IImageModelSettings Interface
Definition
Important
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[System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ImageModelSettingsTypeConverter))]
public interface IImageModelSettings : Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Runtime.IJsonSerializable[<System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ImageModelSettingsTypeConverter))>]
type IImageModelSettings = interface
interface IJsonSerializablePublic Interface IImageModelSettings
Implements IJsonSerializable- Derived
- Attributes
- Implements
Properties
| AdvancedSetting |
Settings for advanced scenarios. |
| AmsGradient |
Enable AMSGrad when optimizer is 'adam' or 'adamw'. |
| Augmentation |
Settings for using Augmentations. |
| Beta1 |
Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1]. |
| Beta2 |
Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1]. |
| CheckpointFrequency |
Frequency to store model checkpoints. Must be a positive integer. |
| CheckpointModelDescription |
Description for the input. |
| CheckpointModelJobInputType |
[Required] Specifies the type of job. |
| CheckpointModelMode |
Input Asset Delivery Mode. |
| CheckpointModelUri |
[Required] Input Asset URI. |
| CheckpointRunId |
The id of a previous run that has a pretrained checkpoint for incremental training. |
| Distributed |
Whether to use distributed training. |
| EarlyStopping |
Enable early stopping logic during training. |
| EarlyStoppingDelay |
Minimum number of epochs or validation evaluations to wait before primary metric improvement is tracked for early stopping. Must be a positive integer. |
| EarlyStoppingPatience |
Minimum number of epochs or validation evaluations with no primary metric improvement before the run is stopped. Must be a positive integer. |
| EnableOnnxNormalization |
Enable normalization when exporting ONNX model. |
| EvaluationFrequency |
Frequency to evaluate validation dataset to get metric scores. Must be a positive integer. |
| GradientAccumulationStep |
Gradient accumulation means running a configured number of "GradAccumulationStep" steps without updating the model weights while accumulating the gradients of those steps, and then using the accumulated gradients to compute the weight updates. Must be a positive integer. |
| LayersToFreeze |
Number of layers to freeze for the model. Must be a positive integer. For instance, passing 2 as value for 'seresnext' means freezing layer0 and layer1. For a full list of models supported and details on layer freeze, please see: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models. |
| LearningRate |
Initial learning rate. Must be a float in the range [0, 1]. |
| LearningRateScheduler |
Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'. |
| ModelName |
Name of the model to use for training. For more information on the available models please visit the official documentation: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models. |
| Momentum |
Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1]. |
| Nesterov |
Enable nesterov when optimizer is 'sgd'. |
| NumberOfEpoch |
Number of training epochs. Must be a positive integer. |
| NumberOfWorker |
Number of data loader workers. Must be a non-negative integer. |
| Optimizer |
Type of optimizer. |
| RandomSeed |
Random seed to be used when using deterministic training. |
| StepLrGamma |
Value of gamma when learning rate scheduler is 'step'. Must be a float in the range [0, 1]. |
| StepLrStepSize |
Value of step size when learning rate scheduler is 'step'. Must be a positive integer. |
| TrainingBatchSize |
Training batch size. Must be a positive integer. |
| ValidationBatchSize |
Validation batch size. Must be a positive integer. |
| WarmupCosineLrCycle |
Value of cosine cycle when learning rate scheduler is 'warmup_cosine'. Must be a float in the range [0, 1]. |
| WarmupCosineLrWarmupEpoch |
Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer. |
| WeightDecay |
Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be a float in the range[0, 1]. |
Methods
| ToJson(JsonObject, SerializationMode) | (Inherited from IJsonSerializable) |