This features allows to inspect the running metrics over generations from tensorboard directly without having to call plotting functions
Describe the solution you'd expect
Create a TensorBoard callback in sklearn_genetic.callbacks.loggers, it must let you select the log dir and internally use tf.summary.scalar(.., step=gen) to log the record from the algorithms logbook
This features allows to inspect the running metrics over generations from tensorboard directly without having to call plotting functions
Describe the solution you'd expect Create a TensorBoard callback in sklearn_genetic.callbacks.loggers, it must let you select the log dir and internally use tf.summary.scalar(.., step=gen) to log the record from the algorithms logbook
Additional context Documentation: https://www.tensorflow.org/api_docs/python/tf/summary/scalar