java.lang.Object
- com.azure.resourcemanager.machinelearning.models.ImageModelDistributionSettings
- - com.azure.resourcemanager.machinelearning.models.ImageModelDistributionSettingsClassification

```
public final class ImageModelDistributionSettingsClassification
extends ImageModelDistributionSettings
```
Distribution expressions to sweep over values of model settings. <example> Some examples are: <code> ModelName = "choice('seresnext', 'resnest50')"; LearningRate = "uniform(0.001, 0.01)"; LayersToFreeze = "choice(0, 2)"; </code></example> For more details on how to compose distribution expressions please check the documentation: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters 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.

Constructor Summary

Constructors
Constructor Description

ImageModelDistributionSettingsClassification()

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`String`	`trainingCropSize()`	Get the trainingCropSize property: Image crop size that is input to the neural network for the training dataset.
`void`	`validate()`	Validates the instance.
`String`	`validationCropSize()`	Get the validationCropSize property: Image crop size that is input to the neural network for the validation dataset.
`String`	`validationResizeSize()`	Get the validationResizeSize property: Image size to which to resize before cropping for validation dataset.
`String`	`weightedLoss()`	Get the weightedLoss property: Weighted loss.
`ImageModelDistributionSettingsClassification`	`withAmsGradient(String amsGradient)`	Set the amsGradient property: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
`ImageModelDistributionSettingsClassification`	`withAugmentations(String augmentations)`	Set the augmentations property: Settings for using Augmentations.
`ImageModelDistributionSettingsClassification`	`withBeta1(String beta1)`	Set the beta1 property: Value of 'beta1' when optimizer is 'adam' or 'adamw'.
`ImageModelDistributionSettingsClassification`	`withBeta2(String beta2)`	Set the beta2 property: Value of 'beta2' when optimizer is 'adam' or 'adamw'.
`ImageModelDistributionSettingsClassification`	`withDistributed(String distributed)`	Set the distributed property: Whether to use distributer training.
`ImageModelDistributionSettingsClassification`	`withEarlyStopping(String earlyStopping)`	Set the earlyStopping property: Enable early stopping logic during training.
`ImageModelDistributionSettingsClassification`	`withEarlyStoppingDelay(String earlyStoppingDelay)`	Set the earlyStoppingDelay property: Minimum number of epochs or validation evaluations to wait before primary metric improvement is tracked for early stopping.
`ImageModelDistributionSettingsClassification`	`withEarlyStoppingPatience(String earlyStoppingPatience)`	Set the earlyStoppingPatience property: Minimum number of epochs or validation evaluations with no primary metric improvement before the run is stopped.
`ImageModelDistributionSettingsClassification`	`withEnableOnnxNormalization(String enableOnnxNormalization)`	Set the enableOnnxNormalization property: Enable normalization when exporting ONNX model.
`ImageModelDistributionSettingsClassification`	`withEvaluationFrequency(String evaluationFrequency)`	Set the evaluationFrequency property: Frequency to evaluate validation dataset to get metric scores.
`ImageModelDistributionSettingsClassification`	`withGradientAccumulationStep(String gradientAccumulationStep)`	Set the gradientAccumulationStep property: 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.
`ImageModelDistributionSettingsClassification`	`withLayersToFreeze(String layersToFreeze)`	Set the layersToFreeze property: Number of layers to freeze for the model.
`ImageModelDistributionSettingsClassification`	`withLearningRate(String learningRate)`	Set the learningRate property: Initial learning rate.
`ImageModelDistributionSettingsClassification`	`withLearningRateScheduler(String learningRateScheduler)`	Set the learningRateScheduler property: Type of learning rate scheduler.
`ImageModelDistributionSettingsClassification`	`withModelName(String modelName)`	Set the modelName property: Name of the model to use for training.
`ImageModelDistributionSettingsClassification`	`withMomentum(String momentum)`	Set the momentum property: Value of momentum when optimizer is 'sgd'.
`ImageModelDistributionSettingsClassification`	`withNesterov(String nesterov)`	Set the nesterov property: Enable nesterov when optimizer is 'sgd'.
`ImageModelDistributionSettingsClassification`	`withNumberOfEpochs(String numberOfEpochs)`	Set the numberOfEpochs property: Number of training epochs.
`ImageModelDistributionSettingsClassification`	`withNumberOfWorkers(String numberOfWorkers)`	Set the numberOfWorkers property: Number of data loader workers.
`ImageModelDistributionSettingsClassification`	`withOptimizer(String optimizer)`	Set the optimizer property: Type of optimizer.
`ImageModelDistributionSettingsClassification`	`withRandomSeed(String randomSeed)`	Set the randomSeed property: Random seed to be used when using deterministic training.
`ImageModelDistributionSettingsClassification`	`withSplitRatio(String splitRatio)`	Set the splitRatio property: If validation data is not defined, this specifies the split ratio for splitting train data into random train and validation subsets.
`ImageModelDistributionSettingsClassification`	`withStepLRGamma(String stepLRGamma)`	Set the stepLRGamma property: Value of gamma when learning rate scheduler is 'step'.
`ImageModelDistributionSettingsClassification`	`withStepLRStepSize(String stepLRStepSize)`	Set the stepLRStepSize property: Value of step size when learning rate scheduler is 'step'.
`ImageModelDistributionSettingsClassification`	`withTrainingBatchSize(String trainingBatchSize)`	Set the trainingBatchSize property: Training batch size.
`ImageModelDistributionSettingsClassification`	`withTrainingCropSize(String trainingCropSize)`	Set the trainingCropSize property: Image crop size that is input to the neural network for the training dataset.
`ImageModelDistributionSettingsClassification`	`withValidationBatchSize(String validationBatchSize)`	Set the validationBatchSize property: Validation batch size.
`ImageModelDistributionSettingsClassification`	`withValidationCropSize(String validationCropSize)`	Set the validationCropSize property: Image crop size that is input to the neural network for the validation dataset.
`ImageModelDistributionSettingsClassification`	`withValidationResizeSize(String validationResizeSize)`	Set the validationResizeSize property: Image size to which to resize before cropping for validation dataset.
`ImageModelDistributionSettingsClassification`	`withWarmupCosineLRCycles(String warmupCosineLRCycles)`	Set the warmupCosineLRCycles property: Value of cosine cycle when learning rate scheduler is 'warmup_cosine'.
`ImageModelDistributionSettingsClassification`	`withWarmupCosineLRWarmupEpochs(String warmupCosineLRWarmupEpochs)`	Set the warmupCosineLRWarmupEpochs property: Value of warmup epochs when learning rate scheduler is 'warmup_cosine'.
`ImageModelDistributionSettingsClassification`	`withWeightDecay(String weightDecay)`	Set the weightDecay property: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'.
`ImageModelDistributionSettingsClassification`	`withWeightedLoss(String weightedLoss)`	Set the weightedLoss property: Weighted loss.

Methods inherited from class com.azure.resourcemanager.machinelearning.models.ImageModelDistributionSettings
amsGradient, augmentations, beta1, beta2, distributed, earlyStopping, earlyStoppingDelay, earlyStoppingPatience, enableOnnxNormalization, evaluationFrequency, gradientAccumulationStep, layersToFreeze, learningRate, learningRateScheduler, modelName, momentum, nesterov, numberOfEpochs, numberOfWorkers, optimizer, randomSeed, splitRatio, stepLRGamma, stepLRStepSize, trainingBatchSize, validationBatchSize, warmupCosineLRCycles, warmupCosineLRWarmupEpochs, weightDecay

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - ImageModelDistributionSettingsClassification
```
public ImageModelDistributionSettingsClassification()
```
- Method Detail
  - trainingCropSize
```
public String trainingCropSize()
```
    Get the trainingCropSize property: Image crop size that is input to the neural network for the training dataset. Must be a positive integer.
    
    Returns:
    
    the trainingCropSize value.
  - withTrainingCropSize
```
public ImageModelDistributionSettingsClassification withTrainingCropSize(String trainingCropSize)
```
    Set the trainingCropSize property: Image crop size that is input to the neural network for the training dataset. Must be a positive integer.
    
    Parameters:
    
    trainingCropSize - the trainingCropSize value to set.
    
    Returns:
    
    the ImageModelDistributionSettingsClassification object itself.
  - validationCropSize
```
public String validationCropSize()
```
    Get the validationCropSize property: Image crop size that is input to the neural network for the validation dataset. Must be a positive integer.
    
    Returns:
    
    the validationCropSize value.
  - withValidationCropSize
```
public ImageModelDistributionSettingsClassification withValidationCropSize(String validationCropSize)
```
    Set the validationCropSize property: Image crop size that is input to the neural network for the validation dataset. Must be a positive integer.
    
    Parameters:
    
    validationCropSize - the validationCropSize value to set.
    
    Returns:
    
    the ImageModelDistributionSettingsClassification object itself.
  - validationResizeSize
```
public String validationResizeSize()
```
    Get the validationResizeSize property: Image size to which to resize before cropping for validation dataset. Must be a positive integer.
    
    Returns:
    
    the validationResizeSize value.
  - withValidationResizeSize
```
public ImageModelDistributionSettingsClassification withValidationResizeSize(String validationResizeSize)
```
    Set the validationResizeSize property: Image size to which to resize before cropping for validation dataset. Must be a positive integer.
    
    Parameters:
    
    validationResizeSize - the validationResizeSize value to set.
    
    Returns:
    
    the ImageModelDistributionSettingsClassification object itself.
  - weightedLoss
```
public String weightedLoss()
```
    Get the weightedLoss property: 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.
    
    Returns:
    
    the weightedLoss value.
  - withWeightedLoss
```
public ImageModelDistributionSettingsClassification withWeightedLoss(String weightedLoss)
```
    Set the weightedLoss property: 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.
    
    Parameters:
    
    weightedLoss - the weightedLoss value to set.
    
    Returns:
    
    the ImageModelDistributionSettingsClassification object itself.
  - withAmsGradient
```
public ImageModelDistributionSettingsClassification withAmsGradient(String amsGradient)
```
    Set the amsGradient property: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
    
    Overrides:
    
    withAmsGradient in class ImageModelDistributionSettings
    
    Parameters:
    
    amsGradient - the amsGradient value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withAugmentations
```
public ImageModelDistributionSettingsClassification withAugmentations(String augmentations)
```
    Set the augmentations property: Settings for using Augmentations.
    
    Overrides:
    
    withAugmentations in class ImageModelDistributionSettings
    
    Parameters:
    
    augmentations - the augmentations value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withBeta1
```
public ImageModelDistributionSettingsClassification withBeta1(String beta1)
```
    Set the beta1 property: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].
    
    Overrides:
    
    withBeta1 in class ImageModelDistributionSettings
    
    Parameters:
    
    beta1 - the beta1 value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withBeta2
```
public ImageModelDistributionSettingsClassification withBeta2(String beta2)
```
    Set the beta2 property: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].
    
    Overrides:
    
    withBeta2 in class ImageModelDistributionSettings
    
    Parameters:
    
    beta2 - the beta2 value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withDistributed
```
public ImageModelDistributionSettingsClassification withDistributed(String distributed)
```
    Set the distributed property: Whether to use distributer training.
    
    Overrides:
    
    withDistributed in class ImageModelDistributionSettings
    
    Parameters:
    
    distributed - the distributed value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withEarlyStopping
```
public ImageModelDistributionSettingsClassification withEarlyStopping(String earlyStopping)
```
    Set the earlyStopping property: Enable early stopping logic during training.
    
    Overrides:
    
    withEarlyStopping in class ImageModelDistributionSettings
    
    Parameters:
    
    earlyStopping - the earlyStopping value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withEarlyStoppingDelay
```
public ImageModelDistributionSettingsClassification withEarlyStoppingDelay(String earlyStoppingDelay)
```
    Set the earlyStoppingDelay property: Minimum number of epochs or validation evaluations to wait before primary metric improvement is tracked for early stopping. Must be a positive integer.
    
    Overrides:
    
    withEarlyStoppingDelay in class ImageModelDistributionSettings
    
    Parameters:
    
    earlyStoppingDelay - the earlyStoppingDelay value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withEarlyStoppingPatience
```
public ImageModelDistributionSettingsClassification withEarlyStoppingPatience(String earlyStoppingPatience)
```
    Set the earlyStoppingPatience property: Minimum number of epochs or validation evaluations with no primary metric improvement before the run is stopped. Must be a positive integer.
    
    Overrides:
    
    withEarlyStoppingPatience in class ImageModelDistributionSettings
    
    Parameters:
    
    earlyStoppingPatience - the earlyStoppingPatience value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withEnableOnnxNormalization
```
public ImageModelDistributionSettingsClassification withEnableOnnxNormalization(String enableOnnxNormalization)
```
    Set the enableOnnxNormalization property: Enable normalization when exporting ONNX model.
    
    Overrides:
    
    withEnableOnnxNormalization in class ImageModelDistributionSettings
    
    Parameters:
    
    enableOnnxNormalization - the enableOnnxNormalization value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withEvaluationFrequency
```
public ImageModelDistributionSettingsClassification withEvaluationFrequency(String evaluationFrequency)
```
    Set the evaluationFrequency property: Frequency to evaluate validation dataset to get metric scores. Must be a positive integer.
    
    Overrides:
    
    withEvaluationFrequency in class ImageModelDistributionSettings
    
    Parameters:
    
    evaluationFrequency - the evaluationFrequency value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withGradientAccumulationStep
```
public ImageModelDistributionSettingsClassification withGradientAccumulationStep(String gradientAccumulationStep)
```
    Set the gradientAccumulationStep property: 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.
    
    Overrides:
    
    withGradientAccumulationStep in class ImageModelDistributionSettings
    
    Parameters:
    
    gradientAccumulationStep - the gradientAccumulationStep value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withLayersToFreeze
```
public ImageModelDistributionSettingsClassification withLayersToFreeze(String layersToFreeze)
```
    Set the layersToFreeze property: 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.
    
    Overrides:
    
    withLayersToFreeze in class ImageModelDistributionSettings
    
    Parameters:
    
    layersToFreeze - the layersToFreeze value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withLearningRate
```
public ImageModelDistributionSettingsClassification withLearningRate(String learningRate)
```
    Set the learningRate property: Initial learning rate. Must be a float in the range [0, 1].
    
    Overrides:
    
    withLearningRate in class ImageModelDistributionSettings
    
    Parameters:
    
    learningRate - the learningRate value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withLearningRateScheduler
```
public ImageModelDistributionSettingsClassification withLearningRateScheduler(String learningRateScheduler)
```
    Set the learningRateScheduler property: Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'.
    
    Overrides:
    
    withLearningRateScheduler in class ImageModelDistributionSettings
    
    Parameters:
    
    learningRateScheduler - the learningRateScheduler value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withModelName
```
public ImageModelDistributionSettingsClassification withModelName(String modelName)
```
    Set the modelName property: 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.
    
    Overrides:
    
    withModelName in class ImageModelDistributionSettings
    
    Parameters:
    
    modelName - the modelName value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withMomentum
```
public ImageModelDistributionSettingsClassification withMomentum(String momentum)
```
    Set the momentum property: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
    
    Overrides:
    
    withMomentum in class ImageModelDistributionSettings
    
    Parameters:
    
    momentum - the momentum value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withNesterov
```
public ImageModelDistributionSettingsClassification withNesterov(String nesterov)
```
    Set the nesterov property: Enable nesterov when optimizer is 'sgd'.
    
    Overrides:
    
    withNesterov in class ImageModelDistributionSettings
    
    Parameters:
    
    nesterov - the nesterov value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withNumberOfEpochs
```
public ImageModelDistributionSettingsClassification withNumberOfEpochs(String numberOfEpochs)
```
    Set the numberOfEpochs property: Number of training epochs. Must be a positive integer.
    
    Overrides:
    
    withNumberOfEpochs in class ImageModelDistributionSettings
    
    Parameters:
    
    numberOfEpochs - the numberOfEpochs value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withNumberOfWorkers
```
public ImageModelDistributionSettingsClassification withNumberOfWorkers(String numberOfWorkers)
```
    Set the numberOfWorkers property: Number of data loader workers. Must be a non-negative integer.
    
    Overrides:
    
    withNumberOfWorkers in class ImageModelDistributionSettings
    
    Parameters:
    
    numberOfWorkers - the numberOfWorkers value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withOptimizer
```
public ImageModelDistributionSettingsClassification withOptimizer(String optimizer)
```
    Set the optimizer property: Type of optimizer. Must be either 'sgd', 'adam', or 'adamw'.
    
    Overrides:
    
    withOptimizer in class ImageModelDistributionSettings
    
    Parameters:
    
    optimizer - the optimizer value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withRandomSeed
```
public ImageModelDistributionSettingsClassification withRandomSeed(String randomSeed)
```
    Set the randomSeed property: Random seed to be used when using deterministic training.
    
    Overrides:
    
    withRandomSeed in class ImageModelDistributionSettings
    
    Parameters:
    
    randomSeed - the randomSeed value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withSplitRatio
```
public ImageModelDistributionSettingsClassification withSplitRatio(String splitRatio)
```
    Set the splitRatio property: If validation data is not defined, this specifies the split ratio for splitting train data into random train and validation subsets. Must be a float in the range [0, 1].
    
    Overrides:
    
    withSplitRatio in class ImageModelDistributionSettings
    
    Parameters:
    
    splitRatio - the splitRatio value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withStepLRGamma
```
public ImageModelDistributionSettingsClassification withStepLRGamma(String stepLRGamma)
```
    Set the stepLRGamma property: Value of gamma when learning rate scheduler is 'step'. Must be a float in the range [0, 1].
    
    Overrides:
    
    withStepLRGamma in class ImageModelDistributionSettings
    
    Parameters:
    
    stepLRGamma - the stepLRGamma value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withStepLRStepSize
```
public ImageModelDistributionSettingsClassification withStepLRStepSize(String stepLRStepSize)
```
    Set the stepLRStepSize property: Value of step size when learning rate scheduler is 'step'. Must be a positive integer.
    
    Overrides:
    
    withStepLRStepSize in class ImageModelDistributionSettings
    
    Parameters:
    
    stepLRStepSize - the stepLRStepSize value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withTrainingBatchSize
```
public ImageModelDistributionSettingsClassification withTrainingBatchSize(String trainingBatchSize)
```
    Set the trainingBatchSize property: Training batch size. Must be a positive integer.
    
    Overrides:
    
    withTrainingBatchSize in class ImageModelDistributionSettings
    
    Parameters:
    
    trainingBatchSize - the trainingBatchSize value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withValidationBatchSize
```
public ImageModelDistributionSettingsClassification withValidationBatchSize(String validationBatchSize)
```
    Set the validationBatchSize property: Validation batch size. Must be a positive integer.
    
    Overrides:
    
    withValidationBatchSize in class ImageModelDistributionSettings
    
    Parameters:
    
    validationBatchSize - the validationBatchSize value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withWarmupCosineLRCycles
```
public ImageModelDistributionSettingsClassification withWarmupCosineLRCycles(String warmupCosineLRCycles)
```
    Set the warmupCosineLRCycles property: Value of cosine cycle when learning rate scheduler is 'warmup_cosine'. Must be a float in the range [0, 1].
    
    Overrides:
    
    withWarmupCosineLRCycles in class ImageModelDistributionSettings
    
    Parameters:
    
    warmupCosineLRCycles - the warmupCosineLRCycles value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withWarmupCosineLRWarmupEpochs
```
public ImageModelDistributionSettingsClassification withWarmupCosineLRWarmupEpochs(String warmupCosineLRWarmupEpochs)
```
    Set the warmupCosineLRWarmupEpochs property: Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer.
    
    Overrides:
    
    withWarmupCosineLRWarmupEpochs in class ImageModelDistributionSettings
    
    Parameters:
    
    warmupCosineLRWarmupEpochs - the warmupCosineLRWarmupEpochs value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - withWeightDecay
```
public ImageModelDistributionSettingsClassification withWeightDecay(String weightDecay)
```
    Set the weightDecay property: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be a float in the range[0, 1].
    
    Overrides:
    
    withWeightDecay in class ImageModelDistributionSettings
    
    Parameters:
    
    weightDecay - the weightDecay value to set.
    
    Returns:
    
    the ImageModelDistributionSettings object itself.
  - validate
```
public void validate()
```
    Validates the instance.
    
    Overrides:
    
    validate in class ImageModelDistributionSettings
    
    Throws:
    
    IllegalArgumentException - thrown if the instance is not valid.

Class ImageModelDistributionSettingsClassification

Constructor Summary

Method Summary

Methods inherited from class com.azure.resourcemanager.machinelearning.models.ImageModelDistributionSettings

Methods inherited from class java.lang.Object

Constructor Detail

ImageModelDistributionSettingsClassification

Method Detail

trainingCropSize

withTrainingCropSize

validationCropSize

withValidationCropSize

validationResizeSize

withValidationResizeSize

weightedLoss

withWeightedLoss

withAmsGradient

withAugmentations

withBeta1

withBeta2

withDistributed

withEarlyStopping

withEarlyStoppingDelay

withEarlyStoppingPatience

withEnableOnnxNormalization

withEvaluationFrequency

withGradientAccumulationStep

withLayersToFreeze

withLearningRate

withLearningRateScheduler

withModelName

withMomentum

withNesterov

withNumberOfEpochs

withNumberOfWorkers

withOptimizer

withRandomSeed

withSplitRatio

withStepLRGamma

withStepLRStepSize

withTrainingBatchSize

withValidationBatchSize

withWarmupCosineLRCycles

withWarmupCosineLRWarmupEpochs

withWeightDecay

validate