def _save_as_numpy(predictions, output_directory, saved_keys):
predictions = predictions[[c for c in predictions.columns if c not in saved_keys]]
npy_filename = os.path.join(output_directory, "{}.npy")
numpy_predictions = to_numpy_dataset(predictions)
for k, v in numpy_predictions.items():
if k not in saved_keys:
k = k.replace("<", "[").replace(">", "]") # Replace <UNK> and <PAD>
np.save(npy_filename.format(k), v)
saved_keys.add(k)
def _save_as_numpy(predictions, output_directory, saved_keys):
predictions = predictions[[
c for c in predictions.columns if c not in saved_keys
]]
npy_filename = os.path.join(output_directory, '{}.npy')
numpy_predictions = to_numpy_dataset(predictions)
for k, v in numpy_predictions.items():
if k not in saved_keys:
np.save(npy_filename.format(k), v)
saved_keys.add(k)
def __init__(self, dataset, features, data_hdf5_fp):
self.features = features
self.data_hdf5_fp = data_hdf5_fp
self.size = len(dataset)
self.dataset = to_numpy_dataset(dataset)