Package com.azure.resourcemanager.machinelearning.models

Class ImageModelSettingsClassification

java.lang.Object
com.azure.resourcemanager.machinelearning.models.ImageModelSettings
com.azure.resourcemanager.machinelearning.models.ImageModelSettingsClassification
All Implemented Interfaces:
com.azure.json.JsonSerializable<ImageModelSettings>
public final class ImageModelSettingsClassification extends ImageModelSettings
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.

  • Constructor Details

    • ImageModelSettingsClassification

      public ImageModelSettingsClassification()
      Creates an instance of ImageModelSettingsClassification class.

  • Method Details

    • trainingCropSize

      public Integer 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 ImageModelSettingsClassification withTrainingCropSize(Integer 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 ImageModelSettingsClassification object itself.

    • validationCropSize

      public Integer 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 ImageModelSettingsClassification withValidationCropSize(Integer 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 ImageModelSettingsClassification object itself.

    • validationResizeSize

      public Integer 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 ImageModelSettingsClassification withValidationResizeSize(Integer 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 ImageModelSettingsClassification object itself.

    • weightedLoss

      public Integer 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 ImageModelSettingsClassification withWeightedLoss(Integer 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 ImageModelSettingsClassification object itself.

    • withAmsGradient

      public ImageModelSettingsClassification withAmsGradient(Boolean amsGradient)
      Set the amsGradient property: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
      Overrides:
      withAmsGradient in class ImageModelSettings
      Parameters:
      amsGradient - the amsGradient value to set.
      Returns:
      the ImageModelSettings object itself.

    • withAdvancedSettings

      public ImageModelSettingsClassification withAdvancedSettings(String advancedSettings)
      Set the advancedSettings property: Settings for advanced scenarios.
      Overrides:
      withAdvancedSettings in class ImageModelSettings
      Parameters:
      advancedSettings - the advancedSettings value to set.
      Returns:
      the ImageModelSettings object itself.

    • withAugmentations

      public ImageModelSettingsClassification withAugmentations(String augmentations)
      Set the augmentations property: Settings for using Augmentations.
      Overrides:
      withAugmentations in class ImageModelSettings
      Parameters:
      augmentations - the augmentations value to set.
      Returns:
      the ImageModelSettings object itself.

    • withBeta1

      public ImageModelSettingsClassification withBeta1(Float 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 ImageModelSettings
      Parameters:
      beta1 - the beta1 value to set.
      Returns:
      the ImageModelSettings object itself.

    • withBeta2

      public ImageModelSettingsClassification withBeta2(Float 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 ImageModelSettings
      Parameters:
      beta2 - the beta2 value to set.
      Returns:
      the ImageModelSettings object itself.

    • withCheckpointFrequency

      public ImageModelSettingsClassification withCheckpointFrequency(Integer checkpointFrequency)
      Set the checkpointFrequency property: Frequency to store model checkpoints. Must be a positive integer.
      Overrides:
      withCheckpointFrequency in class ImageModelSettings
      Parameters:
      checkpointFrequency - the checkpointFrequency value to set.
      Returns:
      the ImageModelSettings object itself.

    • withCheckpointRunId

      public ImageModelSettingsClassification withCheckpointRunId(String checkpointRunId)
      Set the checkpointRunId property: The id of a previous run that has a pretrained checkpoint for incremental training.
      Overrides:
      withCheckpointRunId in class ImageModelSettings
      Parameters:
      checkpointRunId - the checkpointRunId value to set.
      Returns:
      the ImageModelSettings object itself.

    • withCheckpointModel

      public ImageModelSettingsClassification withCheckpointModel(MLFlowModelJobInput checkpointModel)
      Set the checkpointModel property: The pretrained checkpoint model for incremental training.
      Overrides:
      withCheckpointModel in class ImageModelSettings
      Parameters:
      checkpointModel - the checkpointModel value to set.
      Returns:
      the ImageModelSettings object itself.

    • withDistributed

      public ImageModelSettingsClassification withDistributed(Boolean distributed)
      Set the distributed property: Whether to use distributed training.
      Overrides:
      withDistributed in class ImageModelSettings
      Parameters:
      distributed - the distributed value to set.
      Returns:
      the ImageModelSettings object itself.

    • withEarlyStopping

      public ImageModelSettingsClassification withEarlyStopping(Boolean earlyStopping)
      Set the earlyStopping property: Enable early stopping logic during training.
      Overrides:
      withEarlyStopping in class ImageModelSettings
      Parameters:
      earlyStopping - the earlyStopping value to set.
      Returns:
      the ImageModelSettings object itself.

    • withEarlyStoppingDelay

      public ImageModelSettingsClassification withEarlyStoppingDelay(Integer 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 ImageModelSettings
      Parameters:
      earlyStoppingDelay - the earlyStoppingDelay value to set.
      Returns:
      the ImageModelSettings object itself.

    • withEarlyStoppingPatience

      public ImageModelSettingsClassification withEarlyStoppingPatience(Integer 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 ImageModelSettings
      Parameters:
      earlyStoppingPatience - the earlyStoppingPatience value to set.
      Returns:
      the ImageModelSettings object itself.

    • withEvaluationFrequency

      public ImageModelSettingsClassification withEvaluationFrequency(Integer evaluationFrequency)
      Set the evaluationFrequency property: Frequency to evaluate validation dataset to get metric scores. Must be a positive integer.
      Overrides:
      withEvaluationFrequency in class ImageModelSettings
      Parameters:
      evaluationFrequency - the evaluationFrequency value to set.
      Returns:
      the ImageModelSettings object itself.

    • withEnableOnnxNormalization

      public ImageModelSettingsClassification withEnableOnnxNormalization(Boolean enableOnnxNormalization)
      Set the enableOnnxNormalization property: Enable normalization when exporting ONNX model.
      Overrides:
      withEnableOnnxNormalization in class ImageModelSettings
      Parameters:
      enableOnnxNormalization - the enableOnnxNormalization value to set.
      Returns:
      the ImageModelSettings object itself.

    • withGradientAccumulationStep

      public ImageModelSettingsClassification withGradientAccumulationStep(Integer 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 ImageModelSettings
      Parameters:
      gradientAccumulationStep - the gradientAccumulationStep value to set.
      Returns:
      the ImageModelSettings object itself.

    • withLayersToFreeze

      public ImageModelSettingsClassification withLayersToFreeze(Integer 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 ImageModelSettings
      Parameters:
      layersToFreeze - the layersToFreeze value to set.
      Returns:
      the ImageModelSettings object itself.

    • withLearningRate

      public ImageModelSettingsClassification withLearningRate(Float learningRate)
      Set the learningRate property: Initial learning rate. Must be a float in the range [0, 1].
      Overrides:
      withLearningRate in class ImageModelSettings
      Parameters:
      learningRate - the learningRate value to set.
      Returns:
      the ImageModelSettings object itself.

    • withLearningRateScheduler

      public ImageModelSettingsClassification withLearningRateScheduler(LearningRateScheduler learningRateScheduler)
      Set the learningRateScheduler property: Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'.
      Overrides:
      withLearningRateScheduler in class ImageModelSettings
      Parameters:
      learningRateScheduler - the learningRateScheduler value to set.
      Returns:
      the ImageModelSettings object itself.

    • withModelName

      public ImageModelSettingsClassification 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 ImageModelSettings
      Parameters:
      modelName - the modelName value to set.
      Returns:
      the ImageModelSettings object itself.

    • withMomentum

      public ImageModelSettingsClassification withMomentum(Float 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 ImageModelSettings
      Parameters:
      momentum - the momentum value to set.
      Returns:
      the ImageModelSettings object itself.

    • withNesterov

      public ImageModelSettingsClassification withNesterov(Boolean nesterov)
      Set the nesterov property: Enable nesterov when optimizer is 'sgd'.
      Overrides:
      withNesterov in class ImageModelSettings
      Parameters:
      nesterov - the nesterov value to set.
      Returns:
      the ImageModelSettings object itself.

    • withNumberOfEpochs

      public ImageModelSettingsClassification withNumberOfEpochs(Integer numberOfEpochs)
      Set the numberOfEpochs property: Number of training epochs. Must be a positive integer.
      Overrides:
      withNumberOfEpochs in class ImageModelSettings
      Parameters:
      numberOfEpochs - the numberOfEpochs value to set.
      Returns:
      the ImageModelSettings object itself.

    • withNumberOfWorkers

      public ImageModelSettingsClassification withNumberOfWorkers(Integer numberOfWorkers)
      Set the numberOfWorkers property: Number of data loader workers. Must be a non-negative integer.
      Overrides:
      withNumberOfWorkers in class ImageModelSettings
      Parameters:
      numberOfWorkers - the numberOfWorkers value to set.
      Returns:
      the ImageModelSettings object itself.

    • withOptimizer

      public ImageModelSettingsClassification withOptimizer(StochasticOptimizer optimizer)
      Set the optimizer property: Type of optimizer.
      Overrides:
      withOptimizer in class ImageModelSettings
      Parameters:
      optimizer - the optimizer value to set.
      Returns:
      the ImageModelSettings object itself.

    • withRandomSeed

      public ImageModelSettingsClassification withRandomSeed(Integer randomSeed)
      Set the randomSeed property: Random seed to be used when using deterministic training.
      Overrides:
      withRandomSeed in class ImageModelSettings
      Parameters:
      randomSeed - the randomSeed value to set.
      Returns:
      the ImageModelSettings object itself.

    • withStepLRGamma

      public ImageModelSettingsClassification withStepLRGamma(Float 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 ImageModelSettings
      Parameters:
      stepLRGamma - the stepLRGamma value to set.
      Returns:
      the ImageModelSettings object itself.

    • withStepLRStepSize

      public ImageModelSettingsClassification withStepLRStepSize(Integer stepLRStepSize)
      Set the stepLRStepSize property: Value of step size when learning rate scheduler is 'step'. Must be a positive integer.
      Overrides:
      withStepLRStepSize in class ImageModelSettings
      Parameters:
      stepLRStepSize - the stepLRStepSize value to set.
      Returns:
      the ImageModelSettings object itself.

    • withTrainingBatchSize

      public ImageModelSettingsClassification withTrainingBatchSize(Integer trainingBatchSize)
      Set the trainingBatchSize property: Training batch size. Must be a positive integer.
      Overrides:
      withTrainingBatchSize in class ImageModelSettings
      Parameters:
      trainingBatchSize - the trainingBatchSize value to set.
      Returns:
      the ImageModelSettings object itself.

    • withValidationBatchSize

      public ImageModelSettingsClassification withValidationBatchSize(Integer validationBatchSize)
      Set the validationBatchSize property: Validation batch size. Must be a positive integer.
      Overrides:
      withValidationBatchSize in class ImageModelSettings
      Parameters:
      validationBatchSize - the validationBatchSize value to set.
      Returns:
      the ImageModelSettings object itself.

    • withWarmupCosineLRCycles

      public ImageModelSettingsClassification withWarmupCosineLRCycles(Float 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 ImageModelSettings
      Parameters:
      warmupCosineLRCycles - the warmupCosineLRCycles value to set.
      Returns:
      the ImageModelSettings object itself.

    • withWarmupCosineLRWarmupEpochs

      public ImageModelSettingsClassification withWarmupCosineLRWarmupEpochs(Integer 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 ImageModelSettings
      Parameters:
      warmupCosineLRWarmupEpochs - the warmupCosineLRWarmupEpochs value to set.
      Returns:
      the ImageModelSettings object itself.

    • withWeightDecay

      public ImageModelSettingsClassification withWeightDecay(Float 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 ImageModelSettings
      Parameters:
      weightDecay - the weightDecay value to set.
      Returns:
      the ImageModelSettings object itself.

    • validate

      public void validate()
      Validates the instance.
      Overrides:
      validate in class ImageModelSettings
      Throws:
      IllegalArgumentException - thrown if the instance is not valid.

    • toJson

      public com.azure.json.JsonWriter toJson(com.azure.json.JsonWriter jsonWriter) throws IOException
      Specified by:
      toJson in interface com.azure.json.JsonSerializable<ImageModelSettings>
      Overrides:
      toJson in class ImageModelSettings
      Throws:
      IOException

    • fromJson

      public static ImageModelSettingsClassification fromJson(com.azure.json.JsonReader jsonReader) throws IOException
      Reads an instance of ImageModelSettingsClassification from the JsonReader.
      Parameters:
      jsonReader - The JsonReader being read.
      Returns:
      An instance of ImageModelSettingsClassification if the JsonReader was pointing to an instance of it, or null if it was pointing to JSON null.
      Throws:
      IOException - If an error occurs while reading the ImageModelSettingsClassification.