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)

Arguments

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

Details

****** Associated Functions: ******

on_train_cross_validation_end

train_on_session