diff --git a/sdk/attack_pp.py b/sdk/attack_pp.py
index 74a5cb8..011ff9b 100644
--- a/sdk/attack_pp.py
+++ b/sdk/attack_pp.py
@@ -62,6 +62,27 @@ def process_img(img_path="",image_shape=[3,224,224]):
     
     return img
 
+def tensor2img(tensor):
+    
+    mean = [0.485, 0.456, 0.406] 
+    std = [0.229, 0.224, 0.225] 
+    
+    img_mean = np.array(mean).reshape((3, 1, 1))
+    img_std = np.array(std).reshape((3, 1, 1))
+    
+    img=tensor.copy()
+      
+    img *= img_std
+    img += img_mean
+    
+    img = np.round(img*255) 
+    img = np.clip(img,0,255)
+
+    img=img[0].astype(np.uint8)
+        
+    img = img.transpose(1, 2, 0)
+    
+    return img
 
 """
 Explaining and Harnessing Adversarial Examples, I. Goodfellow et al., ICLR 2015
diff --git a/sdk_demo.ipynb b/sdk_demo.ipynb
index 6b0a4fc..886f259 100644
--- a/sdk_demo.ipynb
+++ b/sdk_demo.ipynb
@@ -46,45 +46,6 @@
     "from sdk.attack_pp import *\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'\\nuse_gpu=False\\n\\nx = fluid.layers.data(name=\"x\", shape=[1] ,dtype=\\'int32\\')\\nx.stop_gradient=False\\ny = x*3\\n\\ng = fluid.backward.gradients(targets=y, inputs=[x])[0]\\n\\nplace = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace()\\nexe = fluid.Executor(place)\\nexe.run(fluid.default_startup_program())\\n\\nresult = exe.run(fluid.default_main_program(),\\n                 fetch_list=[y.name],\\n                 feed={ \\'x\\':np.array([1]).astype(\\'int32\\') })\\n#result = result[0][0]\\n\\nprint(result)\\n'"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "\"\"\"\n",
-    "use_gpu=False\n",
-    "\n",
-    "x = fluid.layers.data(name=\"x\", shape=[1] ,dtype='int32')\n",
-    "x.stop_gradient=False\n",
-    "y = x*3\n",
-    "\n",
-    "g = fluid.backward.gradients(targets=y, inputs=[x])[0]\n",
-    "\n",
-    "place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace()\n",
-    "exe = fluid.Executor(place)\n",
-    "exe.run(fluid.default_startup_program())\n",
-    "\n",
-    "result = exe.run(fluid.default_main_program(),\n",
-    "                 fetch_list=[y.name],\n",
-    "                 feed={ 'x':np.array([1]).astype('int32') })\n",
-    "#result = result[0][0]\n",
-    "\n",
-    "print(result)\n",
-    "\"\"\""
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -94,15 +55,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
     "#http://www.paddlepaddle.org.cn/documentation/docs/zh/1.5/user_guides/howto/prepare_data/index_cn.html\n",
     "\n",
-    "#fluid.default_startup_program().random_seed = 1\n",
-    "#fluid.default_main_program().random_seed = 1\n",
-    "\n",
     "class_dim=1000\n",
     "image_shape=[3,224,224]\n",
     "model_name=\"resnet50\"\n",
@@ -112,6 +70,7 @@
     "\n",
     "adv_program=fluid.Program()\n",
     "\n",
+    "#完成初始化\n",
     "with fluid.program_guard(adv_program):\n",
     "    input_layer = fluid.layers.data(name='image', shape=image_shape, dtype='float32')\n",
     "    #设置为可以计算梯度\n",
@@ -133,6 +92,7 @@
     "#创建测试用评估模式\n",
     "eval_program = adv_program.clone(for_test=True)\n",
     "\n",
+    "#定义梯度\n",
     "with fluid.program_guard(adv_program):\n",
     "    label = fluid.layers.data(name=\"label\", shape=[1] ,dtype='int64')\n",
     "    loss = fluid.layers.cross_entropy(input=out, label=label)\n",
@@ -149,7 +109,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -178,7 +138,10 @@
     "\n",
     "pred_label = np.argsort(result)[::-1][:TOPK]\n",
     "print(\"Test-score: {0}, class {1}\".format(result[pred_label], pred_label))\n",
-    "sys.stdout.flush()"
+    "sys.stdout.flush()\n",
+    "\n",
+    "\n",
+    "o_img=tensor2img(img)\n"
    ]
   },
   {
@@ -190,7 +153,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -209,7 +172,8 @@
     "#init_prog(fluid.default_main_program())\n",
     "\n",
     "#生成对抗样本\n",
-    "adv=FGSM(adv_program=adv_program,eval_program=eval_program,gradients=gradients,o=img,input_layer=input_layer,output_layer=out,step_size=16.0/256.0,isTarget=False,target_label=0)\n",
+    "adv=FGSM(adv_program=adv_program,eval_program=eval_program,gradients=gradients,o=img,\n",
+    "         input_layer=input_layer,output_layer=out,step_size=16.0/256.0,isTarget=False,target_label=0)\n",
     "\n",
     "    \n",
     "result = exe.run(eval_program,\n",
@@ -232,7 +196,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {