Package com.azure.resourcemanager.machinelearning.models

Class ImageModelSettings

java.lang.Object
com.azure.resourcemanager.machinelearning.models.ImageModelSettings
All Implemented Interfaces:
com.azure.json.JsonSerializable<ImageModelSettings>
Direct Known Subclasses:
ImageModelSettingsClassification, ImageModelSettingsObjectDetection
public class ImageModelSettings extends Object implements com.azure.json.JsonSerializable<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

    • ImageModelSettings

      public ImageModelSettings()
      Creates an instance of ImageModelSettings class.

  • Method Details

    • amsGradient

      public Boolean amsGradient()
      Get the amsGradient property: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
      Returns:
      the amsGradient value.

    • withAmsGradient

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

    • advancedSettings

      public String advancedSettings()
      Get the advancedSettings property: Settings for advanced scenarios.
      Returns:
      the advancedSettings value.

    • withAdvancedSettings

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

    • augmentations

      public String augmentations()
      Get the augmentations property: Settings for using Augmentations.
      Returns:
      the augmentations value.

    • withAugmentations

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

    • beta1

      public Float beta1()
      Get the beta1 property: Value of 'beta1' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].
      Returns:
      the beta1 value.

    • withBeta1

      public ImageModelSettings 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].
      Parameters:
      beta1 - the beta1 value to set.
      Returns:
      the ImageModelSettings object itself.

    • beta2

      public Float beta2()
      Get the beta2 property: Value of 'beta2' when optimizer is 'adam' or 'adamw'. Must be a float in the range [0, 1].
      Returns:
      the beta2 value.

    • withBeta2

      public ImageModelSettings 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].
      Parameters:
      beta2 - the beta2 value to set.
      Returns:
      the ImageModelSettings object itself.

    • checkpointFrequency

      public Integer checkpointFrequency()
      Get the checkpointFrequency property: Frequency to store model checkpoints. Must be a positive integer.
      Returns:
      the checkpointFrequency value.

    • withCheckpointFrequency

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

    • checkpointRunId

      public String checkpointRunId()
      Get the checkpointRunId property: The id of a previous run that has a pretrained checkpoint for incremental training.
      Returns:
      the checkpointRunId value.

    • withCheckpointRunId

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

    • checkpointModel

      public MLFlowModelJobInput checkpointModel()
      Get the checkpointModel property: The pretrained checkpoint model for incremental training.
      Returns:
      the checkpointModel value.

    • withCheckpointModel

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

    • distributed

      public Boolean distributed()
      Get the distributed property: Whether to use distributed training.
      Returns:
      the distributed value.

    • withDistributed

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

    • earlyStopping

      public Boolean earlyStopping()
      Get the earlyStopping property: Enable early stopping logic during training.
      Returns:
      the earlyStopping value.

    • withEarlyStopping

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

    • earlyStoppingDelay

      public Integer earlyStoppingDelay()
      Get 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.
      Returns:
      the earlyStoppingDelay value.

    • withEarlyStoppingDelay

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

    • earlyStoppingPatience

      public Integer earlyStoppingPatience()
      Get 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.
      Returns:
      the earlyStoppingPatience value.

    • withEarlyStoppingPatience

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

    • evaluationFrequency

      public Integer evaluationFrequency()
      Get the evaluationFrequency property: Frequency to evaluate validation dataset to get metric scores. Must be a positive integer.
      Returns:
      the evaluationFrequency value.

    • withEvaluationFrequency

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

    • enableOnnxNormalization

      public Boolean enableOnnxNormalization()
      Get the enableOnnxNormalization property: Enable normalization when exporting ONNX model.
      Returns:
      the enableOnnxNormalization value.

    • withEnableOnnxNormalization

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

    • gradientAccumulationStep

      public Integer gradientAccumulationStep()
      Get 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.
      Returns:
      the gradientAccumulationStep value.

    • withGradientAccumulationStep

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

    • layersToFreeze

      public Integer layersToFreeze()
      Get 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.
      Returns:
      the layersToFreeze value.

    • withLayersToFreeze

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

    • learningRate

      public Float learningRate()
      Get the learningRate property: Initial learning rate. Must be a float in the range [0, 1].
      Returns:
      the learningRate value.

    • withLearningRate

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

    • learningRateScheduler

      public LearningRateScheduler learningRateScheduler()
      Get the learningRateScheduler property: Type of learning rate scheduler. Must be 'warmup_cosine' or 'step'.
      Returns:
      the learningRateScheduler value.

    • withLearningRateScheduler

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

    • modelName

      public String modelName()
      Get 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.
      Returns:
      the modelName value.

    • withModelName

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

    • momentum

      public Float momentum()
      Get the momentum property: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
      Returns:
      the momentum value.

    • withMomentum

      public ImageModelSettings withMomentum(Float momentum)
      Set the momentum property: Value of momentum when optimizer is 'sgd'. Must be a float in the range [0, 1].
      Parameters:
      momentum - the momentum value to set.
      Returns:
      the ImageModelSettings object itself.

    • nesterov

      public Boolean nesterov()
      Get the nesterov property: Enable nesterov when optimizer is 'sgd'.
      Returns:
      the nesterov value.

    • withNesterov

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

    • numberOfEpochs

      public Integer numberOfEpochs()
      Get the numberOfEpochs property: Number of training epochs. Must be a positive integer.
      Returns:
      the numberOfEpochs value.

    • withNumberOfEpochs

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

    • numberOfWorkers

      public Integer numberOfWorkers()
      Get the numberOfWorkers property: Number of data loader workers. Must be a non-negative integer.
      Returns:
      the numberOfWorkers value.

    • withNumberOfWorkers

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

    • optimizer

      public StochasticOptimizer optimizer()
      Get the optimizer property: Type of optimizer.
      Returns:
      the optimizer value.

    • withOptimizer

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

    • randomSeed

      public Integer randomSeed()
      Get the randomSeed property: Random seed to be used when using deterministic training.
      Returns:
      the randomSeed value.

    • withRandomSeed

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

    • stepLRGamma

      public Float stepLRGamma()
      Get the stepLRGamma property: Value of gamma when learning rate scheduler is 'step'. Must be a float in the range [0, 1].
      Returns:
      the stepLRGamma value.

    • withStepLRGamma

      public ImageModelSettings 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].
      Parameters:
      stepLRGamma - the stepLRGamma value to set.
      Returns:
      the ImageModelSettings object itself.

    • stepLRStepSize

      public Integer stepLRStepSize()
      Get the stepLRStepSize property: Value of step size when learning rate scheduler is 'step'. Must be a positive integer.
      Returns:
      the stepLRStepSize value.

    • withStepLRStepSize

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

    • trainingBatchSize

      public Integer trainingBatchSize()
      Get the trainingBatchSize property: Training batch size. Must be a positive integer.
      Returns:
      the trainingBatchSize value.

    • withTrainingBatchSize

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

    • validationBatchSize

      public Integer validationBatchSize()
      Get the validationBatchSize property: Validation batch size. Must be a positive integer.
      Returns:
      the validationBatchSize value.

    • withValidationBatchSize

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

    • warmupCosineLRCycles

      public Float warmupCosineLRCycles()
      Get the warmupCosineLRCycles property: Value of cosine cycle when learning rate scheduler is 'warmup_cosine'. Must be a float in the range [0, 1].
      Returns:
      the warmupCosineLRCycles value.

    • withWarmupCosineLRCycles

      public ImageModelSettings 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].
      Parameters:
      warmupCosineLRCycles - the warmupCosineLRCycles value to set.
      Returns:
      the ImageModelSettings object itself.

    • warmupCosineLRWarmupEpochs

      public Integer warmupCosineLRWarmupEpochs()
      Get the warmupCosineLRWarmupEpochs property: Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer.
      Returns:
      the warmupCosineLRWarmupEpochs value.

    • withWarmupCosineLRWarmupEpochs

      public ImageModelSettings withWarmupCosineLRWarmupEpochs(Integer warmupCosineLRWarmupEpochs)
      Set the warmupCosineLRWarmupEpochs property: Value of warmup epochs when learning rate scheduler is 'warmup_cosine'. Must be a positive integer.
      Parameters:
      warmupCosineLRWarmupEpochs - the warmupCosineLRWarmupEpochs value to set.
      Returns:
      the ImageModelSettings object itself.

    • weightDecay

      public Float weightDecay()
      Get the weightDecay property: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'. Must be a float in the range[0, 1].
      Returns:
      the weightDecay value.

    • withWeightDecay

      public ImageModelSettings 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].
      Parameters:
      weightDecay - the weightDecay value to set.
      Returns:
      the ImageModelSettings object itself.

    • validate

      public void validate()
      Validates the instance.
      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>
      Throws:
      IOException

    • fromJson

      public static ImageModelSettings fromJson(com.azure.json.JsonReader jsonReader) throws IOException
      Reads an instance of ImageModelSettings from the JsonReader.
      Parameters:
      jsonReader - The JsonReader being read.
      Returns:
      An instance of ImageModelSettings 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 ImageModelSettings.