The instance of the class should be created by using training_session() function. A training session trains a model using the specified trainer and configs. Different aspects of training such as data sources, checkpointing, cross validation, progress printing can be configured using the corresponding config classes.
TrainingSession(trainer, mb_source, mb_size, model_inputs_to_streams, max_samples, progress_frequency, checkpoint_config, cv_config, test_config)
| trainer | (Trainer): trainer |
|---|---|
| mb_source | (MinibatchSource): minibatch source used for training |
| mb_size | (minibatch_size_schedule or int): minibatch size schedule for training |
| model_inputs_to_streams | (dict): mapping between input variables and input streams |
| max_samples | (int): maximum number of samples used for training |
| progress_frequency | (int): frequency in samples for aggregated progress printing |
| checkpoint_config | (CheckpointConfig): checkpoint configuration |
| cv_config | (CrossValidationConfig): cross validation configuration |
| test_config | (TestConfig): test configuration |
****** Associated Functions: ******
on_train_cross_validation_end
train_on_session