ValueError: Data cardinality is ambiguous: x sizes: 60000 y sizes: 10000 Make sure all arrays contai-CodePudding

I'm trying to train a model using MNIST dataset from keras

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense,Flatten

mnist = keras.datasets.mnist

(x_train,x_test),(y_train,y_test) = mnist.load_data()
import numpy as np
import matplotlib.pyplot as plt 

print(np.min(x_train),np.max(x_train))

x_train = x_train/255.0
x_test = x_test/255.0
print(np.min(x_train),np.max(x_train))
print(x_test.min(),x_test.max())

model = Sequential()
model.add(Flatten(input_shape=(28,28)))
model.add(Dense(128,activation='relu'))
model.add(Dense(10,activation='softmax'))
model.summary()

model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',metrics='accuracy')
model.fit(x_train,y_train,epochs=10)

When I train the model my console throws this error:

ValueError: Data cardinality is ambiguous:
  x sizes: 60000
  y sizes: 10000
Make sure all arrays contain the same number of samples.

Full error:

ValueError                                Traceback (most recent call last)
c:\Users\USER\Documents\DSProject\text_Recog_tf.ipynb Cell 7' in <cell line: 2>()
      1 model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',metrics='accuracy')
----> 2 model.fit(x_train,y_train,epochs=10)

File c:\Users\USER\AppData\Local\Programs\Python\Python310\lib\site-packages\keras\utils\traceback_utils.py:67, in filter_traceback.<locals>.error_handler(*args, **kwargs)
     65 except Exception as e:  # pylint: disable=broad-except
     66   filtered_tb = _process_traceback_frames(e.__traceback__)
---> 67   raise e.with_traceback(filtered_tb) from None
     68 finally:
     69   del filtered_tb

File c:\Users\USER\AppData\Local\Programs\Python\Python310\lib\site-packages\keras\engine\data_adapter.py:1655, in _check_data_cardinality(data)
   1651   msg  = "  {} sizes: {}\n".format(
   1652       label, ", ".join(str(i.shape[0])
   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)

ValueError: Data cardinality is ambiguous:
  x sizes: 60000
  y sizes: 10000
Make sure all arrays contain the same number of samples.

I'm not sure nor I understand what the error was because I'm just a novice following a tutorial video on youtube

CodePudding user response：

use this code to load the dataset

(x_train,y_train),(x_test,y_test) = mnist.load_data()
print(len(x_train), len(y_train))

the resultant print is

60000 60000

So now you have 60000 images and 60000 labels