speechbrain.utils.train_logger module¶

Loggers for experiment monitoring.

Authors

Summary¶

Classes:

`FileTrainLogger`	Text logger of training information.
`TensorboardLogger`	Logs training information in the format required by Tensorboard.
`TrainLogger`	Abstract class defining an interface for training loggers.

class speechbrain.utils.train_logger.TrainLogger[source]¶

Abstract class defining an interface for training loggers.

log_stats(stats_meta, train_stats=None, valid_stats=None, test_stats=None, verbose=False)[source]¶

Log the stats for one epoch.

Parameters

stats_meta (dict of str:scalar pairs) – Meta information about the stats (e.g., epoch, learning-rate, etc.).
train_stats (dict of str:list pairs) – Each loss type is represented with a str : list pair including all the values for the training pass.
valid_stats (dict of str:list pairs) – Each loss type is represented with a str : list pair including all the values for the validation pass.
test_stats (dict of str:list pairs) – Each loss type is represented with a str : list pair including all the values for the test pass.
verbose (bool) – Whether to also put logging information to the standard logger.

class speechbrain.utils.train_logger.FileTrainLogger(save_file, precision=2)[source]¶

Text logger of training information.

Parameters

save_file (str) – The file to use for logging train information.
precision (int) – Number of decimal places to display. Default 2, example: 1.35e-5.
summary_fns (dict of str:function pairs) – Each summary function should take a list produced as output from a training/validation pass and summarize it to a single scalar.

log_stats(stats_meta, train_stats=None, valid_stats=None, test_stats=None, verbose=True)[source]¶: See TrainLogger.log_stats()

class speechbrain.utils.train_logger.TensorboardLogger(save_dir)[source]¶

Logs training information in the format required by Tensorboard.

Parameters: save_dir (str) – A directory for storing all the relevant logs.
Raises: ImportError if Tensorboard is not installed. –

log_stats(stats_meta, train_stats=None, valid_stats=None, test_stats=None, verbose=False)[source]¶: See TrainLogger.log_stats()