ValueError: Can not squeeze dim[1], expected a dimension of 1, got 3 for 'sparse_softmax_cross_entropy_loss

Question

I tried to replace the training and validation data with local images. But when running the training code, it came up with the error :

ValueError: Ca

Answer 1

i write the code that change [1,0,0], [0,1,0], [0,0,1] to 0,1,2.

import numpy as np
import tensorflow as tf

def change_to_right(wrong_labels):
    right_labels=[]
    for x in wrong_labels:
        for i in range(0,len(wrong_labels[0])):
            if x[i]==1:
                right_labels.append(i)
    return right_labels

wrong_labels =np.array([[0,0,1,0], [0,0,1,0], [1,0,0,0],[0,1,0,0]])
right_labels =tf.convert_to_tensor(np.array(change_to_right(wrong_labels)))