Tensorflow模型培训:缺少1个必需的位置参数:“self”

我正试图按照以下示例练习神经网络分类器: Train your first neural network: basic classification ,这是我的代码,直到模型培训为止:

import tensorflow as tf
from tensorflow import keras

import numpy as np
from matplotlib.pyplot import show
import matplotlib.pyplot as plt

from matplotlib.pyplot import figure
from matplotlib.pyplot import imshow
from matplotlib.pyplot import colorbar
from matplotlib.pyplot import axis
from matplotlib.pyplot import plot
from matplotlib.pyplot import show

print(tf.__version__)

fashion_mnist = keras.datasets.fashion_mnist

(train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()


#figure(); imshow(train_images[1]); colorbar(); axis('auto') 

class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat', 
               'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']

N1, N2, N3 = test_images.shape

train_images = train_images / 255.0
test_images  = test_images / 255.0

model = keras.Sequential
([
    keras.layers.Flatten(input_shape=(N2, N3)),
    keras.layers.Dense(128, activation=tf.nn.relu),
    keras.layers.Dense(10, activation=tf.nn.softmax)
])


model.compile(optimizer='adam', 
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])


model.fit(train_images, train_labels, epochs=5)

它返回的错误是

TypeError: _method_wrapper() missing 1 required positional argument: 'self'

发生在

model.compile(optimizer='adam', 
                  loss='sparse_categorical_crossentropy',
                  metrics=['accuracy'])

我在谷歌上搜索了一下,似乎

m = model()
m.compile()

可以避免“自我”错误。然而,它得到了新的错误,培训仍然没有发生。

Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz
32768/29515 [=================================] - 0s 0us/step
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz
26427392/26421880 [==============================] - 1s 0us/step
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz
8192/5148 [===============================================] - 0s 0us/step
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz
4423680/4422102 [==============================] - 0s 0us/step