我正在努力在以下函数的每次迭代中获得相同的数据分割?
def data(filename):
X_train = data('train-images.gz')
Y_train = data('train-labels.gz')
X_test = data('t10k-images.gz')
Y_test = data('t10k-labels.gz')
X_train, X_devel = X_train[:, :-devel_size], X_train[:, -devel_size:]
Y_train, Y_devel = Y_train[:-devel_size], Y_train[-devel_size:]
return X_train, Y_train, X_devel, Y_devel, X_test, Y_test
当我调用它时,如何为上述功能提供相同的数据来训练和验证?
原因是,我想用几种优化技术重新运行该功能并比较准确性。
设置随机种子。
tf.random.set_seed(1)
np.random.seed(1)