Getting started guide

First of all look at main classes of Neural Pipeline:

• Trainer - class, that implements training process
• TrainConfig - class, that store hyperparameters
• AbstractTrainStage - base class for single stage of training process. Don’t worry, Neural Pipeline have predefined classes for common use cases: TrainStage, ValidationStage and more common - StandardStage
• DataProducer - class, that unite datasets and unite it’s interface
• FileStructManager - class, that manage file structure

Training stages needed for customize training process. With it Trainer work by this scheme (dataflow scheme for single epoch):

Now step by step create training process:

• Create dataset
• Create TrainConfig
• Create Trainer
• Start training
  • Add Tensorboard monitor
• Continue training

After this tutorial look to segmentation example for explore how to work with specific metrics.