import tensorflow as tf

        return out
    
    def valid_inference(self,images):
        images=tf.cast(images,tf.float32)/255.0
        l1 = tf.matmul(images, self.w1)+self.b1
        l1=tf.nn.relu(l1)
        out = tf.matmul(l1, self.w2)+self.b2
        return out
    
    def softmax_loss(self,predicts,labels):
        predicts=tf.nn.softmax(predicts)
        labels=tf.one_hot(labels,classnum)
