IImageModelDistributionSettingsClassification Interface

Reference

Definition

Namespace:: Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401

Assembly:: Az.MachineLearningServices.private.dll

Important

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[System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ImageModelDistributionSettingsClassificationTypeConverter))]
public interface IImageModelDistributionSettingsClassification : Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IImageModelDistributionSettings

[<System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ImageModelDistributionSettingsClassificationTypeConverter))>]
type IImageModelDistributionSettingsClassification = interface
    interface IJsonSerializable
    interface IImageModelDistributionSettings

Public Interface IImageModelDistributionSettingsClassification
Implements IImageModelDistributionSettings

Derived: Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ImageModelDistributionSettingsClassification

Attributes: TypeConverterAttribute

Implements: IImageModelDistributionSettings IJsonSerializable

Examples

Some examples are:

ModelName = "choice('seresnext', 'resnest50')";
LearningRate = "uniform(0.001, 0.01)";
LayersToFreeze = "choice(0, 2)";

Properties

AmsGradient	Enable AMSGrad when optimizer is 'adam' or 'adamw'. (Inherited from IImageModelDistributionSettings)
Augmentation	Settings for using Augmentations. (Inherited from IImageModelDistributionSettings)
Beta1	Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1]. (Inherited from IImageModelDistributionSettings)
Beta2	Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1]. (Inherited from IImageModelDistributionSettings)
Distributed	Whether to use distributer training. (Inherited from IImageModelDistributionSettings)
EarlyStopping	Enable early stopping logic during training. (Inherited from IImageModelDistributionSettings)
EarlyStoppingDelay	Minimum number of epochs or validation evaluations to wait before primary metric improvement is tracked for early stopping. Must be a positive integer. (Inherited from IImageModelDistributionSettings)
EarlyStoppingPatience	Minimum number of epochs or validation evaluations with no primary metric improvement before the run is stopped. Must be a positive integer. (Inherited from IImageModelDistributionSettings)
EnableOnnxNormalization	Enable normalization when exporting ONNX model. (Inherited from IImageModelDistributionSettings)
EvaluationFrequency	Frequency to evaluate validation dataset to get metric scores. Must be a positive integer. (Inherited from IImageModelDistributionSettings)
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. (Inherited from IImageModelDistributionSettings)
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. (Inherited from IImageModelDistributionSettings)
LearningRate	Initial learning rate. Must be a float in the range [0, 1]. (Inherited from IImageModelDistributionSettings)
LearningRateScheduler	Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'. (Inherited from IImageModelDistributionSettings)
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. (Inherited from IImageModelDistributionSettings)
Momentum	Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1]. (Inherited from IImageModelDistributionSettings)
Nesterov	Enable nesterov when optimizer is 'sgd'. (Inherited from IImageModelDistributionSettings)
NumberOfEpoch	Number of training epochs. Must be a positive integer. (Inherited from IImageModelDistributionSettings)
NumberOfWorker	Number of data loader workers. Must be a non-negative integer. (Inherited from IImageModelDistributionSettings)
Optimizer	Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'. (Inherited from IImageModelDistributionSettings)
RandomSeed	Random seed to be used when using deterministic training. (Inherited from IImageModelDistributionSettings)
StepLrGamma	Value of gamma when learning rate scheduler is 'step'. Must be a float in the range [0, 1]. (Inherited from IImageModelDistributionSettings)
StepLrStepSize	Value of step size when learning rate scheduler is 'step'. Must be a positive integer. (Inherited from IImageModelDistributionSettings)
TrainingBatchSize	Training batch size. Must be a positive integer. (Inherited from IImageModelDistributionSettings)
TrainingCropSize	Image crop size that is input to the neural network for the training dataset. Must be a positive integer.
ValidationBatchSize	Validation batch size. Must be a positive integer. (Inherited from IImageModelDistributionSettings)
ValidationCropSize	Image crop size that is input to the neural network for the validation dataset. Must be a positive integer.
ValidationResizeSize	Image size to which to resize before cropping for validation dataset. 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]. (Inherited from IImageModelDistributionSettings)
WarmupCosineLrWarmupEpoch	Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer. (Inherited from IImageModelDistributionSettings)
WeightDecay	Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be a float in the range[0, 1]. (Inherited from IImageModelDistributionSettings)
WeightedLoss	Weighted loss. The accepted values are 0 for no weighted loss. 1 for weighted loss with sqrt.(class_weights). 2 for weighted loss with class_weights. Must be 0 or 1 or 2.

Methods

ToJson(JsonObject, SerializationMode)

(Inherited from IJsonSerializable)

Applies to

Delen via