我在做一个关于使用mnist的colabs的小项目。当我得到这个令人烦恼的错误时，我决定改变数据集。不久前我也发了一个关于这个的帖子。但是这个问题没有解决。告诉我我哪里出错了。
我的代码：

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import tensorflow as tf
from tensorflow import keras

data = keras.datasets.cifar10

df = data.load_data()

(X_train, y_train),(X_test, y_test) = df

X_train_flat = X_train.reshape(-1,32*32)
X_test_flat = X_test.reshape(-1, 32*32)

from tensorflow.keras import Sequential
from tensorflow.keras.layers import Dense

model = Sequential([
                    #first hidden layer
                    Dense(units=10,
                          input_shape = (1024,),
                          activation='sigmoid'),
                    #second hidden layer
                    #Dense(units=10,
                     #     input_shape = (784,),
                      #    activation='sigmoid')
])
model.compile(
    optimizer='adam',
    loss='sparse_categorical_crossentropy',
    metrics=['accuracy']
)

model.fit(X_test_flat, y_train, epochs=15)#im getting the error on this line

y_pred = model.predict(X_test_flat)

model.evaluate(X_test_flat, y_test)

错误是：

ValueError                                Traceback (most recent call last)
<ipython-input-13-5508f48e747b> in <module>
----> 1 model.fit(X_test_flat, y_train, epochs=15)

1 frames
/usr/local/lib/python3.7/dist-packages/keras/engine/data_adapter.py in _check_data_cardinality(data)
   1653                            for i in tf.nest.flatten(single_data)))
   1654     msg += "Make sure all arrays contain the same number of samples."
-> 1655     raise ValueError(msg)
   1656 
   1657 

ValueError: Data cardinality is ambiguous:
  x sizes: 30000
  y sizes: 50000
Make sure all arrays contain the same number of samples.

为任何格式问题道歉。我不在我的pc rn上