def cli():
for experiments_file in (
"larq_zoo.training.basic_experiments",
"larq_zoo.training.multi_stage_experiments",
):
importlib.import_module(experiments_file)
from zookeeper import cli
cli()
train_data,
epochs=hparams.epochs,
steps_per_epoch=dataset.train_examples // hparams.batch_size,
validation_data=validation_data,
validation_steps=dataset.validation_examples // hparams.batch_size,
verbose=2 if tensorboard else 1,
initial_epoch=initial_epoch,
callbacks=callbacks,
)
model_name = build_model.__name__
model.save_weights(path.join(output_dir, f"{model_name}_weights.h5"))
# Save weights without top
notop_model = build_model(hparams,
**dataset.preprocessing.kwargs,
include_top=False)
notop_model.set_weights(
model.get_weights()[:len(notop_model.get_weights())])
notop_model.save_weights(
path.join(output_dir, f"{model_name}_weights_notop.h5"))
if __name__ == "__main__":
import importlib
# Running it without the CLI requires us to first import larq_zoo
# in order to register the models and datasets
importlib.import_module("larq_zoo")
cli()