def list_shuffle(*data):
idxs = np_rng.permutation(np.arange(len(data[0])))
if len(data) == 1:
return [data[0][idx] for idx in idxs]
else:
return [[d[idx] for idx in idxs] for d in data]
def shuffle_list(*data):
idxs = np_rng.permutation(np.arange(len(data[0])))
if len(data) == 1:
return [data[0][idx] for idx in idxs]
else:
return [[d[idx] for idx in idxs] for d in data]
def tensor_shuffle(data1, data2):
print(data1)
idxs = np_rng.permutation(np.arange(data1.shape[0]))
return data1[idxs], data2[idxs]