解决TypeError: __init__() takes from 1 to 3 positional arguments but 6 were given_深度学习

2022-01-12 22:20:24.272950: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
Traceback (most recent call last):
  File "E:/Code/PyCharm/深度学习/图像分类/NIN/train.py", line 27, in <module>
    history = model.NIN(10)
  File "E:\Code\PyCharm\深度学习\图像分类\NIN\model.py", line 26, in __init__
    kernel_size=1)
  File "D:\Anaconda\lib\site-packages\tensorflow\python\training\tracking\base.py", line 530, in _method_wrapper
    result = method(self, *args, **kwargs)
TypeError: __init__() takes from 1 to 3 positional arguments but 6 were given

问题原因：
我在使用​​​Sequential​​​模块搭建网络时，中间掺杂不同的层，但是我们有用列表进行封装，所以导致参数不对应
解决方案：
使用列表进行封装使之成为一个参数

self.mlpconv1 = Sequential([
            Conv2D(filters=6,
                   kernel_size=1),
            ReLU(),
            Conv2D(filters=6,
                   kernel_size=1),
            ReLU(),
            Conv2D(filters=6,
                   kernel_size=1)]
        )