Crate burn_train

A library for training neural networks using the burn crate.

Modules

• checkpoint
  The checkpoint module.
• logger
  The logger module.
• metric
  The metric module.
• renderer
  Renderer modules to display metrics and training information.
• train
  The trainer module.

Structs

• ClassificationOutput
  Simple classification output adapted for multiple metrics.
• Learner
  Learner struct encapsulating all components necessary to train a Neural Network model.
• LearnerBuilder
  Struct to configure and create a learner.
• LearnerSummary
  Detailed training summary.
• MetricEarlyStoppingStrategy
  An early stopping strategy based on a metrics collected during training or validation.
• MetricEntry
  Contains the metric value at a given time.
• MetricSummary
  Contains the summary of recorded values for a given metric.
• MultiDevicesTrainStep
  Multi devices train step.
• MultiLabelClassificationOutput
  Multi-label classification output adapted for multiple metrics.
• RegressionOutput
  Simple regression output adapted for multiple metrics.
• SummaryMetrics
  Contains the summary of recorded metrics for the training and validation steps.
• TrainEpoch
  A training epoch.
• TrainOutput
  A training output.
• TrainingInterrupter
  A handle that allows aborting the training process early.
• ValidEpoch
  A validation epoch.

Enums

• StoppingCondition
  The condition that early stopping strategies should follow.

Traits

• EarlyStoppingStrategy
  A strategy that checks if the training should be stopped.
• TrainStep
  Trait to be implemented for training models.
• ValidStep
  Trait to be implemented for validating models.