constants Package
This package defines constants used in Azure Machine Learning SDKv2.
Classes
| AssetTypes |
AssetTypes is an enumeration of values for the asset types of a dataset. Asset types are used to identify the type of an asset. An asset can be a file, folder, mlflow model, triton model, mltable or custom model. |
| BatchDeploymentOutputAction | |
| DataGenerationTaskType | |
| DataGenerationType | |
| DistributionType | |
| ImportSourceType | |
| InputOutputModes |
InputOutputModes is an enumeration of values for the input/output modes of a dataset. Input/output modes are used to identify the type of an asset when it is created using the API. |
| InputTypes |
InputTypes is an enumeration of values for the input types of a dataset. Input types are used to identify the type of an asset. |
| JobType | |
| ModelType |
ModelType is an enumeration of values for the model types. Model types are used to identify the type of a model when it is created using the API. Model types can be 'CustomModel', 'MLFlowModel' or 'TritonModel'. |
| ParallelTaskType | |
| Scope |
Scope is an enumeration of values for the scope of an asset. Scope can be 'subscription' or 'resource_group'. |
| WorkspaceKind |
Enum of workspace categories. |
Enums
| AcrAccountSku |
Azure Container Registry SKUs. |
| IPProtectionLevel |
Note This is an experimental class, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information. Intellectual property protection level. |
| ImageClassificationModelNames |
Model names that are supported for Image Classification tasks. |
| ImageInstanceSegmentationModelNames |
Model names that are supported for Image Instance Segmentation tasks. |
| ImageObjectDetectionModelNames |
Model names that are supported for Image Object Detection tasks. |
| ListViewType |
ListViewType. |
| ManagedServiceIdentityType |
Type of managed service identity (where both SystemAssigned and UserAssigned types are allowed). |
| MonitorDatasetContext |
Note This is an experimental class, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information. |
| MonitorFeatureType |
Note This is an experimental class, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information. |
| MonitorMetricName |
Note This is an experimental class, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information. |
| MonitorModelType |
Note This is an experimental class, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information. |
| MonitorSignalType |
Note This is an experimental class, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information. |
| MonitorTargetTasks | |
| NlpLearningRateScheduler |
Enum of learning rate schedulers that aligns with those supported by HF |
| NlpModels |
Model names that are supported for NLP (Natural Language Processing) tasks. |
| StorageAccountType |
Storage account types. |
| TabularTrainingMode |
Note This is an experimental class, and may change at any time. Please see https://aka.ms/azuremlexperimental for more information. Mode to enable/disable distributed training. |
| TimeZone |
Time zones that a job or compute instance schedule accepts. |
