Expand description
Train module
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§
- Classification
Output - Simple classification output adapted for multiple metrics.
- File
Application Logger Installer - This struct is used to install a local file application logger to output logs to a given file path.
- Learner
- Learner struct encapsulating all components necessary to train a Neural Network model.
- Learner
Builder - Struct to configure and create a learner.
- Learner
Summary - Detailed training summary.
- Metric
Early Stopping Strategy - An early stopping strategy based on a metrics collected during training or validation.
- Metric
Entry - Contains the metric value at a given time.
- Metric
Summary - Contains the summary of recorded values for a given metric.
- Multi
Devices Train Step - Multi devices train step.
- Multi
Label Classification Output - Multi-label classification output adapted for multiple metrics.
- Regression
Output - Simple regression output adapted for multiple metrics.
- Summary
Metrics - Contains the summary of recorded metrics for the training and validation steps.
- Train
Epoch - A training epoch.
- Train
Output - A training output.
- Training
Interrupter - A handle that allows aborting the training process early.
- Valid
Epoch - A validation epoch.
Enums§
- Stopping
Condition - The condition that early stopping strategies should follow.
Traits§
- Application
Logger Installer - This trait is used to install an application logger.
- Early
Stopping Strategy - A strategy that checks if the training should be stopped.
- Train
Step - Trait to be implemented for training models.
- Valid
Step - Trait to be implemented for validating models.