ImageModelSettingsClassification Class

Definition

Namespace:

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

Assembly:

Az.MachineLearningServices.private.dll

Settings used for training the model. For more information on the available settings please visit the official documentation: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models.

[System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ImageModelSettingsClassificationTypeConverter))]
public class ImageModelSettingsClassification : Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IImageModelSettingsClassification, Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Runtime.IValidates

[<System.ComponentModel.TypeConverter(typeof(Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.ImageModelSettingsClassificationTypeConverter))>]
type ImageModelSettingsClassification = class
    interface IImageModelSettingsClassification
    interface IJsonSerializable
    interface IImageModelSettings
    interface IValidates

Public Class ImageModelSettingsClassification
Implements IImageModelSettingsClassification, IValidates

Inheritance

Object

ImageModelSettingsClassification

Attributes

TypeConverterAttribute

Implements

IImageModelSettings IImageModelSettingsClassification IJsonSerializable IValidates

Constructors

ImageModelSettingsClassification()

Creates an new ImageModelSettingsClassification instance.

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.
CheckpointModel	The pretrained checkpoint model for incremental training.
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.
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.
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].
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].
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

DeserializeFromDictionary(IDictionary)	Deserializes a IDictionary into an instance of ImageModelSettingsClassification.
DeserializeFromPSObject(PSObject)	Deserializes a PSObject into an instance of ImageModelSettingsClassification.
FromJson(JsonNode)	Deserializes a JsonNode into an instance of Microsoft.Azure.PowerShell.Cmdlets.MachineLearningServices.Models.Api20240401.IImageModelSettingsClassification.
FromJsonString(String)	Creates a new instance of ImageModelSettingsClassification, deserializing the content from a json string.
ToJson(JsonObject, SerializationMode)	Serializes this instance of ImageModelSettingsClassification into a JsonNode.
ToJsonString()	Serializes this instance to a json string.
ToString()
Validate(IEventListener)	Validates that this object meets the validation criteria.