Deeplearning による画像認識を行いたい

Question

現在、mnistのデータを使用し、DeepLearningの勉強をしています。自分で取り込んだ画像に記された数字が何かを当てるプログラムを作製しようと考え、以下のコードを作成しました。

from sklearn.datasets import fetch_mldata
 
mnist = fetch_mldata('MNIST original', data_home=".")
X = mnist.data / 255 
y = mnist.target
import matplotlib.pyplot as plt

 
plt.imshow(X[0].reshape(28, 28), cmap='gray')
print("This is {:.0f}".format(y[0]))
import torch
from torch.utils.data import TensorDataset, DataLoader
 
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(
    X, y, test_size=1/7, random_state=0)
 
X_train = torch.Tensor(X_train)
X_test = torch.Tensor(X_test)
y_train = torch.LongTensor(y_train)
y_test = torch.LongTensor(y_test)
 
ds_train = TensorDataset(X_train, y_train)
ds_test = TensorDataset(X_test, y_test)
 
loader_train = DataLoader(ds_train, batch_size=64, shuffle=True)
loader_test = DataLoader(ds_test, batch_size=64, shuffle=False)

from torch import nn
 
model = nn.Sequential()
model.add_module('fc1', nn.Linear(28*28, 100))
model.add_module('relu1', nn.ReLU())
model.add_module('fc2', nn.Linear(100, 100))
model.add_module('relu2', nn.ReLU())
model.add_module('fc3', nn.Linear(100, 10))
 
print(model)
from torch import optim
 
loss_fn = nn.CrossEntropyLoss()  

optimizer = optim.Adam(model.parameters(), lr=0.01)

from torch.autograd import Variable
 
def train(epoch):
    model.train()  
    for data, target in loader_train:
        data, target = Variable(data), Variable(target)  
        optimizer.zero_grad() 
        output = model(data)  
        loss = loss_fn(output, target) 
        loss.backward() 
        optimizer.step()  
    print("epoch{}:end\n".format(epoch))

def test():
    model.eval() 
    correct = 0
    for data, target in loader_test:
        data, target = Variable(data), Variable(target)  
        output = model(data)          
        pred = output.data.max(1, keepdim=True)[1]  
        correct += pred.eq(target.data.view_as(pred)).sum() 
    data_num = len(loader_test.dataset)  
    print('\n answer: {}/{} ({:.0f}%)\n'.format(correct,data_num, 100. * correct / data_num))
    
for epoch in range(3):
    train(epoch)
 
test()
import tensorflow as tf
img_r = tf.read_file("8.png")
read_image = tf.image.decode_image(img_r, channels=3)
data = Variable(read_image)
output = model(data)  
pred = output.data.max(0, keepdim=True)[1]  
print("I think {}".format(pred))
コード

すると、以下のエラーが表示されてしまいました。
variable data has o be a tensor, but got Tensor

初心者である私にはtensorとTensorの違いが分かりませんでした。エラー内容について教えていただきたいです。