利用tensorflow识别minist中的0和1，遇到如下报错如何解决？

Question

报错：ValueError: Shape mismatch: The shape of labels (received (1,)) should equal the shape of logits except for the last dimension (received (28, 2)).
代码如下：

import tensorflow as tf
from matplotlib import pyplot as plt
from tensorflow import data

mnist = tf.keras.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
x_train01=[]
y_train01=[]
x_test01=[]
y_test01=[]
for (i,j) in zip(x_train, y_train):
    if(j==0 or j==1):
        x_train01.append(i)
        y_train01.append(j)
print(y_train01)
for (i, j) in zip(x_test, y_test):
    if (j == 0 or j == 1):
        x_test01.append(i)
        y_test01.append(j)


train_dataset = data.Dataset.from_tensor_slices((x_train01, y_train01))
test_dataset = data.Dataset.from_tensor_slices((x_test01, y_test01))

print(test_dataset)
#配置网络
model = tf.keras.models.Sequential([
    tf.keras.layers.Flatten(),
    tf.keras.layers.Dense(28, activation='relu'),
    tf.keras.layers.Dense(2, activation='softmax')
])
#配置训练参数
model.compile(optimizer='adam',
              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False),
              metrics=['accuracy'])

#训练模型
model.fit(train_dataset, batch_size=32, epochs=5, validation_data=test_dataset, validation_freq=1)
model.summary()

Answer 1

除了最后一个维度(received (28，2))，标签的形状(received (1，))应该等于logits的形状。