def load_vocabs(transform, save_dir, filename='vocabs.json'):
vocabs = SerializableDict()
vocabs.load_json(os.path.join(save_dir, filename))
for key, value in vocabs.items():
vocab = Vocab()
vocab.copy_from(value)
setattr(transform, key, vocab)
def __init__(self, transform: Transform) -> None:
super().__init__()
self.model: Optional[tf.keras.Model] = None
self.config = SerializableDict()
self.transform = transform
# share config with transform for convenience, so we don't need to pass args around
if self.transform.config:
for k, v in self.transform.config.items():
self.config[k] = v
self.transform.config = self.config
def __init__(self, config: SerializableDict = None, map_x=True, map_y=True, **kwargs) -> None:
super().__init__()
self.map_y = map_y
self.map_x = map_x
if kwargs:
if not config:
config = SerializableDict()
for k, v in kwargs.items():
config[k] = v
self.config = config
self.output_types = None
self.output_shapes = None
self.padding_values = None
def save_vocabs(self, save_dir, filename='vocabs.json'):
vocabs = SerializableDict()
for key, value in vars(self.transform).items():
if isinstance(value, Vocab):
vocabs[key] = value.to_dict()
vocabs.save_json(os.path.join(save_dir, filename))