我想用keras创建一个模型，但是我在构建模型时遇到了一些问题。我试着把它放进去 model.fit , np.array 对于x_列和y_列，但返回相同的错误。
这是密码

X_train, y_train, X_test, y_test = train_test_split(X, y, test_size=0.2)

model = keras.Sequential([

keras.layers.Flatten(input_shape=(3,)),
keras.layers.Dense(128, activation='relu'),
keras.layers.Dense(64, activation='relu'),

keras.layers.Dense(3, activation='softmax')

])

# compile model

optimiser = keras.optimizers.Adam(learning_rate=0.0001)
model.compile(optimizer=optimiser,
                  loss='sparse_categorical_crossentropy',
                  metrics=['accuracy'])

model.summary()

# train model

model.fit(X_train, y_train, validation_data=(X_test, y_test), batch_size=32, epochs=100)

错误

ValueError: Data cardinality is ambiguous:
  x sizes: 4928
  y sizes: 1233
Make sure all arrays contain the same number of samples.