inferno.trainers.callbacks.logging package¶

Submodules¶

inferno.trainers.callbacks.logging.base module¶

class inferno.trainers.callbacks.logging.base.Logger(log_directory=None)[source]¶

Bases: inferno.trainers.callbacks.base.Callback

A special callback for logging.

Loggers are special because they’re required to be serializable, whereas other callbacks have no such guarantees. In this regard, they jointly handled by trainers and the callback engine.

log_directory¶

set_log_directory(log_directory)[source]¶

inferno.trainers.callbacks.logging.tensorboard module¶

class inferno.trainers.callbacks.logging.tensorboard.TaggedImage(array, tag)[source]¶: Bases: object

class inferno.trainers.callbacks.logging.tensorboard.TensorboardLogger(log_directory=None, log_scalars_every=None, log_images_every=None, send_image_at_batch_indices='all', send_image_at_channel_indices='all', send_volume_at_z_indices='mid')[source]¶

Bases: inferno.trainers.callbacks.logging.base.Logger

Class to enable logging of training progress to Tensorboard.

Currently supports logging scalars and images.

end_of_training_iteration(**_)[source]¶

end_of_validation_run(**_)[source]¶

extract_images_from_batch(batch, base_tag=None, prefix=None)[source]¶

get_config()[source]¶

log_histogram(tag, values, step, bins=1000)[source]¶: Logs the histogram of a list/vector of values.

log_image_or_volume_batch(tag, batch, step=None)[source]¶

log_images(tag, images, step, image_format='CHW')[source]¶: Logs a list of images.

log_images_every¶

log_images_now¶

log_object(tag, object_, allow_scalar_logging=True, allow_image_logging=True)[source]¶

log_scalar(tag, value, step)[source]¶

tag : basestring: Name of the scalar

value step : int

training iteration

log_scalars_every¶

log_scalars_now¶

observe_state(key, observe_while='training')[source]¶

observe_states(keys, observe_while='training')[source]¶

observe_training_and_validation_state(key)[source]¶

observe_training_and_validation_states(keys)[source]¶

writer¶

Module contents¶

inferno.trainers.callbacks.logging.get_logger(name)[source]¶

class inferno.trainers.callbacks.logging.TensorboardLogger(log_directory=None, log_scalars_every=None, log_images_every=None, send_image_at_batch_indices='all', send_image_at_channel_indices='all', send_volume_at_z_indices='mid')[source]¶