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Difference between steps_per_epoch and epochs in model.fit_generator

See original GitHub issue

I have doubt about the parameter steps_per_epoch and epochs in model.fit_generator.

I found that below two functions work the same way. model.fit_generator(generate_arrays_from_file, steps_per_epoch=10, epochs=1) model.fit_generator(generate_arrays_from_file, steps_per_epoch=1, epochs=10)

Am I right? Or I can do something between epochs?

Issue Analytics

State:
Created 6 years ago
Reactions:1
Comments:5 (2 by maintainers)

Top GitHub Comments

5reactions

samre12commented, Aug 13, 2017

model.fit_generator requires the input dataset generator to run infinitely. steps_per_epoch is used to generate the entire dataset once by calling the generator steps_per_epoch times where as epochs gives the number of times the model is trained over the entire dataset. As @ISosnovik pointed out, callbacks can be used to perform certain operations such as Tensorboard Logging (specific to Tensorflow backend), model checkpointing etc. at the end of each epoch.

1reaction

ISosnovikcommented, Aug 6, 2017

You can use callbacks. In this case, some operations would be performed when the epoch is started/ended.