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§
- Agent
EnvAsync Loop - An asynchronous agent/environement interface.
- Agent
EnvBase Loop - A simple, synchronized agent/environement interface.
- Async
Agent EnvLoop Config - Configuration for an async agent/environment loop.
- Async
Processor Evaluation - Event processor for the model evaluation.
- Async
Processor Training - Event processor for the training process.
- Classification
Output - Simple classification output adapted for multiple metrics.
- Episode
Summary - Summary of an episode.
- Evaluation
Item - An evaluation item.
- Evaluation
Result - The result of an evaluation.
- Evaluator
- Evaluates a model on a specific dataset.
- Evaluator
Builder - Struct to configure and create an evaluator.
- Evaluator
Component Types Marker - A marker type used to provide evaluation components.
- Event
Processor Error - Every failure an event processor reported at once, oldest first.
- File
Application Logger Installer - This struct is used to install a local file application logger to output logs to a given file path.
- Interrupter
- A handle that allows aborting the training/evaluation process early.
- Interruption
- A stop made through
Interrupter::stop, without an error. - Learner
- Learner struct encapsulating all components necessary to train a Neural Network model.
- Learner
Summary - Detailed training summary.
- Learner
Summary Config - Learning summary config.
- Learning
Checkpointer - Used to create, delete, or load checkpoints of the training process.
- Learning
Result - The result of a training, containing the model along with the renderer.
- 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
Error - A metric that could not process an event.
- Metric
Summary - Contains the summary of recorded values for a given metric.
- Module
Sharder - Describes how the module is distributed across multiple devices.
- Multi
Agent EnvLoop - An asynchronous runner for multiple agent/environement interfaces.
- Multi
Label Classification Output - Multi-label classification output adapted for multiple metrics.
- OffPolicy
Config - Parameters of an on policy training with multi environments and double-batching.
- OffPolicy
Strategy - Off-policy reinforcement learning strategy with multi-env experience collection and double-batching.
- RLCheckpointer
- Used to create, delete, or load checkpoints of the training process.
- RLComponents
- Struct to minimise parameters passed to RLStrategy::train.
- RLComponents
Marker - Concrete type that implements the RLComponentsTypes trait.
- RLEvent
Processor - An event processor that handles:
- RLResult
- The result of reinforcement learning, containing the final policy along with the renderer.
- RLTraining
- Structure to configure and launch reinforcement learning trainings.
- Regression
Output - Regression output adapted for the loss metric.
- Sequence
Output - Sequence prediction output adapted for multiple metrics.
- Summary
Metrics - Contains the summary of recorded metrics for the training and validation steps.
- Supervised
Training - Structure to configure and launch supervised learning trainings.
- Time
Step - A timestep debscribing an iteration of the state/decision process.
- Train
Output - A training output.
- Training
Components - Struct to minimise parameters passed to SupervisedLearningStrategy::train. These components are used during training.
- Training
Item - A learner item.
- Trajectory
- A trajectory, i.e. a list of ordered TimeStep.
Enums§
- Agent
Evaluation Event - Event happening during evaluation of a reinforcement learning’s agent.
- Evaluator
Event - Event happening during the evaluation process.
- Event
Processor Failure - A failure an event processor reported.
- Execution
Strategy - Describes where training runs.
- Learner
Event - Event happening during the training/validation process.
- Multi
Device Optim - Determine how the optimization is performed when training with multiple devices.
- RLEvent
- Event happening during reinforcement learning.
- RLStrategies
- The strategy for reinforcement learning.
- Stopping
Condition - The condition that early stopping strategies should follow.
- Training
Error - An error that stopped training or evaluation.
- Training
Strategy - How should the learner run the learning for the model
Traits§
- Agent
EnvLoop - Trait for a structure that implements an agent/environement interface.
- Agent
Metric Registration - Trait to fake variadic generics for train step metrics.
- Agent
Text Metric Registration - Trait to fake variadic generics for train step text metrics.
- Application
Logger Installer - This trait is used to install an application logger.
- Clone
Early Stopping Strategy - A helper trait to provide type-erased cloning.
- Early
Stopping Strategy - A strategy that checks if the training should be stopped.
- Episode
Metric Registration - Trait to fake variadic generics for episode metrics.
- Episode
Text Metric Registration - Trait to fake variadic generics for episode text metrics.
- Eval
Metric Registration - Trait to fake variadic generics.
- Eval
Text Metric Registration - Trait to fake variadic generics.
- Evaluator
Component Types - All components necessary to evaluate a model grouped in one trait.
- Event
Processor Evaluation - Process events happening during evaluation.
- Event
Processor Training - Process events happening during training and validation.
- Inference
Step - Trait to be implemented for validating models.
- Item
Lazy - Items that are lazy are not ready to be processed by metrics.
- Learner
Model - A single keyword trait for a Burn module used for learning.
- Metric
Registration - Trait to fake variadic generics.
- RLComponents
Types - All components used by the reinforcement learning paradigm, grouped in one trait.
- RLStrategy
- Provides the
fitfunction for any learning strategy - Supervised
Learning Strategy - Provides the
fitfunction for any learning strategy - Text
Metric Registration - Trait to fake variadic generics.
- Train
Metric Registration - Trait to fake variadic generics for env step metrics.
- Train
Step - Trait to be implemented for models to be able to be trained.
- Train
Text Metric Registration - Trait to fake variadic generics for env step text metrics.
Type Aliases§
- Custom
Learning Strategy - A reference to an implementation of SupervisedLearningStrategy.
- CustomRL
Strategy - A reference to an implementation of RLStrategy.
- RLAgent
Record - The record of the learning agent.
- RLEvent
Processor Type - The event processor type for reinforcement learning.
- RLPolicy
Record - The record of the policy.
- Supervised
Training Event Processor - The event processor type for supervised learning.
- Train
Loader - A reference to the training split DataLoader.
- Valid
Loader - A reference to the validation split DataLoader.