Use MNIST in tensorflow 2_ 784 data set for handwritten digit recognition

import tensorflow._api.v2.compat.v1 as tf
tf.disable_v2_behavior
tf.compat.v1.disable_eager_execution()
import numpy as np
# Statement to use TensorFlow1 edition 
 
from scipy.io import  loadmat
mnist = loadmat('G:/pythonProject/MachineLearning/2 classification /mnist-original.mat')# hold mnist_784 Data sets are downloaded separately , And then use loadmat Read 

X = mnist['data'].T# This must be transposed , Because the ranks are opposite ！！！！！
y = mnist['label'].T.flatten()# Expand the data 
y= y.astype(np.uint8)# Change format to uint8

# And then use pandas Label y Heat code , Finally, convert the data into ndarray Format 
import pandas as pd
y_pd =  pd.Series(y)
y_oneHot = pd.get_dummies(y_pd)
y = np.array(y_oneHot.values)
# Okay X,y Now it can be used for training