Pytorch使用shuffle打乱数据的操作

 def Shuffle(self, x, y,random=None, int=int):
         if random is None:
            random = self.random
                 for i in range(len(x)):
            j = int(random() * (i + 1))
            if j<=len(x)-1:
                x[i],x[j]=x[j],x[i]
                y[i],y[j]=y[j],y[i]
          retrun x,y

 def Shuffle(self, x, y,random=None, int=int):
        """x, random=random.random -> shuffle list x in place; return None.
        Optional arg random is a 0-argument function returning a random
        float in [0.0, 1.0); by default, the standard random.random.
        """
        if random is None:
            random = self.random #random=random.random
        #转成numpy
        if torch.is_tensor(x)==True:
            if self.use_cuda==True:
               x=x.cpu().numpy()
            else:
               x=x.numpy()
        if torch.is_tensor(y) == True:
            if self.use_cuda==True:
               y=y.cpu().numpy()
            else:
               y=y.numpy()
        #开始随机置换
        for i in range(len(x)):
            j = int(random() * (i + 1))
            if j<=len(x)-1:#交换
                x[i],x[j]=x[j],x[i]
                y[i],y[j]=y[j],y[i]
        #转回tensor
        if self.use_cuda == True:
            x=torch.from_numpy(x).cuda()
            y=torch.from_numpy(y).cuda()
        else:
            x = torch.from_numpy(x)
            y = torch.from_numpy(y)
        return x,y

image_list=[]           # list of images
label_list=[]           # list of labels
 
temp = np.array([image_list, label_list])
temp = temp.transpose()
np.random.shuffle(temp)
 
images = temp[:, 0]     # array of images   (N,)
labels = temp[:, 1]

image_list=[]           # list of images
label_list=[]           # list of labels
 
##如果image_list存的是读取的特征数据，而不是图片路径，不要注释后面两句（list无法索引内部list）
#[list indices must be integers or slices, not list]
#image_list = np.array(image_list)
#label_list = np.array(label_list)
 
index = [i for i in range(len(image_list))]
np.random.shuffle(index)
images = image_list[index]
labels = label_list[index]