Save/Load models using HDF5 files

save_model_hdf5(object, filepath, overwrite = TRUE,
  include_optimizer = TRUE)

load_model_hdf5(filepath, custom_objects = NULL, compile = TRUE)

Arguments

object

Model object to save

filepath

File path

overwrite

Overwrite existing file if necessary

include_optimizer

If TRUE, save optimizer's state.

custom_objects

Mapping class names (or function names) of custom (non-Keras) objects to class/functions

compile

Whether to compile the model after loading.

Details

The following components of the model are saved:

  • The model architecture, allowing to re-instantiate the model.

  • The model weights.

  • The state of the optimizer, allowing to resume training exactly where you left off. This allows you to save the entirety of the state of a model in a single file.

Saved models can be reinstantiated via load_model(). The model returned by load_model() is a compiled model ready to be used (unless the saved model was never compiled in the first place or compile = FALSE is specified.

See also

Other model persistence: get_weights, model_to_json, model_to_yaml, save_model_weights_hdf5