ImageModelDistributionSettings |
ImageModelDistributionSettings.withAmsGradient(String amsGradient) |
Set the amsGradient property: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withAugmentations(String augmentations) |
Set the augmentations property: Settings for using Augmentations.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withBeta1(String beta1) |
Set the beta1 property: Value of 'beta1' when optimizer is 'adam' or 'adamw'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withBeta2(String beta2) |
Set the beta2 property: Value of 'beta2' when optimizer is 'adam' or 'adamw'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withDistributed(String distributed) |
Set the distributed property: Whether to use distributer training.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withEarlyStopping(String earlyStopping) |
Set the earlyStopping property: Enable early stopping logic during training.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.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.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withEarlyStoppingPatience(String earlyStoppingPatience) |
Set the earlyStoppingPatience property: Minimum number of epochs or validation evaluations with no primary metric
improvement before the run is stopped.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withEnableOnnxNormalization(String enableOnnxNormalization) |
Set the enableOnnxNormalization property: Enable normalization when exporting ONNX model.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withEvaluationFrequency(String evaluationFrequency) |
Set the evaluationFrequency property: Frequency to evaluate validation dataset to get metric scores.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.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.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withLayersToFreeze(String layersToFreeze) |
Set the layersToFreeze property: Number of layers to freeze for the model.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withLearningRate(String learningRate) |
Set the learningRate property: Initial learning rate.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withLearningRateScheduler(String learningRateScheduler) |
Set the learningRateScheduler property: Type of learning rate scheduler.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withModelName(String modelName) |
Set the modelName property: Name of the model to use for training.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withMomentum(String momentum) |
Set the momentum property: Value of momentum when optimizer is 'sgd'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withNesterov(String nesterov) |
Set the nesterov property: Enable nesterov when optimizer is 'sgd'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withNumberOfEpochs(String numberOfEpochs) |
Set the numberOfEpochs property: Number of training epochs.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withNumberOfWorkers(String numberOfWorkers) |
Set the numberOfWorkers property: Number of data loader workers.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withOptimizer(String optimizer) |
Set the optimizer property: Type of optimizer.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withRandomSeed(String randomSeed) |
Set the randomSeed property: Random seed to be used when using deterministic training.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.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.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withStepLRGamma(String stepLRGamma) |
Set the stepLRGamma property: Value of gamma when learning rate scheduler is 'step'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withStepLRStepSize(String stepLRStepSize) |
Set the stepLRStepSize property: Value of step size when learning rate scheduler is 'step'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withTrainingBatchSize(String trainingBatchSize) |
Set the trainingBatchSize property: Training batch size.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withValidationBatchSize(String validationBatchSize) |
Set the validationBatchSize property: Validation batch size.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withWarmupCosineLRCycles(String warmupCosineLRCycles) |
Set the warmupCosineLRCycles property: Value of cosine cycle when learning rate scheduler is 'warmup_cosine'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withWarmupCosineLRWarmupEpochs(String warmupCosineLRWarmupEpochs) |
Set the warmupCosineLRWarmupEpochs property: Value of warmup epochs when learning rate scheduler is
'warmup_cosine'.
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ImageModelDistributionSettings |
ImageModelDistributionSettings.withWeightDecay(String weightDecay) |
Set the weightDecay property: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'.
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