def elmo_export(self, epoch: Optional[int] = None) -> None:
"""
Dump the trained weights from a model to a HDF5 file and export a TF-Hub module.
"""
if hasattr(self, 'sess'):
self.sess.close()
path = self.save_path
if epoch:
from_path = path.parent / self.epoch_save_path / str(epoch) / path.parts[-1]
weights_to_path = path.parent / self.dumps_save_path / f'weights_epoch_n_{epoch}.hdf5'
tf_hub_to_path = path.parent / self.tf_hub_save_path / f'tf_hub_model_epoch_n_{epoch}'
from_path.resolve()
weights_to_path.resolve()
tf_hub_to_path.resolve()
log.info(f'[exporting {epoch} epoch]')
else:
from_path = path
weights_to_path = path.parent / self.dumps_save_path / 'weights.hdf5'
tf_hub_to_path = path.parent / self.tf_hub_save_path / 'tf_hub_model'
weights_to_path.parent.mkdir(parents=True, exist_ok=True)
tf_hub_to_path.parent.mkdir(parents=True, exist_ok=True)
# Check presence of the model files
if tf.train.checkpoint_exists(str(from_path)):
dump_weights(from_path.parent, weights_to_path, self.permanent_options)
options = copy.deepcopy(self.permanent_options)
options['char_cnn']['n_characters'] = 262
export2hub(weights_to_path, tf_hub_to_path, options)
def elmo_export(self, epoch: Optional[int] = None) -> None:
"""
Dump the trained weights from a model to a HDF5 file and export a TF-Hub module.
"""
if hasattr(self, 'sess'):
self.sess.close()
path = self.save_path
if epoch:
from_path = path.parent / self.epoch_save_path / str(
epoch) / path.parts[-1]
weights_to_path = path.parent / self.dumps_save_path / f'weights_epoch_n_{epoch}.hdf5'
tf_hub_to_path = path.parent / self.tf_hub_save_path / f'tf_hub_model_epoch_n_{epoch}'
from_path.resolve()
weights_to_path.resolve()
tf_hub_to_path.resolve()
log.info(f'[exporting {epoch} epoch]')
else:
from_path = path
weights_to_path = path.parent / self.dumps_save_path / 'weights.hdf5'
tf_hub_to_path = path.parent / self.tf_hub_save_path / 'tf_hub_model'
weights_to_path.parent.mkdir(parents=True, exist_ok=True)
tf_hub_to_path.parent.mkdir(parents=True, exist_ok=True)
# Check presence of the model files
if tf.train.checkpoint_exists(str(from_path)):
dump_weights(from_path.parent, weights_to_path,
self.permanent_options)
options = copy.deepcopy(self.permanent_options)
options['char_cnn']['n_characters'] = 262
export2hub(weights_to_path, tf_hub_to_path, options)