenceConfiguration] = None, **kwargs: Any): + self.type = "custom" + self.inference_configuration = inference_configuration + + @classmethod + def _from_rest_object(cls, rest_obj: RestCustomInferencingServer) -> "RestCustomInferencingServer": + return CustomInferencingServer( + type=rest_obj.server_type, inference_configuration=rest_obj.inference_configuration + ) + + def _to_rest_object(self) -> RestCustomInferencingServer: + return RestCustomInferencingServer(server_type=self.type, inference_configuration=self.inference_configuration) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/model_configuration.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/model_configuration.py new file mode 100644 index 00000000..73c777cf --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/model_configuration.py @@ -0,0 +1,55 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# ---------------------------------------------------------- + + +from typing import Optional + +from azure.ai.ml._exception_helper import log_and_raise_error +from azure.ai.ml._restclient.v2023_04_01_preview.models import ModelConfiguration as RestModelConfiguration +from azure.ai.ml._utils._experimental import experimental +from azure.ai.ml.exceptions import ErrorCategory, ErrorTarget, ValidationErrorType, ValidationException + + +@experimental +class ModelConfiguration: + """ModelConfiguration. + + :param mode: The mode of the model. Possible values include: "Copy", "Download". + :type mode: str + :param mount_path: The mount path of the model. + :type mount_path: str + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START model_configuration_entity_create] + :end-before: [END model_configuration_entity_create] + :language: python + :dedent: 8 + :caption: Creating a Model Configuration object. + """ + + def __init__(self, *, mode: Optional[str] = None, mount_path: Optional[str] = None): + self.mode = mode + self.mount_path = mount_path + + @classmethod + def _from_rest_object(cls, rest_obj: RestModelConfiguration) -> "ModelConfiguration": + return ModelConfiguration(mode=rest_obj.mode, mount_path=rest_obj.mount_path) + + def _to_rest_object(self) -> RestModelConfiguration: + self._validate() + return RestModelConfiguration(mode=self.mode, mount_path=self.mount_path) + + def _validate(self) -> None: + if self.mode is not None and self.mode.lower() not in ["copy", "download"]: + msg = "Mode must be either 'Copy' or 'Download'" + err = ValidationException( + message=msg, + target=ErrorTarget.MODEL, + no_personal_data_message=msg, + error_category=ErrorCategory.USER_ERROR, + error_type=ValidationErrorType.INVALID_VALUE, + ) + log_and_raise_error(err) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/model_package.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/model_package.py new file mode 100644 index 00000000..c4797c20 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/_package/model_package.py @@ -0,0 +1,338 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +# pylint: disable=protected-access, redefined-builtin + +import re +from os import PathLike +from pathlib import Path +from typing import IO, Any, AnyStr, Dict, List, Optional, Union + +from azure.ai.ml._restclient.v2023_08_01_preview.models import CodeConfiguration +from azure.ai.ml._restclient.v2023_08_01_preview.models import ModelPackageInput as RestModelPackageInput +from azure.ai.ml._restclient.v2023_08_01_preview.models import PackageInputPathId as RestPackageInputPathId +from azure.ai.ml._restclient.v2023_08_01_preview.models import PackageInputPathUrl as RestPackageInputPathUrl +from azure.ai.ml._restclient.v2023_08_01_preview.models import PackageInputPathVersion as RestPackageInputPathVersion +from azure.ai.ml._restclient.v2023_08_01_preview.models import PackageRequest, PackageResponse +from azure.ai.ml._schema.assets.package.model_package import ModelPackageSchema +from azure.ai.ml._utils._experimental import experimental +from azure.ai.ml._utils.utils import dump_yaml_to_file, snake_to_pascal +from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY, PARAMS_OVERRIDE_KEY +from azure.ai.ml.entities._resource import Resource +from azure.ai.ml.entities._util import load_from_dict + +from .base_environment_source import BaseEnvironment +from .inferencing_server import AzureMLBatchInferencingServer, AzureMLOnlineInferencingServer +from .model_configuration import ModelConfiguration + + +@experimental +class PackageInputPathId: + """Package input path specified with a resource ID. + + :param input_path_type: The type of the input path. Accepted values are "Url", "PathId", and "PathVersion". + :type input_path_type: Optional[str] + :param resource_id: The resource ID of the input path. e.g. "azureml://subscriptions/<>/resourceGroups/ + <>/providers/Microsoft.MachineLearningServices/workspaces/<>/data/<>/versions/<>". + :type resource_id: Optional[str] + """ + + def __init__( + self, + *, + input_path_type: Optional[str] = None, + resource_id: Optional[str] = None, + ) -> None: + self.input_path_type = input_path_type + self.resource_id = resource_id + + def _to_rest_object(self) -> RestPackageInputPathId: + return RestPackageInputPathId( + input_path_type=self.input_path_type, + resource_id=self.resource_id, + ) + + @classmethod + def _from_rest_object(cls, package_input_path_id_rest_object: RestPackageInputPathId) -> "PackageInputPathId": + return PackageInputPathId( + input_path_type=package_input_path_id_rest_object.input_path_type, + resource_id=package_input_path_id_rest_object.resource_id, + ) + + +@experimental +class PackageInputPathVersion: + """Package input path specified with a resource name and version. + + :param input_path_type: The type of the input path. Accepted values are "Url", "PathId", and "PathVersion". + :type input_path_type: Optional[str] + :param resource_name: The resource name of the input path. + :type resource_name: Optional[str] + :param resource_version: The resource version of the input path. + :type resource_version: Optional[str] + """ + + def __init__( + self, + *, + input_path_type: Optional[str] = None, + resource_name: Optional[str] = None, + resource_version: Optional[str] = None, + ) -> None: + self.input_path_type = input_path_type + self.resource_name = resource_name + self.resource_version = resource_version + + def _to_rest_object(self) -> RestPackageInputPathVersion: + return RestPackageInputPathVersion( + input_path_type=self.input_path_type, + resource_name=self.resource_name, + resource_version=self.resource_version, + ) + + @classmethod + def _from_rest_object( + cls, package_input_path_version_rest_object: RestPackageInputPathVersion + ) -> "PackageInputPathVersion": + return PackageInputPathVersion( + input_path_type=package_input_path_version_rest_object.input_path_type, + resource_name=package_input_path_version_rest_object.resource_name, + resource_version=package_input_path_version_rest_object.resource_version, + ) + + +@experimental +class PackageInputPathUrl: + """Package input path specified with a url. + + :param input_path_type: The type of the input path. Accepted values are "Url", "PathId", and "PathVersion". + :type input_path_type: Optional[str] + :param url: The url of the input path. e.g. "azureml://subscriptions/<>/resourceGroups/ + <>/providers/Microsoft.MachineLearningServices/workspaces/data/<>/versions/<>". + :type url: Optional[str] + """ + + def __init__(self, *, input_path_type: Optional[str] = None, url: Optional[str] = None) -> None: + self.input_path_type = input_path_type + self.url = url + + def _to_rest_object(self) -> RestPackageInputPathUrl: + return RestPackageInputPathUrl( + input_path_type=self.input_path_type, + url=self.url, + ) + + @classmethod + def _from_rest_object(cls, package_input_path_url_rest_object: RestPackageInputPathUrl) -> "PackageInputPathUrl": + return PackageInputPathUrl( + input_path_type=package_input_path_url_rest_object.input_path_type, + url=package_input_path_url_rest_object.url, + ) + + +@experimental +class ModelPackageInput: + """Model package input. + + :param type: The type of the input. + :type type: Optional[str] + :param path: The path of the input. + :type path: Optional[Union[~azure.ai.ml.entities.PackageInputPathId, ~azure.ai.ml.entities.PackageInputPathUrl, + ~azure.ai.ml.entities.PackageInputPathVersion]] + :param mode: The input mode. + :type mode: Optional[str] + :param mount_path: The mount path for the input. + :type mount_path: Optional[str] + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START model_package_input_entity_create] + :end-before: [END model_package_input_entity_create] + :language: python + :dedent: 8 + :caption: Create a Model Package Input object. + """ + + def __init__( + self, + *, + type: Optional[str] = None, + path: Optional[Union[PackageInputPathId, PackageInputPathUrl, PackageInputPathVersion]] = None, + mode: Optional[str] = None, + mount_path: Optional[str] = None, + ) -> None: + self.type = type + self.path = path + self.mode = mode + self.mount_path = mount_path + + def _to_rest_object(self) -> RestModelPackageInput: + if self.path is None: + return RestModelPackageInput( + input_type=snake_to_pascal(self.type), + path=None, + mode=snake_to_pascal(self.mode), + mount_path=self.mount_path, + ) + return RestModelPackageInput( + input_type=snake_to_pascal(self.type), + path=self.path._to_rest_object(), + mode=snake_to_pascal(self.mode), + mount_path=self.mount_path, + ) + + @classmethod + def _from_rest_object(cls, model_package_input_rest_object: RestModelPackageInput) -> "ModelPackageInput": + return ModelPackageInput( + type=model_package_input_rest_object.input_type, + path=model_package_input_rest_object.path._from_rest_object(), + mode=model_package_input_rest_object.mode, + mount_path=model_package_input_rest_object.mount_path, + ) + + +@experimental +class ModelPackage(Resource, PackageRequest): + """Model package. + + :param target_environment_name: The target environment name for the model package. + :type target_environment_name: str + :param inferencing_server: The inferencing server of the model package. + :type inferencing_server: Union[~azure.ai.ml.entities.AzureMLOnlineInferencingServer, + ~azure.ai.ml.entities.AzureMLBatchInferencingServer] + :param base_environment_source: The base environment source of the model package. + :type base_environment_source: Optional[~azure.ai.ml.entities.BaseEnvironment] + :param target_environment_version: The version of the model package. + :type target_environment_version: Optional[str] + :param environment_variables: The environment variables of the model package. + :type environment_variables: Optional[dict[str, str]] + :param inputs: The inputs of the model package. + :type inputs: Optional[list[~azure.ai.ml.entities.ModelPackageInput]] + :param model_configuration: The model configuration. + :type model_configuration: Optional[~azure.ai.ml.entities.ModelConfiguration] + :param tags: The tags of the model package. + :type tags: Optional[dict[str, str]] + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START model_package_entity_create] + :end-before: [END model_package_entity_create] + :language: python + :dedent: 8 + :caption: Create a Model Package object. + """ + + def __init__( + self, + *, + target_environment: Union[str, Dict[str, str]], + inferencing_server: Union[AzureMLOnlineInferencingServer, AzureMLBatchInferencingServer], + base_environment_source: Optional[BaseEnvironment] = None, + environment_variables: Optional[Dict[str, str]] = None, + inputs: Optional[List[ModelPackageInput]] = None, + model_configuration: Optional[ModelConfiguration] = None, + tags: Optional[Dict[str, str]] = None, + **kwargs: Any, + ): + if isinstance(target_environment, dict): + target_environment = target_environment["name"] + env_version = None + else: + parse_id = re.match(r"azureml:(\w+):(\d+)$", target_environment) + + if parse_id: + target_environment = parse_id.group(1) + env_version = parse_id.group(2) + else: + env_version = None + + super().__init__( + name=target_environment, + target_environment_id=target_environment, + base_environment_source=base_environment_source, + inferencing_server=inferencing_server, + model_configuration=model_configuration, + inputs=inputs, + tags=tags, + environment_variables=environment_variables, + ) + self.environment_version = env_version + + @classmethod + def _load( + cls, + data: Optional[Dict] = None, + yaml_path: Optional[Union[PathLike, str]] = None, + params_override: Optional[list] = None, + **kwargs: Any, + ) -> "ModelPackage": + params_override = params_override or [] + data = data or {} + context = { + BASE_PATH_CONTEXT_KEY: Path(yaml_path).parent if yaml_path else Path("./"), + PARAMS_OVERRIDE_KEY: params_override, + } + res: ModelPackage = load_from_dict(ModelPackageSchema, data, context, **kwargs) + return res + + def dump( + self, + dest: Union[str, PathLike, IO[AnyStr]], + **kwargs: Any, + ) -> None: + """Dumps the job content into a file in YAML format. + + :param dest: The local path or file stream to write the YAML content to. + If dest is a file path, a new file will be created. + If dest is an open file, the file will be written to directly. + :type dest: Union[PathLike, str, IO[AnyStr]] + :raises FileExistsError: Raised if dest is a file path and the file already exists. + :raises IOError: Raised if dest is an open file and the file is not writable. + """ + yaml_serialized = self._to_dict() + dump_yaml_to_file(dest, yaml_serialized, default_flow_style=False) + + def _to_dict(self) -> Dict: + return dict(ModelPackageSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self)) + + @classmethod + def _from_rest_object(cls, model_package_rest_object: PackageResponse) -> Any: + target_environment_id = model_package_rest_object.target_environment_id + return target_environment_id + + def _to_rest_object(self) -> PackageRequest: + code = None + + if ( + self.inferencing_server + and hasattr(self.inferencing_server, "code_configuration") + and self.inferencing_server.code_configuration + ): + self.inferencing_server.code_configuration._validate() + code_id = ( + self.inferencing_server.code_configuration.code + if isinstance(self.inferencing_server.code_configuration.code, str) + else self.inferencing_server.code_configuration.code.id + ) + code = CodeConfiguration( + code_id=code_id, + scoring_script=self.inferencing_server.code_configuration.scoring_script, + ) + self.inferencing_server.code_configuration = code + + package_request = PackageRequest( + target_environment_id=self.target_environment_id, + base_environment_source=( + self.base_environment_source._to_rest_object() if self.base_environment_source else None + ), + inferencing_server=self.inferencing_server._to_rest_object() if self.inferencing_server else None, + model_configuration=self.model_configuration._to_rest_object() if self.model_configuration else None, + inputs=[input._to_rest_object() for input in self.inputs] if self.inputs else None, + tags=self.tags, + environment_variables=self.environment_variables, + ) + + return package_request diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/artifact.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/artifact.py new file mode 100644 index 00000000..f82e2aa0 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/artifact.py @@ -0,0 +1,131 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- +from abc import abstractmethod +from os import PathLike +from pathlib import Path, PurePosixPath +from typing import Any, Dict, Optional, Union +from urllib.parse import urljoin + +from azure.ai.ml._utils.utils import is_mlflow_uri, is_url +from azure.ai.ml.entities._assets.asset import Asset + + +class ArtifactStorageInfo: + def __init__( + self, + name: str, + version: str, + relative_path: str, + datastore_arm_id: Optional[str], + container_name: str, + storage_account_url: Optional[str] = None, + is_file: Optional[bool] = None, + indicator_file: Optional[str] = None, + ): + self.name = name + self.version = version + self.relative_path = relative_path + self.datastore_arm_id = datastore_arm_id + self.container_name = container_name + self.storage_account_url = storage_account_url + self.is_file = is_file + self.indicator_file = indicator_file + + @property + def full_storage_path(self) -> Optional[str]: + if self.storage_account_url is None: + return f"{self.container_name}/{self.relative_path}" + return urljoin(self.storage_account_url, f"{self.container_name}/{self.relative_path}") + + @property + def subdir_path(self) -> Optional[str]: + if self.is_file: + path = PurePosixPath(self.relative_path).parent + if self.storage_account_url is None: + return f"{self.container_name}/{path}" + return urljoin(self.storage_account_url, f"{self.container_name}/{path}") + return self.full_storage_path + + +class Artifact(Asset): + """Base class for artifact, can't be instantiated directly. + + :param name: Name of the resource. + :type name: str + :param version: Version of the resource. + :type version: str + :param path: The local or remote path to the asset. + :type path: Union[str, os.PathLike] + :param description: Description of the resource. + :type description: str + :param tags: Tag dictionary. Tags can be added, removed, and updated. + :type tags: dict[str, str] + :param properties: The asset property dictionary. + :type properties: dict[str, str] + :param datastore: The datastore to upload the local artifact to. + :type datastore: str + :param kwargs: A dictionary of additional configuration parameters. + :type kwargs: dict + """ + + def __init__( + self, + name: Optional[str] = None, + version: Optional[str] = None, + description: Optional[str] = None, + tags: Optional[Dict] = None, + properties: Optional[Dict] = None, + path: Optional[Union[str, PathLike]] = None, + datastore: Optional[str] = None, + **kwargs: Any, + ): + super().__init__( + name=name, + version=version, + description=description, + tags=tags, + properties=properties, + **kwargs, + ) + self.path = path + self.datastore = datastore + + @property + def path(self) -> Optional[Union[str, PathLike]]: + return self._path + + @path.setter + def path(self, value: Optional[Union[str, PathLike]]) -> None: + if not value or is_url(value) or Path(value).is_absolute() or is_mlflow_uri(value): + self._path = value + else: + self._path = Path(self.base_path, value).resolve() + + @abstractmethod + def _to_dict(self) -> Dict: + pass + + def __eq__(self, other: Any) -> bool: + return ( + type(self) == type(other) # pylint: disable = unidiomatic-typecheck + and self.name == other.name + and self.id == other.id + and self.version == other.version + and self.description == other.description + and self.tags == other.tags + and self.properties == other.properties + and self.base_path == other.base_path + and self._is_anonymous == other._is_anonymous + ) + + def __ne__(self, other: Any) -> bool: + return not self.__eq__(other) + + @abstractmethod + def _update_path(self, asset_artifact: ArtifactStorageInfo) -> None: + """Updates an an artifact with the remote path of a local upload. + + :param asset_artifact: The asset storage info of the artifact + :type asset_artifact: ArtifactStorageInfo + """ diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/code.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/code.py new file mode 100644 index 00000000..b08149ab --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/code.py @@ -0,0 +1,142 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- +import os +from os import PathLike +from pathlib import Path +from typing import Any, Dict, Optional, Union + +from azure.ai.ml._restclient.v2022_05_01.models import CodeVersionData, CodeVersionDetails +from azure.ai.ml._schema import CodeAssetSchema +from azure.ai.ml._utils._arm_id_utils import AMLVersionedArmId +from azure.ai.ml._utils._asset_utils import IgnoreFile, get_content_hash, get_content_hash_version, get_ignore_file +from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY, PARAMS_OVERRIDE_KEY, ArmConstants +from azure.ai.ml.entities._assets import Artifact +from azure.ai.ml.entities._system_data import SystemData +from azure.ai.ml.entities._util import load_from_dict + +from .artifact import ArtifactStorageInfo + + +class Code(Artifact): + """Code for training and scoring. + + :param name: Name of the resource. + :type name: str + :param version: Version of the resource. + :type version: str + :param path: A local path or a remote uri. A datastore remote uri example is like, + "azureml://subscriptions/{}/resourcegroups/{}/workspaces/{}/datastores/{}/paths/path_on_datastore/" + :type path: str + :param description: Description of the resource. + :type description: str + :param tags: Tag dictionary. Tags can be added, removed, and updated. + :type tags: dict[str, str] + :param properties: The asset property dictionary. + :type properties: dict[str, str] + :param ignore_file: Ignore file for the resource. + :type ignore_file: IgnoreFile + :param kwargs: A dictionary of additional configuration parameters. + :type kwargs: dict + """ + + def __init__( + self, + *, + name: Optional[str] = None, + version: Optional[str] = None, + description: Optional[str] = None, + tags: Optional[Dict] = None, + properties: Optional[Dict] = None, + path: Optional[Union[str, PathLike]] = None, + ignore_file: Optional[IgnoreFile] = None, + **kwargs: Any, + ): + super().__init__( + name=name, + version=version, + description=description, + tags=tags, + properties=properties, + path=path, + **kwargs, + ) + self._arm_type = ArmConstants.CODE_VERSION_TYPE + if self.path and os.path.isabs(self.path): + # Only calculate hash for local files + self._ignore_file = get_ignore_file(self.path) if ignore_file is None else ignore_file + self._hash_sha256 = get_content_hash(self.path, self._ignore_file) + + @classmethod + def _load( + cls, + data: Optional[Dict] = None, + yaml_path: Optional[Union[PathLike, str]] = None, + params_override: Optional[list] = None, + **kwargs: Any, + ) -> "Code": + data = data or {} + params_override = params_override or [] + context = { + BASE_PATH_CONTEXT_KEY: Path(yaml_path).parent if yaml_path else Path("./"), + PARAMS_OVERRIDE_KEY: params_override, + } + res: Code = load_from_dict(CodeAssetSchema, data, context, **kwargs) + return res + + def _to_dict(self) -> Dict: + res: dict = CodeAssetSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self) + return res + + @classmethod + def _from_rest_object(cls, code_rest_object: CodeVersionData) -> "Code": + rest_code_version: CodeVersionDetails = code_rest_object.properties + arm_id = AMLVersionedArmId(arm_id=code_rest_object.id) + code = Code( + id=code_rest_object.id, + name=arm_id.asset_name, + version=arm_id.asset_version, + path=rest_code_version.code_uri, + description=rest_code_version.description, + tags=rest_code_version.tags, + properties=rest_code_version.properties, + # pylint: disable=protected-access + creation_context=SystemData._from_rest_object(code_rest_object.system_data), + is_anonymous=rest_code_version.is_anonymous, + ) + return code + + def _to_rest_object(self) -> CodeVersionData: + properties = {} + if hasattr(self, "_hash_sha256"): + properties["hash_sha256"] = self._hash_sha256 + properties["hash_version"] = get_content_hash_version() + code_version = CodeVersionDetails(code_uri=self.path, is_anonymous=self._is_anonymous, properties=properties) + code_version_resource = CodeVersionData(properties=code_version) + + return code_version_resource + + def _update_path(self, asset_artifact: ArtifactStorageInfo) -> None: + """Update an artifact with the remote path of a local upload. + + :param asset_artifact: The asset storage info of the artifact + :type asset_artifact: ArtifactStorageInfo + """ + if asset_artifact.is_file: + # Code paths cannot be pointers to single files. It must be a pointer to a container + # Skipping the setter to avoid being resolved as a local path + self._path = asset_artifact.subdir_path # pylint: disable=attribute-defined-outside-init + else: + self._path = asset_artifact.full_storage_path # pylint: disable=attribute-defined-outside-init + + # pylint: disable=unused-argument + def _to_arm_resource_param(self, **kwargs: Any) -> Dict: + properties = self._to_rest_object().properties + + return { + self._arm_type: { + ArmConstants.NAME: self.name, + ArmConstants.VERSION: self.version, + ArmConstants.PROPERTIES_PARAMETER_NAME: self._serialize.body(properties, "CodeVersionDetails"), + } + } diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/data.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/data.py new file mode 100644 index 00000000..710e959a --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/data.py @@ -0,0 +1,237 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +# pylint: disable=protected-access + +import os +import re +from os import PathLike +from pathlib import Path +from typing import Any, Dict, List, Optional, Tuple, Type, Union + +from azure.ai.ml._exception_helper import log_and_raise_error +from azure.ai.ml._restclient.v2023_04_01_preview.models import ( + DataContainer, + DataContainerProperties, + DataType, + DataVersionBase, + DataVersionBaseProperties, + MLTableData, + UriFileDataVersion, + UriFolderDataVersion, +) +from azure.ai.ml._schema import DataSchema +from azure.ai.ml._utils._arm_id_utils import get_arm_id_object_from_id +from azure.ai.ml._utils.utils import is_url +from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY, PARAMS_OVERRIDE_KEY, SHORT_URI_FORMAT, AssetTypes +from azure.ai.ml.entities._assets import Artifact +from azure.ai.ml.entities._system_data import SystemData +from azure.ai.ml.entities._util import load_from_dict +from azure.ai.ml.exceptions import ErrorCategory, ErrorTarget, ValidationErrorType, ValidationException + +from .artifact import ArtifactStorageInfo + +DataAssetTypeModelMap: Dict[str, Type[DataVersionBaseProperties]] = { + AssetTypes.URI_FILE: UriFileDataVersion, + AssetTypes.URI_FOLDER: UriFolderDataVersion, + AssetTypes.MLTABLE: MLTableData, +} + + +def getModelForDataAssetType(data_asset_type: str) -> Optional[Type[DataVersionBaseProperties]]: + model = DataAssetTypeModelMap.get(data_asset_type) + if model is None: + msg = "Unknown DataType {}".format(data_asset_type) + err = ValidationException( + message=msg, + no_personal_data_message=msg, + error_type=ValidationErrorType.INVALID_VALUE, + target=ErrorTarget.DATA, + error_category=ErrorCategory.USER_ERROR, + ) + log_and_raise_error(err) + return model + + +DataTypeMap: Dict[DataType, str] = { + DataType.URI_FILE: AssetTypes.URI_FILE, + DataType.URI_FOLDER: AssetTypes.URI_FOLDER, + DataType.MLTABLE: AssetTypes.MLTABLE, +} + + +def getDataAssetType(data_type: DataType) -> str: + return DataTypeMap.get(data_type, data_type) # pass through value if no match found + + +class Data(Artifact): + """Data for training and scoring. + + :param name: Name of the resource. + :type name: str + :param version: Version of the resource. + :type version: str + :param description: Description of the resource. + :type description: str + :param tags: Tag dictionary. Tags can be added, removed, and updated. + :type tags: dict[str, str] + :param properties: The asset property dictionary. + :type properties: dict[str, str] + :param path: The path to the asset on the datastore. This can be local or remote + :type path: str + :param type: The type of the asset. Valid values are uri_file, uri_folder, mltable. Defaults to uri_folder. + :type type: Literal[AssetTypes.URI_FILE, AssetTypes.URI_FOLDER, AssetTypes.MLTABLE] + :param kwargs: A dictionary of additional configuration parameters. + :type kwargs: dict + """ + + def __init__( + self, + *, + name: Optional[str] = None, + version: Optional[str] = None, + description: Optional[str] = None, + tags: Optional[Dict] = None, + properties: Optional[Dict] = None, + path: Optional[str] = None, # if type is mltable, the path has to be a folder. + type: str = AssetTypes.URI_FOLDER, # pylint: disable=redefined-builtin + **kwargs: Any, + ): + self._path: Optional[Union[Path, str, PathLike]] = None + + self._skip_validation = kwargs.pop("skip_validation", False) + self._mltable_schema_url = kwargs.pop("mltable_schema_url", None) + self._referenced_uris = kwargs.pop("referenced_uris", None) + self.type = type + super().__init__( + name=name, + version=version, + path=path, + description=description, + tags=tags, + properties=properties, + **kwargs, + ) + self.path = path + + @property + def path(self) -> Optional[Union[Path, str, PathLike]]: + return self._path + + @path.setter + def path(self, value: str) -> None: + # Call the parent setter to resolve the path with base_path if it was a local path + # TODO: Bug Item number: 2883424 + super(Data, type(self)).path.fset(self, value) # type: ignore + if self.type == AssetTypes.URI_FOLDER and self._path is not None and not is_url(self._path): + self._path = Path(os.path.join(self._path, "")) + + @classmethod + def _load( + cls, + data: Optional[Dict] = None, + yaml_path: Optional[Union[PathLike, str]] = None, + params_override: Optional[list] = None, + **kwargs: Any, + ) -> "Data": + data = data or {} + params_override = params_override or [] + context = { + BASE_PATH_CONTEXT_KEY: Path(yaml_path).parent if yaml_path else Path("./"), + PARAMS_OVERRIDE_KEY: params_override, + } + data_asset = Data._load_from_dict(yaml_data=data, context=context, **kwargs) + + return data_asset + + @classmethod + def _load_from_dict(cls, yaml_data: Dict, context: Dict, **kwargs: Any) -> "Data": + return Data(**load_from_dict(DataSchema, yaml_data, context, **kwargs)) + + def _to_dict(self) -> Dict: + res: dict = DataSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self) + return res + + def _to_container_rest_object(self) -> DataContainer: + VersionDetailsClass = getModelForDataAssetType(self.type) + return DataContainer( + properties=DataContainerProperties( + properties=self.properties, + tags=self.tags, + is_archived=False, + data_type=VersionDetailsClass.data_type if VersionDetailsClass is not None else None, + ) + ) + + def _to_rest_object(self) -> Optional[DataVersionBase]: + VersionDetailsClass = getModelForDataAssetType(self.type) + if VersionDetailsClass is not None: + data_version_details = VersionDetailsClass( + description=self.description, + is_anonymous=self._is_anonymous, + tags=self.tags, + is_archived=False, + properties=self.properties, + data_uri=self.path, + auto_delete_setting=self.auto_delete_setting, + ) + if VersionDetailsClass._attribute_map.get("referenced_uris") is not None: + data_version_details.referenced_uris = self._referenced_uris + return DataVersionBase(properties=data_version_details) + + return None + + @classmethod + def _from_container_rest_object(cls, data_container_rest_object: DataContainer) -> "Data": + data_rest_object_details: DataContainerProperties = data_container_rest_object.properties + data = Data( + name=data_container_rest_object.name, + creation_context=SystemData._from_rest_object(data_container_rest_object.system_data), + tags=data_rest_object_details.tags, + properties=data_rest_object_details.properties, + type=getDataAssetType(data_rest_object_details.data_type), + ) + data.latest_version = data_rest_object_details.latest_version + return data + + @classmethod + def _from_rest_object(cls, data_rest_object: DataVersionBase) -> "Data": + data_rest_object_details: DataVersionBaseProperties = data_rest_object.properties + arm_id_object = get_arm_id_object_from_id(data_rest_object.id) + path = data_rest_object_details.data_uri + data = Data( + id=data_rest_object.id, + name=arm_id_object.asset_name, + version=arm_id_object.asset_version, + path=path, + type=getDataAssetType(data_rest_object_details.data_type), + description=data_rest_object_details.description, + tags=data_rest_object_details.tags, + properties=data_rest_object_details.properties, + creation_context=SystemData._from_rest_object(data_rest_object.system_data), + is_anonymous=data_rest_object_details.is_anonymous, + referenced_uris=getattr(data_rest_object_details, "referenced_uris", None), + auto_delete_setting=getattr(data_rest_object_details, "auto_delete_setting", None), + ) + return data + + @classmethod + def _resolve_cls_and_type(cls, data: Dict, params_override: Optional[List[Dict]] = None) -> Tuple: + from azure.ai.ml.entities._data_import.data_import import DataImport + + if "source" in data: + return DataImport, None + + return cls, None + + def _update_path(self, asset_artifact: ArtifactStorageInfo) -> None: + regex = r"datastores\/(.+)" + # datastore_arm_id is null for registry scenario, so capture the full_storage_path + if not asset_artifact.datastore_arm_id and asset_artifact.full_storage_path: + self.path = asset_artifact.full_storage_path + else: + groups = re.search(regex, asset_artifact.datastore_arm_id) # type: ignore + if groups: + datastore_name = groups.group(1) + self.path = SHORT_URI_FORMAT.format(datastore_name, asset_artifact.relative_path) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/feature_set.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/feature_set.py new file mode 100644 index 00000000..a5bb73fe --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/feature_set.py @@ -0,0 +1,220 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +# pylint: disable=protected-access + +from os import PathLike +from pathlib import Path +from typing import IO, Any, AnyStr, Dict, List, Optional, Union, cast + +from azure.ai.ml._restclient.v2023_10_01.models import ( + FeaturesetContainer, + FeaturesetContainerProperties, + FeaturesetVersion, + FeaturesetVersionProperties, +) +from azure.ai.ml._schema._feature_set.feature_set_schema import FeatureSetSchema +from azure.ai.ml._utils._arm_id_utils import AMLNamedArmId, get_arm_id_object_from_id +from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY, LONG_URI_FORMAT, PARAMS_OVERRIDE_KEY +from azure.ai.ml.entities._assets import Artifact +from azure.ai.ml.entities._feature_set.feature_set_specification import FeatureSetSpecification +from azure.ai.ml.entities._feature_set.materialization_settings import MaterializationSettings +from azure.ai.ml.entities._util import load_from_dict +from azure.ai.ml.exceptions import ErrorCategory, ErrorTarget, ValidationErrorType, ValidationException + +from .artifact import ArtifactStorageInfo + + +class FeatureSet(Artifact): + """Feature Set + + :param name: The name of the Feature Set resource. + :type name: str + :param version: The version of the Feature Set resource. + :type version: str + :param entities: Specifies list of entities. + :type entities: list[str] + :param specification: Specifies the feature set spec details. + :type specification: ~azure.ai.ml.entities.FeatureSetSpecification + :param stage: Feature set stage. Allowed values: Development, Production, Archived. Defatuls to Development. + :type stage: Optional[str] + :param description: The description of the Feature Set resource. Defaults to None. + :type description: Optional[str] + :param tags: Tag dictionary. Tags can be added, removed, and updated. Defaults to None. + :type tags: Optional[dict[str, str]] + :param materialization_settings: Specifies the materialization settings. Defaults to None. + :type materialization_settings: Optional[~azure.ai.ml.entities.MaterializationSettings] + :param kwargs: A dictionary of additional configuration parameters. + :type kwargs: dict + :raises ValidationException: Raised if stage is specified and is not valid. + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_featurestore.py + :start-after: [START configure_feature_set] + :end-before: [END configure_feature_set] + :language: Python + :dedent: 8 + :caption: Instantiating a Feature Set object + """ + + def __init__( + self, + *, + name: str, + version: str, + entities: List[str], + specification: Optional[FeatureSetSpecification], + stage: Optional[str] = "Development", + description: Optional[str] = None, + materialization_settings: Optional[MaterializationSettings] = None, + tags: Optional[Dict] = None, + **kwargs: Any, + ) -> None: + super().__init__( + name=name, + version=version, + description=description, + tags=tags, + path=specification.path if specification is not None else None, + **kwargs, + ) + if stage and stage not in ["Development", "Production", "Archived"]: + msg = f"Stage must be Development, Production, or Archived, found {stage}" + raise ValidationException( + message=msg, + no_personal_data_message=msg, + error_type=ValidationErrorType.INVALID_VALUE, + target=ErrorTarget.FEATURE_SET, + error_category=ErrorCategory.USER_ERROR, + ) + self.entities = entities + self.specification = specification + self.stage = stage + self.materialization_settings = materialization_settings + self.latest_version = None + + def _to_rest_object(self) -> FeaturesetVersion: + featureset_version_properties = FeaturesetVersionProperties( + description=self.description, + properties=self.properties, + tags=self.tags, + entities=self.entities, + materialization_settings=( + self.materialization_settings._to_rest_object() if self.materialization_settings else None + ), + specification=self.specification._to_rest_object() if self.specification is not None else None, + stage=self.stage, + ) + return FeaturesetVersion(name=self.name, properties=featureset_version_properties) + + @classmethod + def _from_rest_object(cls, featureset_rest_object: FeaturesetVersion) -> Optional["FeatureSet"]: + if not featureset_rest_object: + return None + featureset_rest_object_details: FeaturesetVersionProperties = featureset_rest_object.properties + arm_id_object = get_arm_id_object_from_id(featureset_rest_object.id) + featureset = FeatureSet( + id=featureset_rest_object.id, + name=arm_id_object.asset_name, + version=arm_id_object.asset_version, + description=featureset_rest_object_details.description, + tags=featureset_rest_object_details.tags, + entities=featureset_rest_object_details.entities, + materialization_settings=MaterializationSettings._from_rest_object( + featureset_rest_object_details.materialization_settings + ), + specification=FeatureSetSpecification._from_rest_object(featureset_rest_object_details.specification), + stage=featureset_rest_object_details.stage, + properties=featureset_rest_object_details.properties, + ) + return featureset + + @classmethod + def _from_container_rest_object(cls, rest_obj: FeaturesetContainer) -> "FeatureSet": + rest_object_details: FeaturesetContainerProperties = rest_obj.properties + arm_id_object = get_arm_id_object_from_id(rest_obj.id) + featureset = FeatureSet( + name=arm_id_object.asset_name, + description=rest_object_details.description, + tags=rest_object_details.tags, + entities=[], + specification=FeatureSetSpecification(), + version="", + ) + featureset.latest_version = rest_object_details.latest_version + return featureset + + @classmethod + def _load( + cls, + data: Optional[Dict] = None, + yaml_path: Optional[Union[PathLike, str]] = None, + params_override: Optional[list] = None, + **kwargs: Any, + ) -> "FeatureSet": + data = data or {} + params_override = params_override or [] + base_path = Path(yaml_path).parent if yaml_path else Path("./") + context = { + BASE_PATH_CONTEXT_KEY: base_path, + PARAMS_OVERRIDE_KEY: params_override, + } + loaded_schema = load_from_dict(FeatureSetSchema, data, context, **kwargs) + feature_set = FeatureSet(base_path=base_path, **loaded_schema) + return feature_set + + def _to_dict(self) -> Dict: + return dict(FeatureSetSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self)) + + def _update_path(self, asset_artifact: ArtifactStorageInfo) -> None: + # if datastore_arm_id is null, capture the full_storage_path + if not asset_artifact.datastore_arm_id and asset_artifact.full_storage_path: + self.path = asset_artifact.full_storage_path + else: + aml_datastore_id = AMLNamedArmId(asset_artifact.datastore_arm_id) + self.path = LONG_URI_FORMAT.format( + aml_datastore_id.subscription_id, + aml_datastore_id.resource_group_name, + aml_datastore_id.workspace_name, + aml_datastore_id.asset_name, + asset_artifact.relative_path, + ) + + if self.specification is not None: + self.specification.path = self.path + + def dump(self, dest: Union[str, PathLike, IO[AnyStr]], **kwargs: Any) -> None: + """Dump the asset content into a file in YAML format. + + :param dest: The local path or file stream to write the YAML content to. + If dest is a file path, a new file will be created. + If dest is an open file, the file will be written to directly. + :type dest: Union[PathLike, str, IO[AnyStr]] + :raises FileExistsError: Raised if dest is a file path and the file already exists. + :raises IOError: Raised if dest is an open file and the file is not writable. + """ + + import os + import shutil + + from azure.ai.ml._utils.utils import is_url + + origin_spec_path = self.specification.path if self.specification is not None else None + if isinstance(dest, (PathLike, str)) and self.specification is not None and not is_url(self.specification.path): + if os.path.exists(dest): + raise FileExistsError(f"File {dest} already exists.") + relative_path = os.path.basename(cast(PathLike, self.specification.path)) + src_spec_path = ( + str(Path(self._base_path, self.specification.path)) if self.specification.path is not None else "" + ) + dest_spec_path = str(Path(os.path.dirname(dest), relative_path)) + if os.path.exists(dest_spec_path): + shutil.rmtree(dest_spec_path) + shutil.copytree(src=src_spec_path, dst=dest_spec_path) + self.specification.path = str(Path("./", relative_path)) + super().dump(dest=dest, **kwargs) + + if self.specification is not None: + self.specification.path = origin_spec_path diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/index.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/index.py new file mode 100644 index 00000000..35f671d3 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/index.py @@ -0,0 +1,137 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- +from os import PathLike +from pathlib import Path +from typing import Any, Dict, Optional, Union, cast + +# cspell:disable-next-line +from azure.ai.ml._restclient.azure_ai_assets_v2024_04_01.azureaiassetsv20240401.models import Index as RestIndex +from azure.ai.ml._schema import IndexAssetSchema +from azure.ai.ml._utils._arm_id_utils import AMLAssetId, AMLNamedArmId +from azure.ai.ml._utils._experimental import experimental +from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY, LONG_URI_FORMAT, PARAMS_OVERRIDE_KEY +from azure.ai.ml.entities._assets import Artifact +from azure.ai.ml.entities._assets._artifacts.artifact import ArtifactStorageInfo +from azure.ai.ml.entities._system_data import RestSystemData, SystemData +from azure.ai.ml.entities._util import load_from_dict + + +@experimental +class Index(Artifact): + """Index asset. + + :ivar name: Name of the resource. + :vartype name: str + :ivar version: Version of the resource. + :vartype version: str + :ivar id: Fully qualified resource Id: + azureml://workspace/{workspaceName}/indexes/{name}/versions/{version} of the index. Required. + :vartype id: str + :ivar stage: Update stage to 'Archive' for soft delete. Default is Development, which means the + asset is under development. Required. + :vartype stage: str + :ivar description: Description information of the asset. + :vartype description: Optional[str] + :ivar tags: Asset's tags. + :vartype tags: Optional[dict[str, str]] + :ivar properties: Asset's properties. + :vartype properties: Optional[dict[str, str]] + :ivar path: The local or remote path to the asset. + :vartype path: Optional[Union[str, os.PathLike]] + """ + + def __init__( + self, + *, + name: str, + version: Optional[str] = None, + stage: str = "Development", + description: Optional[str] = None, + tags: Optional[Dict[str, str]] = None, + properties: Optional[Dict[str, str]] = None, + path: Optional[Union[str, PathLike]] = None, + datastore: Optional[str] = None, + **kwargs: Any, + ): + self.stage = stage + super().__init__( + name=name, + version=version, + description=description, + tags=tags, + properties=properties, + path=path, + datastore=datastore, + **kwargs, + ) + + @classmethod + def _from_rest_object(cls, index_rest_object: RestIndex) -> "Index": + """Convert the response from the Index API into a Index + + :param RestIndex index_rest_object: + :return: An Index Asset + :rtype: Index + """ + asset_id = AMLAssetId(asset_id=index_rest_object.id) + + return Index( + id=index_rest_object.id, + name=asset_id.asset_name, + version=asset_id.asset_version, + description=index_rest_object.description, + tags=index_rest_object.tags, + properties=index_rest_object.properties, + stage=index_rest_object.stage, + path=index_rest_object.storage_uri, + # pylint: disable-next=protected-access + creation_context=SystemData._from_rest_object( + RestSystemData.from_dict(index_rest_object.system_data.as_dict()) + ), + ) + + def _to_rest_object(self) -> RestIndex: + # Note: Index.name and Index.version get dropped going to RestIndex, since both are encoded in the id + # (when present) + return RestIndex( + stage=self.stage, + storage_uri=self.path, + description=self.description, + tags=self.tags, + properties=self.properties, + id=self.id, + ) + + @classmethod + def _load( + cls, + data: Optional[Dict] = None, + yaml_path: Optional[Union[PathLike, str]] = None, + params_override: Optional[list] = None, + **kwargs: Any, + ) -> "Index": + data = data or {} + params_override = params_override or [] + context = { + BASE_PATH_CONTEXT_KEY: Path(yaml_path).parent if yaml_path else Path("./"), + PARAMS_OVERRIDE_KEY: params_override, + } + return cast(Index, load_from_dict(IndexAssetSchema, data, context, **kwargs)) + + def _to_dict(self) -> Dict: + return cast(dict, IndexAssetSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self)) + + def _update_path(self, asset_artifact: ArtifactStorageInfo) -> None: + """Updates an an artifact with the remote path of a local upload. + + :param ArtifactStorageInfo asset_artifact: The asset storage info of the artifact + """ + aml_datastore_id = AMLNamedArmId(asset_artifact.datastore_arm_id) + self.path = LONG_URI_FORMAT.format( + aml_datastore_id.subscription_id, + aml_datastore_id.resource_group_name, + aml_datastore_id.workspace_name, + aml_datastore_id.asset_name, + asset_artifact.relative_path, + ) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/model.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/model.py new file mode 100644 index 00000000..8e65bd3e --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/_artifacts/model.py @@ -0,0 +1,219 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- +from os import PathLike +from pathlib import Path +from typing import Any, Dict, Optional, Union + +from azure.ai.ml._restclient.v2023_04_01_preview.models import ( + FlavorData, + ModelContainer, + ModelVersion, + ModelVersionProperties, +) +from azure.ai.ml._schema import ModelSchema +from azure.ai.ml._utils._arm_id_utils import AMLNamedArmId, AMLVersionedArmId +from azure.ai.ml._utils._asset_utils import get_ignore_file, get_object_hash +from azure.ai.ml.constants._common import ( + BASE_PATH_CONTEXT_KEY, + LONG_URI_FORMAT, + PARAMS_OVERRIDE_KEY, + ArmConstants, + AssetTypes, +) +from azure.ai.ml.entities._assets import Artifact +from azure.ai.ml.entities._assets.intellectual_property import IntellectualProperty +from azure.ai.ml.entities._system_data import SystemData +from azure.ai.ml.entities._util import get_md5_string, load_from_dict + +from .artifact import ArtifactStorageInfo + + +class Model(Artifact): # pylint: disable=too-many-instance-attributes + """Model for training and scoring. + + :param name: The name of the model. Defaults to a random GUID. + :type name: Optional[str] + :param version: The version of the model. Defaults to "1" if either no name or an unregistered name is provided. + Otherwise, defaults to autoincrement from the last registered version of the model with that name. + :type version: Optional[str] + :param type: The storage format for this entity, used for NCD (Novel Class Discovery). Accepted values are + "custom_model", "mlflow_model", or "triton_model". Defaults to "custom_model". + :type type: Optional[str] + :param utc_time_created: The date and time when the model was created, in + UTC ISO 8601 format. (e.g. '2020-10-19 17:44:02.096572'). + :type utc_time_created: Optional[str] + :param flavors: The flavors in which the model can be interpreted. Defaults to None. + :type flavors: Optional[dict[str, Any]] + :param path: A remote uri or a local path pointing to a model. Defaults to None. + :type path: Optional[str] + :param description: The description of the resource. Defaults to None + :type description: Optional[str] + :param tags: Tag dictionary. Tags can be added, removed, and updated. Defaults to None. + :type tags: Optional[dict[str, str]] + :param properties: The asset property dictionary. Defaults to None. + :type properties: Optional[dict[str, str]] + :param stage: The stage of the resource. Defaults to None. + :type stage: Optional[str] + :param kwargs: A dictionary of additional configuration parameters. + :type kwargs: Optional[dict] + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START model_entity_create] + :end-before: [END model_entity_create] + :language: python + :dedent: 8 + :caption: Creating a Model object. + """ + + def __init__( + self, + *, + name: Optional[str] = None, + version: Optional[str] = None, + type: Optional[str] = None, # pylint: disable=redefined-builtin + path: Optional[Union[str, PathLike]] = None, + utc_time_created: Optional[str] = None, + flavors: Optional[Dict[str, Dict[str, Any]]] = None, + description: Optional[str] = None, + tags: Optional[Dict] = None, + properties: Optional[Dict] = None, + stage: Optional[str] = None, + **kwargs: Any, + ) -> None: + self.job_name = kwargs.pop("job_name", None) + self._intellectual_property = kwargs.pop("intellectual_property", None) + self._system_metadata = kwargs.pop("system_metadata", None) + super().__init__( + name=name, + version=version, + path=path, + description=description, + tags=tags, + properties=properties, + **kwargs, + ) + self.utc_time_created = utc_time_created + self.flavors = dict(flavors) if flavors else None + self._arm_type = ArmConstants.MODEL_VERSION_TYPE + self.type = type or AssetTypes.CUSTOM_MODEL + self.stage = stage + if self._is_anonymous and self.path: + _ignore_file = get_ignore_file(self.path) + _upload_hash = get_object_hash(self.path, _ignore_file) + self.name = get_md5_string(_upload_hash) + + @classmethod + def _load( + cls, + data: Optional[Dict] = None, + yaml_path: Optional[Union[PathLike, str]] = None, + params_override: Optional[list] = None, + **kwargs: Any, + ) -> "Model": + params_override = params_override or [] + data = data or {} + context = { + BASE_PATH_CONTEXT_KEY: Path(yaml_path).parent if yaml_path else Path("./"), + PARAMS_OVERRIDE_KEY: params_override, + } + res: Model = load_from_dict(ModelSchema, data, context, **kwargs) + return res + + def _to_dict(self) -> Dict: + return dict(ModelSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self)) + + @classmethod + def _from_rest_object(cls, model_rest_object: ModelVersion) -> "Model": + rest_model_version: ModelVersionProperties = model_rest_object.properties + arm_id = AMLVersionedArmId(arm_id=model_rest_object.id) + model_stage = rest_model_version.stage if hasattr(rest_model_version, "stage") else None + model_system_metadata = ( + rest_model_version.system_metadata if hasattr(rest_model_version, "system_metadata") else None + ) + if hasattr(rest_model_version, "flavors"): + flavors = {key: flavor.data for key, flavor in rest_model_version.flavors.items()} + model = Model( + id=model_rest_object.id, + name=arm_id.asset_name, + version=arm_id.asset_version, + path=rest_model_version.model_uri, + description=rest_model_version.description, + tags=rest_model_version.tags, + flavors=flavors, # pylint: disable=possibly-used-before-assignment + properties=rest_model_version.properties, + stage=model_stage, + # pylint: disable=protected-access + creation_context=SystemData._from_rest_object(model_rest_object.system_data), + type=rest_model_version.model_type, + job_name=rest_model_version.job_name, + intellectual_property=( + IntellectualProperty._from_rest_object(rest_model_version.intellectual_property) + if rest_model_version.intellectual_property + else None + ), + system_metadata=model_system_metadata, + ) + return model + + @classmethod + def _from_container_rest_object(cls, model_container_rest_object: ModelContainer) -> "Model": + model = Model( + name=model_container_rest_object.name, + version="1", + id=model_container_rest_object.id, + # pylint: disable=protected-access + creation_context=SystemData._from_rest_object(model_container_rest_object.system_data), + ) + model.latest_version = model_container_rest_object.properties.latest_version + + # Setting version to None since if version is not provided it is defaulted to "1". + # This should go away once container concept is finalized. + model.version = None + return model + + def _to_rest_object(self) -> ModelVersion: + model_version = ModelVersionProperties( + description=self.description, + tags=self.tags, + properties=self.properties, + flavors=( + {key: FlavorData(data=dict(value)) for key, value in self.flavors.items()} if self.flavors else None + ), # flatten OrderedDict to dict + model_type=self.type, + model_uri=self.path, + stage=self.stage, + is_anonymous=self._is_anonymous, + ) + model_version.system_metadata = self._system_metadata if hasattr(self, "_system_metadata") else None + + model_version_resource = ModelVersion(properties=model_version) + + return model_version_resource + + def _update_path(self, asset_artifact: ArtifactStorageInfo) -> None: + # datastore_arm_id is null for registry scenario, so capture the full_storage_path + if not asset_artifact.datastore_arm_id and asset_artifact.full_storage_path: + self.path = asset_artifact.full_storage_path + else: + aml_datastore_id = AMLNamedArmId(asset_artifact.datastore_arm_id) + self.path = LONG_URI_FORMAT.format( + aml_datastore_id.subscription_id, + aml_datastore_id.resource_group_name, + aml_datastore_id.workspace_name, + aml_datastore_id.asset_name, + asset_artifact.relative_path, + ) + + def _to_arm_resource_param(self, **kwargs: Any) -> Dict: # pylint: disable=unused-argument + properties = self._to_rest_object().properties + + return { + self._arm_type: { + ArmConstants.NAME: self.name, + ArmConstants.VERSION: self.version, + ArmConstants.PROPERTIES_PARAMETER_NAME: self._serialize.body(properties, "ModelVersionProperties"), + } + } diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/asset.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/asset.py new file mode 100644 index 00000000..b6ee2b55 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/asset.py @@ -0,0 +1,145 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +import uuid +from abc import abstractmethod +from os import PathLike +from typing import IO, Any, AnyStr, Dict, Optional, Union + +from azure.ai.ml._exception_helper import log_and_raise_error +from azure.ai.ml._utils.utils import dump_yaml_to_file +from azure.ai.ml.entities._resource import Resource +from azure.ai.ml.exceptions import ErrorCategory, ErrorTarget, ValidationErrorType, ValidationException + + +class Asset(Resource): + """Base class for asset. + + This class should not be instantiated directly. Instead, use one of its subclasses. + + :param name: The name of the asset. Defaults to a random GUID. + :type name: Optional[str]] + :param version: The version of the asset. Defaults to "1" if no name is provided, otherwise defaults to + autoincrement from the last registered version of the asset with that name. For a model name that has + never been registered, a default version will be assigned. + :type version: Optional[str] + :param description: The description of the resource. Defaults to None. + :type description: Optional[str] + :param tags: Tag dictionary. Tags can be added, removed, and updated. Defaults to None. + :type tags: Optional[dict[str, str]] + :param properties: The asset property dictionary. Defaults to None. + :type properties: Optional[dict[str, str]] + :keyword kwargs: A dictionary of additional configuration parameters. + :paramtype kwargs: Optional[dict] + """ + + def __init__( + self, + name: Optional[str] = None, + version: Optional[str] = None, + description: Optional[str] = None, + tags: Optional[Dict] = None, + properties: Optional[Dict] = None, + **kwargs: Any, + ) -> None: + self._is_anonymous = kwargs.pop("is_anonymous", False) + self._auto_increment_version = kwargs.pop("auto_increment_version", False) + self.auto_delete_setting = kwargs.pop("auto_delete_setting", None) + + if not name and version is None: + name = _get_random_name() + version = "1" + self._is_anonymous = True + elif version is not None and not name: + msg = "If version is specified, name must be specified also." + err = ValidationException( + message=msg, + target=ErrorTarget.ASSET, + no_personal_data_message=msg, + error_category=ErrorCategory.USER_ERROR, + error_type=ValidationErrorType.MISSING_FIELD, + ) + log_and_raise_error(err) + + super().__init__( + name=name, + description=description, + tags=tags, + properties=properties, + **kwargs, + ) + + self.version = version + self.latest_version = None + + @abstractmethod + def _to_dict(self) -> Dict: + """Dump the artifact content into a pure dict object.""" + + @property + def version(self) -> Optional[str]: + """The asset version. + + :return: The asset version. + :rtype: str + """ + return self._version + + @version.setter + def version(self, value: str) -> None: + """Sets the asset version. + + :param value: The asset version. + :type value: str + :raises ValidationException: Raised if value is not a string. + """ + if value: + if not isinstance(value, str): + msg = f"Asset version must be a string, not type {type(value)}." + err = ValidationException( + message=msg, + target=ErrorTarget.ASSET, + no_personal_data_message=msg, + error_category=ErrorCategory.USER_ERROR, + error_type=ValidationErrorType.INVALID_VALUE, + ) + log_and_raise_error(err) + + self._version = value + self._auto_increment_version = self.name and not self._version + + def dump(self, dest: Union[str, PathLike, IO[AnyStr]], **kwargs: Any) -> None: + """Dump the asset content into a file in YAML format. + + :param dest: The local path or file stream to write the YAML content to. + If dest is a file path, a new file will be created. + If dest is an open file, the file will be written to directly. + :type dest: Union[PathLike, str, IO[AnyStr]] + :raises FileExistsError: Raised if dest is a file path and the file already exists. + :raises IOError: Raised if dest is an open file and the file is not writable. + """ + path = kwargs.pop("path", None) + yaml_serialized = self._to_dict() + dump_yaml_to_file(dest, yaml_serialized, default_flow_style=False, path=path, **kwargs) + + def __eq__(self, other: Any) -> bool: + return bool( + self.name == other.name + and self.id == other.id + and self.version == other.version + and self.description == other.description + and self.tags == other.tags + and self.properties == other.properties + and self.base_path == other.base_path + and self._is_anonymous == other._is_anonymous + and self._auto_increment_version == other._auto_increment_version + and self.auto_delete_setting == other.auto_delete_setting + ) + + def __ne__(self, other: Any) -> bool: + return not self.__eq__(other) + + +def _get_random_name() -> str: + return str(uuid.uuid4()) diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/auto_delete_setting.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/auto_delete_setting.py new file mode 100644 index 00000000..ea6bf9e8 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/auto_delete_setting.py @@ -0,0 +1,42 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +from typing import Any, Union + +from azure.ai.ml._restclient.v2023_04_01_preview.models import AutoDeleteSetting as RestAutoDeleteSetting +from azure.ai.ml._utils._experimental import experimental +from azure.ai.ml.constants._common import AutoDeleteCondition +from azure.ai.ml.entities._mixins import DictMixin + + +@experimental +class AutoDeleteSetting(DictMixin): + """Class which defines the auto delete setting. + :param condition: When to check if an asset is expired. + Possible values include: "CreatedGreaterThan", "LastAccessedGreaterThan". + :type condition: AutoDeleteCondition + :param value: Expiration condition value. + :type value: str + """ + + def __init__( + self, + *, + condition: AutoDeleteCondition = AutoDeleteCondition.CREATED_GREATER_THAN, + value: Union[str, None] = None + ): + self.condition = condition + self.value = value + + def _to_rest_object(self) -> RestAutoDeleteSetting: + return RestAutoDeleteSetting(condition=self.condition, value=self.value) + + @classmethod + def _from_rest_object(cls, obj: RestAutoDeleteSetting) -> "AutoDeleteSetting": + return cls(condition=obj.condition, value=obj.value) + + def __eq__(self, other: Any) -> bool: + if not isinstance(other, AutoDeleteSetting): + return NotImplemented + return self.condition == other.condition and self.value == other.value diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/environment.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/environment.py new file mode 100644 index 00000000..865273fb --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/environment.py @@ -0,0 +1,478 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +# pylint: disable=protected-access, too-many-instance-attributes + +import os +from pathlib import Path +from typing import Any, Dict, Optional, Union + +import yaml # type: ignore[import] + +from azure.ai.ml._exception_helper import log_and_raise_error +from azure.ai.ml._restclient.v2023_04_01_preview.models import BuildContext as RestBuildContext +from azure.ai.ml._restclient.v2023_04_01_preview.models import ( + EnvironmentContainer, + EnvironmentVersion, + EnvironmentVersionProperties, +) +from azure.ai.ml._schema import EnvironmentSchema +from azure.ai.ml._utils._arm_id_utils import AMLVersionedArmId +from azure.ai.ml._utils._asset_utils import get_ignore_file, get_object_hash +from azure.ai.ml._utils.utils import dump_yaml, is_url, load_file, load_yaml +from azure.ai.ml.constants._common import ANONYMOUS_ENV_NAME, BASE_PATH_CONTEXT_KEY, PARAMS_OVERRIDE_KEY, ArmConstants +from azure.ai.ml.entities._assets.asset import Asset +from azure.ai.ml.entities._assets.intellectual_property import IntellectualProperty +from azure.ai.ml.entities._mixins import LocalizableMixin +from azure.ai.ml.entities._system_data import SystemData +from azure.ai.ml.entities._util import get_md5_string, load_from_dict +from azure.ai.ml.exceptions import ErrorCategory, ErrorTarget, ValidationErrorType, ValidationException + + +class BuildContext: + """Docker build context for Environment. + + :param path: The local or remote path to the the docker build context directory. + :type path: Union[str, os.PathLike] + :param dockerfile_path: The path to the dockerfile relative to root of docker build context directory. + :type dockerfile_path: str + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START build_context_entity_create] + :end-before: [END build_context_entity_create] + :language: python + :dedent: 8 + :caption: Create a Build Context object. + """ + + def __init__( + self, + *, + dockerfile_path: Optional[str] = None, + path: Optional[Union[str, os.PathLike]] = None, + ): + self.dockerfile_path = dockerfile_path + self.path = path + + def _to_rest_object(self) -> RestBuildContext: + return RestBuildContext(context_uri=self.path, dockerfile_path=self.dockerfile_path) + + @classmethod + def _from_rest_object(cls, rest_obj: RestBuildContext) -> "BuildContext": + return BuildContext( + path=rest_obj.context_uri, + dockerfile_path=rest_obj.dockerfile_path, + ) + + def __eq__(self, other: Any) -> bool: + res: bool = self.dockerfile_path == other.dockerfile_path and self.path == other.path + return res + + def __ne__(self, other: Any) -> bool: + return not self.__eq__(other) + + +class Environment(Asset, LocalizableMixin): + """Environment for training. + + :param name: Name of the resource. + :type name: str + :param version: Version of the asset. + :type version: str + :param description: Description of the resource. + :type description: str + :param image: URI of a custom base image. + :type image: str + :param build: Docker build context to create the environment. Mutually exclusive with "image" + :type build: ~azure.ai.ml.entities._assets.environment.BuildContext + :param conda_file: Path to configuration file listing conda packages to install. + :type conda_file: typing.Union[str, os.PathLike] + :param tags: Tag dictionary. Tags can be added, removed, and updated. + :type tags: dict[str, str] + :param properties: The asset property dictionary. + :type properties: dict[str, str] + :param datastore: The datastore to upload the local artifact to. + :type datastore: str + :param kwargs: A dictionary of additional configuration parameters. + :type kwargs: dict + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START env_entity_create] + :end-before: [END env_entity_create] + :language: python + :dedent: 8 + :caption: Create a Environment object. + """ + + def __init__( + self, + *, + name: Optional[str] = None, + version: Optional[str] = None, + description: Optional[str] = None, + image: Optional[str] = None, + build: Optional[BuildContext] = None, + conda_file: Optional[Union[str, os.PathLike, Dict]] = None, + tags: Optional[Dict] = None, + properties: Optional[Dict] = None, + datastore: Optional[str] = None, + **kwargs: Any, + ): + self._arm_type: str = "" + self.latest_version: str = "" # type: ignore[assignment] + self.image: Optional[str] = None + inference_config = kwargs.pop("inference_config", None) + os_type = kwargs.pop("os_type", None) + self._intellectual_property = kwargs.pop("intellectual_property", None) + + super().__init__( + name=name, + version=version, + description=description, + tags=tags, + properties=properties, + **kwargs, + ) + + self.conda_file = conda_file + self.image = image + self.build = build + self.inference_config = inference_config + self.os_type = os_type + self._arm_type = ArmConstants.ENVIRONMENT_VERSION_TYPE + self._conda_file_path = ( + _resolve_path(base_path=self.base_path, input=conda_file) + if isinstance(conda_file, (os.PathLike, str)) + else None + ) + self.path = None + self.datastore = datastore + self._upload_hash = None + + self._translated_conda_file = None + if self.conda_file: + self._translated_conda_file = dump_yaml(self.conda_file, sort_keys=True) # service needs str representation + + if self.build and self.build.path and not is_url(self.build.path): + path = Path(self.build.path) + if not path.is_absolute(): + path = Path(self.base_path, path).resolve() + self.path = path + + if self._is_anonymous: + if self.path: + self._ignore_file = get_ignore_file(path) + self._upload_hash = get_object_hash(path, self._ignore_file) + self._generate_anonymous_name_version(source="build") + elif self.image: + self._generate_anonymous_name_version( + source="image", conda_file=self._translated_conda_file, inference_config=self.inference_config + ) + + @property + def conda_file(self) -> Optional[Union[str, os.PathLike, Dict]]: + """Conda environment specification. + + :return: Conda dependencies loaded from `conda_file` param. + :rtype: Optional[Union[str, os.PathLike]] + """ + return self._conda_file + + @conda_file.setter + def conda_file(self, value: Optional[Union[str, os.PathLike, Dict]]) -> None: + """Set conda environment specification. + + :param value: A path to a local conda dependencies yaml file or a loaded yaml dictionary of dependencies. + :type value: Union[str, os.PathLike, Dict] + :return: None + """ + if not isinstance(value, Dict): + value = _deserialize(self.base_path, value, is_conda=True) + self._conda_file = value + + @classmethod + def _load( + cls, + data: Optional[dict] = None, + yaml_path: Optional[Union[os.PathLike, str]] = None, + params_override: Optional[list] = None, + **kwargs: Any, + ) -> "Environment": + params_override = params_override or [] + data = data or {} + context = { + BASE_PATH_CONTEXT_KEY: Path(yaml_path).parent if yaml_path else Path("./"), + PARAMS_OVERRIDE_KEY: params_override, + } + res: Environment = load_from_dict(EnvironmentSchema, data, context, **kwargs) + return res + + def _to_rest_object(self) -> EnvironmentVersion: + self.validate() + environment_version = EnvironmentVersionProperties() + if self.conda_file: + environment_version.conda_file = self._translated_conda_file + if self.image: + environment_version.image = self.image + if self.build: + environment_version.build = self.build._to_rest_object() + if self.os_type: + environment_version.os_type = self.os_type + if self.tags: + environment_version.tags = self.tags + if self._is_anonymous: + environment_version.is_anonymous = self._is_anonymous + if self.inference_config: + environment_version.inference_config = self.inference_config + if self.description: + environment_version.description = self.description + if self.properties: + environment_version.properties = self.properties + + environment_version_resource = EnvironmentVersion(properties=environment_version) + + return environment_version_resource + + @classmethod + def _from_rest_object(cls, env_rest_object: EnvironmentVersion) -> "Environment": + rest_env_version = env_rest_object.properties + arm_id = AMLVersionedArmId(arm_id=env_rest_object.id) + + environment = Environment( + id=env_rest_object.id, + name=arm_id.asset_name, + version=arm_id.asset_version, + description=rest_env_version.description, + tags=rest_env_version.tags, + creation_context=( + SystemData._from_rest_object(env_rest_object.system_data) if env_rest_object.system_data else None + ), + is_anonymous=rest_env_version.is_anonymous, + image=rest_env_version.image, + os_type=rest_env_version.os_type, + inference_config=rest_env_version.inference_config, + build=BuildContext._from_rest_object(rest_env_version.build) if rest_env_version.build else None, + properties=rest_env_version.properties, + intellectual_property=( + IntellectualProperty._from_rest_object(rest_env_version.intellectual_property) + if rest_env_version.intellectual_property + else None + ), + ) + + if rest_env_version.conda_file: + translated_conda_file = yaml.safe_load(rest_env_version.conda_file) + environment.conda_file = translated_conda_file + environment._translated_conda_file = rest_env_version.conda_file + + return environment + + @classmethod + def _from_container_rest_object(cls, env_container_rest_object: EnvironmentContainer) -> "Environment": + env = Environment( + name=env_container_rest_object.name, + version="1", + id=env_container_rest_object.id, + creation_context=SystemData._from_rest_object(env_container_rest_object.system_data), + ) + env.latest_version = env_container_rest_object.properties.latest_version + + # Setting version to None since if version is not provided it is defaulted to "1". + # This should go away once container concept is finalized. + env.version = None + return env + + def _to_arm_resource_param(self, **kwargs: Any) -> Dict: # pylint: disable=unused-argument + properties = self._to_rest_object().properties + + return { + self._arm_type: { + ArmConstants.NAME: self.name, + ArmConstants.VERSION: self.version, + ArmConstants.PROPERTIES_PARAMETER_NAME: self._serialize.body(properties, "EnvironmentVersion"), + } + } + + def _to_dict(self) -> Dict: + res: dict = EnvironmentSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self) + return res + + def validate(self) -> None: + """Validate the environment by checking its name, image and build + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START env_entities_validate] + :end-before: [END env_entities_validate] + :language: python + :dedent: 8 + :caption: Validate environment example. + """ + + if self.name is None: + msg = "Environment name is required" + err = ValidationException( + message=msg, + target=ErrorTarget.ENVIRONMENT, + no_personal_data_message=msg, + error_category=ErrorCategory.USER_ERROR, + error_type=ValidationErrorType.MISSING_FIELD, + ) + log_and_raise_error(err) + if self.image is None and self.build is None: + msg = "Docker image or Dockerfile is required for environments" + err = ValidationException( + message=msg, + target=ErrorTarget.ENVIRONMENT, + no_personal_data_message=msg, + error_category=ErrorCategory.USER_ERROR, + error_type=ValidationErrorType.MISSING_FIELD, + ) + log_and_raise_error(err) + if self.image and self.build: + msg = "Docker image or Dockerfile should be provided not both" + err = ValidationException( + message=msg, + target=ErrorTarget.ENVIRONMENT, + no_personal_data_message=msg, + error_category=ErrorCategory.USER_ERROR, + error_type=ValidationErrorType.INVALID_VALUE, + ) + log_and_raise_error(err) + + def __eq__(self, other: object) -> bool: + if not isinstance(other, Environment): + return NotImplemented + return ( + self.name == other.name + and self.id == other.id + and self.version == other.version + and self.description == other.description + and self.tags == other.tags + and self.properties == other.properties + and self.base_path == other.base_path + and self.image == other.image + and self.build == other.build + and self.conda_file == other.conda_file + and self.inference_config == other.inference_config + and self._is_anonymous == other._is_anonymous + and self.os_type == other.os_type + and self._intellectual_property == other._intellectual_property + ) + + def __ne__(self, other: object) -> bool: + return not self.__eq__(other) + + def _generate_anonymous_name_version( + self, source: str, conda_file: Optional[str] = None, inference_config: Optional[Dict] = None + ) -> None: + hash_str = "" + if source == "image": + hash_str = hash_str.join(get_md5_string(self.image)) + if inference_config: + hash_str = hash_str.join(get_md5_string(yaml.dump(inference_config, sort_keys=True))) + if conda_file: + hash_str = hash_str.join(get_md5_string(conda_file)) + if source == "build": + if self.build is not None and not self.build.dockerfile_path: + hash_str = hash_str.join(get_md5_string(self._upload_hash)) + else: + if self.build is not None: + hash_str = hash_str.join(get_md5_string(self._upload_hash)).join( + get_md5_string(self.build.dockerfile_path) + ) + version_hash = get_md5_string(hash_str) + self.version = version_hash + self.name = ANONYMOUS_ENV_NAME + + def _localize(self, base_path: str) -> None: + """Called on an asset got from service to clean up remote attributes like id, creation_context, etc. and update + base_path. + + :param base_path: The base path + :type base_path: str + """ + if not getattr(self, "id", None): + raise ValueError("Only remote asset can be localize but got a {} without id.".format(type(self))) + self._id = None + self._creation_context = None + self._base_path = base_path + if self._is_anonymous: + self.name, self.version = None, None + + +# TODO: Remove _DockerBuild and _DockerConfiguration classes once local endpoint moves to using updated env +class _DockerBuild: + """Helper class to encapsulate Docker build info for Environment.""" + + def __init__( + self, + base_path: Optional[Union[str, os.PathLike]] = None, + dockerfile: Optional[str] = None, + ): + self.dockerfile = _deserialize(base_path, dockerfile) + + @classmethod + def _to_rest_object(cls) -> None: + return None + + def _from_rest_object(self, rest_obj: Any) -> None: + self.dockerfile = rest_obj.dockerfile + + def __eq__(self, other: Any) -> bool: + res: bool = self.dockerfile == other.dockerfile + return res + + def __ne__(self, other: Any) -> bool: + return not self.__eq__(other) + + +def _deserialize( + base_path: Optional[Union[str, os.PathLike]], + input: Optional[Union[str, os.PathLike, Dict]], # pylint: disable=redefined-builtin + is_conda: bool = False, +) -> Optional[Union[str, os.PathLike, Dict]]: + """Deserialize user input files for conda and docker. + + :param base_path: The base path for all files supplied by user. + :type base_path: Union[str, os.PathLike] + :param input: Input to be deserialized. Will be either dictionary of file contents or path to file. + :type input: Union[str, os.PathLike, Dict[str, str]] + :param is_conda: If file is conda file, it will be returned as dictionary + :type is_conda: bool + :return: The deserialized data + :rtype: Union[str, Dict] + """ + + if input: + path = _resolve_path(base_path=base_path, input=input) + data: Union[str, Dict] = "" + if is_conda: + data = load_yaml(path) + else: + data = load_file(path) + return data + return input + + +def _resolve_path(base_path: Any, input: Any) -> Path: # pylint: disable=redefined-builtin + """Deserialize user input files for conda and docker. + + :param base_path: The base path for all files supplied by user. + :type base_path: Union[str, os.PathLike] + :param input: Input to be deserialized. Will be either dictionary of file contents or path to file. + :type input: Union[str, os.PathLike, Dict[str, str]] + :return: The resolved path + :rtype: Path + """ + + path = Path(input) + if not path.is_absolute(): + path = Path(base_path, path).resolve() + return path diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/federated_learning_silo.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/federated_learning_silo.py new file mode 100644 index 00000000..8255f887 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/federated_learning_silo.py @@ -0,0 +1,123 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- +# TODO determine where this file should live. + +from os import PathLike +from typing import IO, Any, AnyStr, Dict, List, Optional, Union + +from azure.ai.ml import Input +from azure.ai.ml._utils.utils import dump_yaml_to_file, load_yaml +from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY + + +# Entity representation of a federated learning silo. +# Used by Federated Learning DSL nodes as inputs for creating +# FL subgraphs in pipelines. +# The functionality of this entity is limited, and it exists mostly +# To simplify the process of loading and validating these objects from YAML. +class FederatedLearningSilo: + def __init__( + self, + *, + compute: str, + datastore: str, + inputs: Dict[str, Input], + ): + """ + A pseudo-entity that represents a federated learning silo, which is an isolated compute with its own + datastore and input targets. This is meant to be used in conjunction with the + Federated Learning DSL node to create federated learning pipelines. This does NOT represent any specific + AML resource, and is instead merely meant to simply client-side experiences with managing FL data distribution. + Standard usage involves the "load_list" classmethod to load a list of these objects from YAML, which serves + as a necessary input for FL processes. + + + :param compute: The resource id of a compute. + :type compute: str + :param datastore: The resource id of a datastore. + :type datastore: str + :param inputs: A dictionary of input entities that exist in the previously specified datastore. + The keys of this dictionary are the keyword names that these inputs should be entered into. + :type inputs: dict[str, Input] + :param kwargs: A dictionary of additional configuration parameters. + :type kwargs: dict + """ + self.compute = compute + self.datastore = datastore + self.inputs = inputs + + def dump( + self, + dest: Union[str, PathLike, IO[AnyStr]], + # pylint: disable=unused-argument + **kwargs: Any, + ) -> None: + """Dump the Federated Learning Silo spec into a file in yaml format. + + :param dest: Either + * A path to a local file + * A writeable file-like object + :type dest: Union[str, PathLike, IO[AnyStr]] + """ + yaml_serialized = self._to_dict() + dump_yaml_to_file(dest, yaml_serialized, default_flow_style=False) + + def _to_dict(self) -> Dict: + # JIT import to avoid experimental warnings on unrelated calls + from azure.ai.ml._schema.assets.federated_learning_silo import FederatedLearningSiloSchema + + schema = FederatedLearningSiloSchema(context={BASE_PATH_CONTEXT_KEY: "./"}) + + return Dict(schema.dump(self)) + + @classmethod + def _load_from_dict(cls, silo_dict: dict) -> "FederatedLearningSilo": + data_input = silo_dict.get("inputs", {}) + return FederatedLearningSilo(compute=silo_dict["compute"], datastore=silo_dict["datastore"], inputs=data_input) + + # simple load based off mltable metadata loading style + @classmethod + def _load( + cls, + yaml_path: Optional[Union[PathLike, str]] = None, + ) -> "FederatedLearningSilo": + yaml_dict = load_yaml(yaml_path) + return FederatedLearningSilo._load_from_dict(silo_dict=yaml_dict) + + @classmethod + def load_list( + cls, + *, + yaml_path: Optional[Union[PathLike, str]], + list_arg: str, + ) -> List["FederatedLearningSilo"]: + """ + Loads a list of federated learning silos from YAML. This is the expected entry point + for this class; load a list of these, then supply them to the federated learning DSL + package node in order to produce an FL pipeline. + + The structure of the supplied YAML file is assumed to be a list of FL silos under the + name specified by the list_arg input, as shown below. + + list_arg: + - silo 1 ... + - silo 2 ... + + :keyword yaml_path: A path leading to a local YAML file which contains a list of + FederatedLearningSilo objects. + :paramtype yaml_path: Optional[Union[PathLike, str]] + :keyword list_arg: A string that names the top-level value which contains the list + of FL silos. + :paramtype list_arg: str + :return: The list of federated learning silos + :rtype: List[FederatedLearningSilo] + """ + yaml_dict = load_yaml(yaml_path) + return [ + FederatedLearningSilo._load_from_dict(silo_dict=silo_yaml_dict) for silo_yaml_dict in yaml_dict[list_arg] + ] + + # There are no to/from rest object functions because this object has no + # rest object equivalent. Any conversions should be done as part of the + # to/from rest object functions of OTHER entity objects. diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/intellectual_property.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/intellectual_property.py new file mode 100644 index 00000000..58b96a1b --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/intellectual_property.py @@ -0,0 +1,49 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +from typing import Any, Optional + +from azure.ai.ml._restclient.v2023_04_01_preview.models import IntellectualProperty as RestIntellectualProperty +from azure.ai.ml._utils._experimental import experimental +from azure.ai.ml.constants._assets import IPProtectionLevel +from azure.ai.ml.entities._mixins import RestTranslatableMixin + + +@experimental +class IntellectualProperty(RestTranslatableMixin): + """Intellectual property settings definition. + + :keyword publisher: The publisher's name. + :paramtype publisher: Optional[str] + :keyword protection_level: Asset Protection Level. Accepted values are IPProtectionLevel.ALL ("all") and + IPProtectionLevel.NONE ("none"). Defaults to IPProtectionLevel.ALL ("all"). + :paramtype protection_level: Optional[Union[str, ~azure.ai.ml.constants.IPProtectionLevel]] + + .. admonition:: Example: + + .. literalinclude:: ../samples/ml_samples_misc.py + :start-after: [START intellectual_property_configuration] + :end-before: [END intellectual_property_configuration] + :language: python + :dedent: 8 + :caption: Configuring intellectual property settings on a CommandComponent. + """ + + def __init__( + self, *, publisher: Optional[str] = None, protection_level: IPProtectionLevel = IPProtectionLevel.ALL + ) -> None: + self.publisher = publisher + self.protection_level = protection_level + + def _to_rest_object(self) -> RestIntellectualProperty: + return RestIntellectualProperty(publisher=self.publisher, protection_level=self.protection_level) + + @classmethod + def _from_rest_object(cls, obj: RestIntellectualProperty) -> "IntellectualProperty": + return cls(publisher=obj.publisher, protection_level=obj.protection_level) + + def __eq__(self, other: Any) -> bool: + if not isinstance(other, IntellectualProperty): + return NotImplemented + return self.publisher == other.publisher and self.protection_level == other.protection_level diff --git a/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/workspace_asset_reference.py b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/workspace_asset_reference.py new file mode 100644 index 00000000..1e7d1ba2 --- /dev/null +++ b/.venv/lib/python3.12/site-packages/azure/ai/ml/entities/_assets/workspace_asset_reference.py @@ -0,0 +1,87 @@ +# --------------------------------------------------------- +# Copyright (c) Microsoft Corporation. All rights reserved. +# --------------------------------------------------------- + +import os +from pathlib import Path +from typing import Any, Dict, Optional, Union + +from azure.ai.ml._restclient.v2021_10_01_dataplanepreview.models import ( + ResourceManagementAssetReferenceData, + ResourceManagementAssetReferenceDetails, +) +from azure.ai.ml._schema import WorkspaceAssetReferenceSchema +from azure.ai.ml.constants._common import BASE_PATH_CONTEXT_KEY, PARAMS_OVERRIDE_KEY +from azure.ai.ml.entities._assets.asset import Asset +from azure.ai.ml.entities._util import load_from_dict + + +class WorkspaceAssetReference(Asset): + """Workspace Model Reference. + + This is for SDK internal use only, might be deprecated in the future. + :param name: Model name + :type name: str + :param version: Model version + :type version: str + :param asset_id: Model asset id + :type version: str + :param kwargs: A dictionary of additional configuration parameters. + :type kwargs: dict + """ + + def __init__( + self, + *, + name: Optional[str] = None, + version: Optional[str] = None, + asset_id: Optional[str] = None, + properties: Optional[Dict] = None, + **kwargs: Any, + ): + super().__init__( + name=name, + version=version, + properties=properties, + **kwargs, + ) + self.asset_id = asset_id + + @classmethod + def _load( + cls: Any, + data: Optional[dict] = None, + yaml_path: Optional[Union[os.PathLike, str]] = None, + params_override: Optional[list] = None, + **kwargs: Any, + ) -> "WorkspaceAssetReference": + data = data or {} + params_override = params_override or [] + context = { + BASE_PATH_CONTEXT_KEY: Path(yaml_path).parent if yaml_path else Path("./"), + PARAMS_OVERRIDE_KEY: params_override, + } + res: WorkspaceAssetReference = load_from_dict(WorkspaceAssetReferenceSchema, data, context, **kwargs) + return res + + def _to_rest_object(self) -> ResourceManagementAssetReferenceData: + resource_management_details = ResourceManagementAssetReferenceDetails( + destination_name=self.name, + destination_version=self.version, + source_asset_id=self.asset_id, + ) + resource_management = ResourceManagementAssetReferenceData(properties=resource_management_details) + return resource_management + + @classmethod + def _from_rest_object(cls, resource_object: ResourceManagementAssetReferenceData) -> "WorkspaceAssetReference": + resource_management = WorkspaceAssetReference( + name=resource_object.properties.destination_name, + version=resource_object.properties.destination_version, + asset_id=resource_object.properties.source_asset_id, + ) + + return resource_management + + def _to_dict(self) -> Dict: + return dict(WorkspaceAssetReferenceSchema(context={BASE_PATH_CONTEXT_KEY: "./"}).dump(self)) |