neptunecontrib.monitoring.keras

Module Contents

Classes

NeptuneMonitor(experiment=None, prefix=’‘)

Logs Keras metrics to Neptune.

class neptunecontrib.monitoring.keras.NeptuneMonitor(experiment=None, prefix='')[source]

Bases: tensorflow.keras.callbacks.Callback

Logs Keras metrics to Neptune.

Goes over the last_metrics and smooth_loss after each batch and epoch and logs them to appropriate Neptune channels.

See the example experiment here TODO

Parameters
  • experimentneptune.Experiment, optional: Neptune experiment. If not provided, falls back on the current experiment.

  • prefix – str, optional: Prefix that should be added before the metric_name and valid_name before logging to the appropriate channel. Defaul is empty string (‘’).

Examples

Now, create Neptune experiment, instantiate the monitor and pass it to callbacks:

TODO update for keras

Note

You need to have Keras or Tensorflow 2 installed on your computer to use this module.

_log_metrics(self, logs, trigger)[source]
on_batch_end(self, batch, logs=None)[source]

A backwards compatibility alias for on_train_batch_end.

on_epoch_end(self, epoch, logs=None)[source]

Called at the end of an epoch.

Subclasses should override for any actions to run. This function should only be called during TRAIN mode.

Parameters
  • epoch – Integer, index of epoch.

  • logs – Dict, metric results for this training epoch, and for the validation epoch if validation is performed. Validation result keys are prefixed with val_.