Trainers

Here are implemented the trainers used to train the Autoencoder models

BaseTrainer	Base class to perform model training.
CoupledOptimizerTrainer	Trainer using distinct optimizers for encoder and decoder nn.
AdversarialTrainer	Trainer using distinct optimizers for the autoencoder and the discriminator.
CoupledOptimizerAdversarialTrainer	Trainer using distinct optimizers for the encoder, decoder and discriminator.

Training Callbacks

Training Callbacks for training monitoring integrated in pythae (inspired from https://github.com/huggingface/transformers/blob/master/src/transformers/trainer_callback.py)

TrainingCallback	Base class for creating training callbacks
CallbackHandler	Class to handle list of Callback.
MetricConsolePrinterCallback	A TrainingCallback printing the training logs in the console.
ProgressBarCallback	A TrainingCallback printing the training progress bar.
WandbCallback	A TrainingCallback integrating the experiment tracking tool wandb (https://wandb.ai/).
MLFlowCallback	A TrainingCallback integrating the experiment tracking tool mlflow (https://mlflow.org/).
CometCallback	A TrainingCallback integrating the experiment tracking tool comet_ml (https://www.comet.com/site/).