flair.trainers.plugins.TensorboardLogger#

class flair.trainers.plugins.TensorboardLogger(log_dir=None, comment='', tracked_metrics=())View on GitHub #

Plugin that takes care of tensorboard logging.

__init__(log_dir=None, comment='', tracked_metrics=())View on GitHub #

Initializes the TensorboardLogger.

Parameters:

log_dir – Directory into which tensorboard log files will be written
comment – The comment to specify Comment log_dir suffix appended to the default log_dir. If log_dir is assigned, this argument has no effect.
tracked_metrics – List of tuples that specify which metrics (in addition to the main_score) shall be plotted in tensorboard, could be [(“macro avg”, ‘f1-score’), (“macro avg”, ‘precision’)] for example

Methods

`__init__`([log_dir, comment, tracked_metrics])	Initializes the TensorboardLogger.
`attach_to`(pluggable)	Attach this plugin to a Pluggable.
`detach`()	Detach a plugin from the Pluggable it is attached to.
`get_state`()
`hook`([first_arg])	Convience function for BasePlugin.mark_func_as_hook).
`mark_func_as_hook`(func, *events)	Mark method as a hook triggered by the Pluggable.
`metric_recorded`(record)

Attributes

`attach_to_all_processes`	If set, the plugin will be attached to all processes when distributed, not just the main process.
`corpus`
`model`
`pluggable`
`trainer`

property attach_to_all_processes: bool#: If set, the plugin will be attached to all processes when distributed, not just the main process.