def load_weight(self, base_directory: str, filename: str,
model: keras.models.Model) -> keras.models.Model:
if filename == '':
model.load_weights(
os.path.join(base_directory, self.weight_filename))
else:
model.load_weights(filename)
return model
def load_checkpoint(self, fs: FSBase, model: keras.models.Model) -> None:
with tempfile.NamedTemporaryFile(suffix=".h5") as tf:
local_fs = FileSystem()
with fs.open("model.h5", "rb") as fin:
local_fs.writefile(tf.name, fin)
model.load_weights(tf.name)