diff --git a/tutorials/notebook/nlp_application.ipynb b/tutorials/notebook/nlp_application.ipynb
index 7d5926b9d0dbd65ce27da550e7760e72142ba0b5..8920dfef4cd45971f0711cba8d898f1065df77ec 100644
--- a/tutorials/notebook/nlp_application.ipynb
+++ b/tutorials/notebook/nlp_application.ipynb
@@ -46,7 +46,9 @@
     "3. 定义网络。\n",
     "4. 定义优化器和损失函数。\n",
     "5. 使用网络训练数据，生成模型。\n",
-    "6. 得到模型之后，使用验证数据集，查看模型精度情况。"
+    "6. 得到模型之后，使用验证数据集，查看模型精度情况。\n",
+    "\n",
+    "> 本次体验流程支持CPU或GPU环境，Ascend环境暂不支持。"
    ]
   },
   {
@@ -854,4161 +856,8 @@
       "epoch: 1 step: 8, loss is 0.6819\n",
       "epoch: 1 step: 9, loss is 0.7372\n",
       "epoch: 1 step: 10, loss is 0.6948\n",
-      "epoch: 1 step: 11, loss is 0.6961\n",
-      "epoch: 1 step: 12, loss is 0.6975\n",
-      "epoch: 1 step: 13, loss is 0.6931\n",
-      "epoch: 1 step: 14, loss is 0.6903\n",
-      "epoch: 1 step: 15, loss is 0.6720\n",
-      "epoch: 1 step: 16, loss is 0.7079\n",
-      "epoch: 1 step: 17, loss is 0.7125\n",
-      "epoch: 1 step: 18, loss is 0.7477\n",
-      "epoch: 1 step: 19, loss is 0.6924\n",
-      "epoch: 1 step: 20, loss is 0.7085\n",
-      "epoch: 1 step: 21, loss is 0.6958\n",
-      "epoch: 1 step: 22, loss is 0.6918\n",
-      "epoch: 1 step: 23, loss is 0.6985\n",
-      "epoch: 1 step: 24, loss is 0.6919\n",
-      "epoch: 1 step: 25, loss is 0.6858\n",
-      "epoch: 1 step: 26, loss is 0.6796\n",
-      "epoch: 1 step: 27, loss is 0.7113\n",
-      "epoch: 1 step: 28, loss is 0.7065\n",
-      "epoch: 1 step: 29, loss is 0.6910\n",
-      "epoch: 1 step: 30, loss is 0.6896\n",
-      "epoch: 1 step: 31, loss is 0.6968\n",
-      "epoch: 1 step: 32, loss is 0.6906\n",
-      "epoch: 1 step: 33, loss is 0.6932\n",
-      "epoch: 1 step: 34, loss is 0.6872\n",
-      "epoch: 1 step: 35, loss is 0.6887\n",
-      "epoch: 1 step: 36, loss is 0.6789\n",
-      "epoch: 1 step: 37, loss is 0.6729\n",
-      "epoch: 1 step: 38, loss is 0.7344\n",
-      "epoch: 1 step: 39, loss is 0.6946\n",
-      "epoch: 1 step: 40, loss is 0.6977\n",
-      "epoch: 1 step: 41, loss is 0.7134\n",
-      "epoch: 1 step: 42, loss is 0.6807\n",
-      "epoch: 1 step: 43, loss is 0.6798\n",
-      "epoch: 1 step: 44, loss is 0.7065\n",
-      "epoch: 1 step: 45, loss is 0.6930\n",
-      "epoch: 1 step: 46, loss is 0.6925\n",
-      "epoch: 1 step: 47, loss is 0.6824\n",
-      "epoch: 1 step: 48, loss is 0.7224\n",
-      "epoch: 1 step: 49, loss is 0.7051\n",
-      "epoch: 1 step: 50, loss is 0.7195\n",
-      "epoch: 1 step: 51, loss is 0.6927\n",
-      "epoch: 1 step: 52, loss is 0.7097\n",
-      "epoch: 1 step: 53, loss is 0.6849\n",
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-      "epoch: 1 step: 56, loss is 0.6934\n",
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-      "epoch: 1 step: 58, loss is 0.7068\n",
-      "epoch: 1 step: 59, loss is 0.6920\n",
-      "epoch: 1 step: 60, loss is 0.7120\n",
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-      "epoch: 1 step: 64, loss is 0.6958\n",
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-      "epoch: 1 step: 66, loss is 0.6876\n",
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-      "epoch: 1 step: 68, loss is 0.7101\n",
-      "epoch: 1 step: 69, loss is 0.7078\n",
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-      "epoch: 1 step: 88, loss is 0.6821\n",
-      "epoch: 1 step: 89, loss is 0.6899\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "epoch: 1 step: 90, loss is 0.6860\n",
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-     ]
-    },
-    {
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-     "output_type": "stream",
-     "text": [
-      "epoch: 1 step: 179, loss is 0.6838\n",
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-     ]
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-     "text": [
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-     ]
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-     "text": [
-      "epoch: 1 step: 357, loss is 0.6403\n",
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-      "Epoch time: 40590.832, per step time: 104.079, avg loss: 0.668\n",
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-     ]
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-     "text": [
-      "epoch: 2 step: 54, loss is 0.5748\n",
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-     ]
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-     "text": [
-      "epoch: 2 step: 143, loss is 0.5716\n",
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-     ]
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-     "text": [
-      "epoch: 2 step: 232, loss is 0.5745\n",
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-     ]
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-      "Epoch time: 41081.172, per step time: 105.336, avg loss: 0.564\n",
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-     ]
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-      "epoch: 3 step: 18, loss is 0.3993\n",
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-     ]
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-      "epoch: 3 step: 107, loss is 0.4050\n",
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-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 3 step: 196, loss is 0.3696\n",
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-     ]
-    },
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-     "text": [
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-     ]
-    },
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-      "epoch: 3 step: 374, loss is 0.3921\n",
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-      "Epoch time: 41946.990, per step time: 107.556, avg loss: 0.403\n",
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-     ]
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-     ]
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-      "epoch: 4 step: 160, loss is 0.4387\n",
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-     ]
-    },
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-     ]
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-      "epoch: 4 step: 338, loss is 0.4460\n",
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-      "Epoch time: 42451.503, per step time: 108.850, avg loss: 0.368\n",
-      "************************************************************\n",
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-     ]
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-      "epoch: 5 step: 35, loss is 0.3577\n",
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-     ]
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-      "epoch: 5 step: 124, loss is 0.3165\n",
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-     ]
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-     ]
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-      "epoch: 5 step: 302, loss is 0.3439\n",
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-     ]
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-     "text": [
-      "Epoch time: 40547.118, per step time: 103.967, avg loss: 0.346\n",
-      "************************************************************\n",
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-     ]
-    },
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-     "text": [
-      "epoch: 6 step: 88, loss is 0.3815\n",
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-     ]
-    },
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-      "epoch: 6 step: 177, loss is 0.3473\n",
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-     ]
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-      "epoch: 6 step: 266, loss is 0.1851\n",
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-     ]
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-     "text": [
-      "epoch: 6 step: 355, loss is 0.4533\n",
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-      "Epoch time: 41775.770, per step time: 107.117, avg loss: 0.330\n",
-      "************************************************************\n",
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-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 7 step: 52, loss is 0.3062\n",
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-      "epoch: 7 step: 140, loss is 0.1529\n"
-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 7 step: 141, loss is 0.4725\n",
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-      "epoch: 7 step: 229, loss is 0.2926\n"
-     ]
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-      "epoch: 7 step: 230, loss is 0.4031\n",
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-      "epoch: 7 step: 318, loss is 0.3245\n"
-     ]
-    },
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-     "text": [
-      "epoch: 7 step: 319, loss is 0.2874\n",
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-      "Epoch time: 42367.284, per step time: 108.634, avg loss: 0.312\n",
-      "************************************************************\n",
-      "epoch: 8 step: 1, loss is 0.2149\n",
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-      "epoch: 8 step: 15, loss is 0.2004\n"
-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 8 step: 16, loss is 0.2551\n",
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-      "epoch: 8 step: 104, loss is 0.3204\n"
-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 8 step: 105, loss is 0.3339\n",
-      "epoch: 8 step: 106, loss is 0.3085\n",
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-      "epoch: 8 step: 193, loss is 0.3332\n"
-     ]
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-     "text": [
-      "epoch: 8 step: 194, loss is 0.2501\n",
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-      "epoch: 8 step: 282, loss is 0.2485\n"
-     ]
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-     "text": [
-      "epoch: 8 step: 283, loss is 0.3052\n",
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-      "epoch: 8 step: 371, loss is 0.3270\n"
-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 8 step: 372, loss is 0.2237\n",
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-      "Epoch time: 41559.509, per step time: 106.563, avg loss: 0.294\n",
-      "************************************************************\n",
-      "epoch: 9 step: 1, loss is 0.2256\n",
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-      "epoch: 9 step: 68, loss is 0.2170\n"
-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 9 step: 69, loss is 0.4718\n",
-      "epoch: 9 step: 70, loss is 0.4030\n",
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-     ]
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-      "epoch: 9 step: 158, loss is 0.2664\n",
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-      "epoch: 9 step: 246, loss is 0.1876\n"
-     ]
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-      "epoch: 9 step: 247, loss is 0.3666\n",
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-      "epoch: 9 step: 335, loss is 0.2407\n"
-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 9 step: 336, loss is 0.2749\n",
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-      "Epoch time: 41044.824, per step time: 105.243, avg loss: 0.279\n",
-      "************************************************************\n",
-      "epoch: 10 step: 1, loss is 0.2735\n",
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-      "epoch: 10 step: 32, loss is 0.2214\n"
-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "epoch: 10 step: 33, loss is 0.2019\n",
-      "epoch: 10 step: 34, loss is 0.2363\n",
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-      "epoch: 10 step: 85, loss is 0.2267\n",
-      "epoch: 10 step: 86, loss is 0.3805\n",
-      "epoch: 10 step: 87, loss is 0.2122\n",
-      "epoch: 10 step: 88, loss is 0.2837\n",
-      "epoch: 10 step: 89, loss is 0.2378\n",
-      "epoch: 10 step: 90, loss is 0.2685\n",
-      "epoch: 10 step: 91, loss is 0.2153\n",
-      "epoch: 10 step: 92, loss is 0.1842\n",
-      "epoch: 10 step: 93, loss is 0.2125\n",
-      "epoch: 10 step: 94, loss is 0.2021\n",
-      "epoch: 10 step: 95, loss is 0.3926\n",
-      "epoch: 10 step: 96, loss is 0.1395\n",
-      "epoch: 10 step: 97, loss is 0.1523\n",
-      "epoch: 10 step: 98, loss is 0.1938\n",
-      "epoch: 10 step: 99, loss is 0.2635\n",
-      "epoch: 10 step: 100, loss is 0.2527\n",
-      "epoch: 10 step: 101, loss is 0.2829\n",
-      "epoch: 10 step: 102, loss is 0.2359\n",
-      "epoch: 10 step: 103, loss is 0.0937\n",
-      "epoch: 10 step: 104, loss is 0.1952\n",
-      "epoch: 10 step: 105, loss is 0.2002\n",
-      "epoch: 10 step: 106, loss is 0.3605\n",
-      "epoch: 10 step: 107, loss is 0.3041\n",
-      "epoch: 10 step: 108, loss is 0.2202\n",
-      "epoch: 10 step: 109, loss is 0.2284\n",
-      "epoch: 10 step: 110, loss is 0.2802\n",
-      "epoch: 10 step: 111, loss is 0.2795\n",
-      "epoch: 10 step: 112, loss is 0.2365\n",
-      "epoch: 10 step: 113, loss is 0.3807\n",
-      "epoch: 10 step: 114, loss is 0.2560\n",
-      "epoch: 10 step: 115, loss is 0.2673\n",
-      "epoch: 10 step: 116, loss is 0.3012\n",
-      "epoch: 10 step: 117, loss is 0.2159\n",
-      "epoch: 10 step: 118, loss is 0.1535\n",
-      "epoch: 10 step: 119, loss is 0.2864\n",
-      "epoch: 10 step: 120, loss is 0.2596\n",
-      "epoch: 10 step: 121, loss is 0.3524\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "epoch: 10 step: 122, loss is 0.3619\n",
-      "epoch: 10 step: 123, loss is 0.2152\n",
-      "epoch: 10 step: 124, loss is 0.3646\n",
-      "epoch: 10 step: 125, loss is 0.2300\n",
-      "epoch: 10 step: 126, loss is 0.2405\n",
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-      "epoch: 10 step: 128, loss is 0.3845\n",
-      "epoch: 10 step: 129, loss is 0.4600\n",
-      "epoch: 10 step: 130, loss is 0.3505\n",
-      "epoch: 10 step: 131, loss is 0.1911\n",
-      "epoch: 10 step: 132, loss is 0.1612\n",
-      "epoch: 10 step: 133, loss is 0.3517\n",
-      "epoch: 10 step: 134, loss is 0.2793\n",
-      "epoch: 10 step: 135, loss is 0.1697\n",
-      "epoch: 10 step: 136, loss is 0.1566\n",
-      "epoch: 10 step: 137, loss is 0.3282\n",
-      "epoch: 10 step: 138, loss is 0.3097\n",
-      "epoch: 10 step: 139, loss is 0.2631\n",
-      "epoch: 10 step: 140, loss is 0.3907\n",
-      "epoch: 10 step: 141, loss is 0.3358\n",
-      "epoch: 10 step: 142, loss is 0.3061\n",
-      "epoch: 10 step: 143, loss is 0.1727\n",
-      "epoch: 10 step: 144, loss is 0.2522\n",
-      "epoch: 10 step: 145, loss is 0.3008\n",
-      "epoch: 10 step: 146, loss is 0.3309\n",
-      "epoch: 10 step: 147, loss is 0.3308\n",
-      "epoch: 10 step: 148, loss is 0.2165\n",
-      "epoch: 10 step: 149, loss is 0.2901\n",
-      "epoch: 10 step: 150, loss is 0.2647\n",
-      "epoch: 10 step: 151, loss is 0.3280\n",
-      "epoch: 10 step: 152, loss is 0.2017\n",
-      "epoch: 10 step: 153, loss is 0.2675\n",
-      "epoch: 10 step: 154, loss is 0.2361\n",
-      "epoch: 10 step: 155, loss is 0.3119\n",
-      "epoch: 10 step: 156, loss is 0.3522\n",
-      "epoch: 10 step: 157, loss is 0.1649\n",
-      "epoch: 10 step: 158, loss is 0.3038\n",
-      "epoch: 10 step: 159, loss is 0.3336\n",
-      "epoch: 10 step: 160, loss is 0.3087\n",
-      "epoch: 10 step: 161, loss is 0.2617\n",
-      "epoch: 10 step: 162, loss is 0.3109\n",
-      "epoch: 10 step: 163, loss is 0.2865\n",
-      "epoch: 10 step: 164, loss is 0.2566\n",
-      "epoch: 10 step: 165, loss is 0.1423\n",
-      "epoch: 10 step: 166, loss is 0.2079\n",
-      "epoch: 10 step: 167, loss is 0.2017\n",
-      "epoch: 10 step: 168, loss is 0.2564\n",
-      "epoch: 10 step: 169, loss is 0.2955\n",
-      "epoch: 10 step: 170, loss is 0.2940\n",
-      "epoch: 10 step: 171, loss is 0.2015\n",
-      "epoch: 10 step: 172, loss is 0.2100\n",
-      "epoch: 10 step: 173, loss is 0.3030\n",
-      "epoch: 10 step: 174, loss is 0.1818\n",
-      "epoch: 10 step: 175, loss is 0.3993\n",
-      "epoch: 10 step: 176, loss is 0.2567\n",
-      "epoch: 10 step: 177, loss is 0.1747\n",
-      "epoch: 10 step: 178, loss is 0.2136\n",
-      "epoch: 10 step: 179, loss is 0.3743\n",
-      "epoch: 10 step: 180, loss is 0.2902\n",
-      "epoch: 10 step: 181, loss is 0.3440\n",
-      "epoch: 10 step: 182, loss is 0.1998\n",
-      "epoch: 10 step: 183, loss is 0.2522\n",
-      "epoch: 10 step: 184, loss is 0.2341\n",
-      "epoch: 10 step: 185, loss is 0.4920\n",
-      "epoch: 10 step: 186, loss is 0.2786\n",
-      "epoch: 10 step: 187, loss is 0.2460\n",
-      "epoch: 10 step: 188, loss is 0.2580\n",
-      "epoch: 10 step: 189, loss is 0.3025\n",
-      "epoch: 10 step: 190, loss is 0.4090\n",
-      "epoch: 10 step: 191, loss is 0.3260\n",
-      "epoch: 10 step: 192, loss is 0.3987\n",
-      "epoch: 10 step: 193, loss is 0.2152\n",
-      "epoch: 10 step: 194, loss is 0.3381\n",
-      "epoch: 10 step: 195, loss is 0.2607\n",
-      "epoch: 10 step: 196, loss is 0.4350\n",
-      "epoch: 10 step: 197, loss is 0.2947\n",
-      "epoch: 10 step: 198, loss is 0.3505\n",
-      "epoch: 10 step: 199, loss is 0.2185\n",
-      "epoch: 10 step: 200, loss is 0.1370\n",
-      "epoch: 10 step: 201, loss is 0.2361\n",
-      "epoch: 10 step: 202, loss is 0.3012\n",
-      "epoch: 10 step: 203, loss is 0.4109\n",
-      "epoch: 10 step: 204, loss is 0.1969\n",
-      "epoch: 10 step: 205, loss is 0.2397\n",
-      "epoch: 10 step: 206, loss is 0.1650\n",
-      "epoch: 10 step: 207, loss is 0.1021\n",
-      "epoch: 10 step: 208, loss is 0.2504\n",
-      "epoch: 10 step: 209, loss is 0.3086\n",
-      "epoch: 10 step: 210, loss is 0.5832\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "epoch: 10 step: 211, loss is 0.3747\n",
-      "epoch: 10 step: 212, loss is 0.1915\n",
-      "epoch: 10 step: 213, loss is 0.2435\n",
-      "epoch: 10 step: 214, loss is 0.1964\n",
-      "epoch: 10 step: 215, loss is 0.1412\n",
-      "epoch: 10 step: 216, loss is 0.3663\n",
-      "epoch: 10 step: 217, loss is 0.2127\n",
-      "epoch: 10 step: 218, loss is 0.3638\n",
-      "epoch: 10 step: 219, loss is 0.2969\n",
-      "epoch: 10 step: 220, loss is 0.2878\n",
-      "epoch: 10 step: 221, loss is 0.3518\n",
-      "epoch: 10 step: 222, loss is 0.2342\n",
-      "epoch: 10 step: 223, loss is 0.2159\n",
-      "epoch: 10 step: 224, loss is 0.3619\n",
-      "epoch: 10 step: 225, loss is 0.2785\n",
-      "epoch: 10 step: 226, loss is 0.2721\n",
-      "epoch: 10 step: 227, loss is 0.2554\n",
-      "epoch: 10 step: 228, loss is 0.3147\n",
-      "epoch: 10 step: 229, loss is 0.2355\n",
-      "epoch: 10 step: 230, loss is 0.2799\n",
-      "epoch: 10 step: 231, loss is 0.3037\n",
-      "epoch: 10 step: 232, loss is 0.3153\n",
-      "epoch: 10 step: 233, loss is 0.2251\n",
-      "epoch: 10 step: 234, loss is 0.3054\n",
-      "epoch: 10 step: 235, loss is 0.2202\n",
-      "epoch: 10 step: 236, loss is 0.3073\n",
-      "epoch: 10 step: 237, loss is 0.2066\n",
-      "epoch: 10 step: 238, loss is 0.1443\n",
-      "epoch: 10 step: 239, loss is 0.2317\n",
-      "epoch: 10 step: 240, loss is 0.3590\n",
-      "epoch: 10 step: 241, loss is 0.2146\n",
-      "epoch: 10 step: 242, loss is 0.3797\n",
-      "epoch: 10 step: 243, loss is 0.2756\n",
-      "epoch: 10 step: 244, loss is 0.1608\n",
-      "epoch: 10 step: 245, loss is 0.2442\n",
-      "epoch: 10 step: 246, loss is 0.2288\n",
-      "epoch: 10 step: 247, loss is 0.2711\n",
-      "epoch: 10 step: 248, loss is 0.0924\n",
-      "epoch: 10 step: 249, loss is 0.3406\n",
-      "epoch: 10 step: 250, loss is 0.2317\n",
-      "epoch: 10 step: 251, loss is 0.2523\n",
-      "epoch: 10 step: 252, loss is 0.2392\n",
-      "epoch: 10 step: 253, loss is 0.2634\n",
-      "epoch: 10 step: 254, loss is 0.3347\n",
-      "epoch: 10 step: 255, loss is 0.2345\n",
-      "epoch: 10 step: 256, loss is 0.3497\n",
-      "epoch: 10 step: 257, loss is 0.2975\n",
-      "epoch: 10 step: 258, loss is 0.2213\n",
-      "epoch: 10 step: 259, loss is 0.2213\n",
-      "epoch: 10 step: 260, loss is 0.3164\n",
-      "epoch: 10 step: 261, loss is 0.2560\n",
-      "epoch: 10 step: 262, loss is 0.1884\n",
-      "epoch: 10 step: 263, loss is 0.3105\n",
-      "epoch: 10 step: 264, loss is 0.2927\n",
-      "epoch: 10 step: 265, loss is 0.2530\n",
-      "epoch: 10 step: 266, loss is 0.3810\n",
-      "epoch: 10 step: 267, loss is 0.2432\n",
-      "epoch: 10 step: 268, loss is 0.3442\n",
-      "epoch: 10 step: 269, loss is 0.2244\n",
-      "epoch: 10 step: 270, loss is 0.3054\n",
-      "epoch: 10 step: 271, loss is 0.2844\n",
-      "epoch: 10 step: 272, loss is 0.3220\n",
-      "epoch: 10 step: 273, loss is 0.2778\n",
-      "epoch: 10 step: 274, loss is 0.2705\n",
-      "epoch: 10 step: 275, loss is 0.1720\n",
-      "epoch: 10 step: 276, loss is 0.1866\n",
-      "epoch: 10 step: 277, loss is 0.3264\n",
-      "epoch: 10 step: 278, loss is 0.3074\n",
-      "epoch: 10 step: 279, loss is 0.1466\n",
-      "epoch: 10 step: 280, loss is 0.1658\n",
-      "epoch: 10 step: 281, loss is 0.2875\n",
-      "epoch: 10 step: 282, loss is 0.2496\n",
-      "epoch: 10 step: 283, loss is 0.2294\n",
-      "epoch: 10 step: 284, loss is 0.2058\n",
-      "epoch: 10 step: 285, loss is 0.2605\n",
-      "epoch: 10 step: 286, loss is 0.3054\n",
-      "epoch: 10 step: 287, loss is 0.2496\n",
-      "epoch: 10 step: 288, loss is 0.1728\n",
-      "epoch: 10 step: 289, loss is 0.3792\n",
-      "epoch: 10 step: 290, loss is 0.1727\n",
-      "epoch: 10 step: 291, loss is 0.2272\n",
-      "epoch: 10 step: 292, loss is 0.2899\n",
-      "epoch: 10 step: 293, loss is 0.3781\n",
-      "epoch: 10 step: 294, loss is 0.2894\n",
-      "epoch: 10 step: 295, loss is 0.2592\n",
-      "epoch: 10 step: 296, loss is 0.2395\n",
-      "epoch: 10 step: 297, loss is 0.2941\n",
-      "epoch: 10 step: 298, loss is 0.2771\n",
-      "epoch: 10 step: 299, loss is 0.2782\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "epoch: 10 step: 300, loss is 0.2784\n",
-      "epoch: 10 step: 301, loss is 0.2806\n",
-      "epoch: 10 step: 302, loss is 0.2436\n",
-      "epoch: 10 step: 303, loss is 0.3769\n",
-      "epoch: 10 step: 304, loss is 0.3425\n",
-      "epoch: 10 step: 305, loss is 0.2269\n",
-      "epoch: 10 step: 306, loss is 0.4220\n",
-      "epoch: 10 step: 307, loss is 0.2467\n",
-      "epoch: 10 step: 308, loss is 0.1316\n",
-      "epoch: 10 step: 309, loss is 0.1762\n",
-      "epoch: 10 step: 310, loss is 0.3126\n",
-      "epoch: 10 step: 311, loss is 0.3991\n",
-      "epoch: 10 step: 312, loss is 0.1567\n",
-      "epoch: 10 step: 313, loss is 0.2893\n",
-      "epoch: 10 step: 314, loss is 0.1417\n",
-      "epoch: 10 step: 315, loss is 0.2252\n",
-      "epoch: 10 step: 316, loss is 0.2381\n",
-      "epoch: 10 step: 317, loss is 0.2423\n",
-      "epoch: 10 step: 318, loss is 0.2374\n",
-      "epoch: 10 step: 319, loss is 0.2307\n",
-      "epoch: 10 step: 320, loss is 0.0773\n",
-      "epoch: 10 step: 321, loss is 0.2638\n",
-      "epoch: 10 step: 322, loss is 0.2122\n",
-      "epoch: 10 step: 323, loss is 0.3638\n",
-      "epoch: 10 step: 324, loss is 0.2257\n",
-      "epoch: 10 step: 325, loss is 0.1227\n",
-      "epoch: 10 step: 326, loss is 0.2076\n",
-      "epoch: 10 step: 327, loss is 0.3363\n",
-      "epoch: 10 step: 328, loss is 0.2720\n",
-      "epoch: 10 step: 329, loss is 0.3177\n",
-      "epoch: 10 step: 330, loss is 0.3589\n",
-      "epoch: 10 step: 331, loss is 0.2251\n",
-      "epoch: 10 step: 332, loss is 0.2356\n",
-      "epoch: 10 step: 333, loss is 0.2400\n",
-      "epoch: 10 step: 334, loss is 0.2644\n",
-      "epoch: 10 step: 335, loss is 0.1769\n",
-      "epoch: 10 step: 336, loss is 0.2161\n",
-      "epoch: 10 step: 337, loss is 0.2156\n",
-      "epoch: 10 step: 338, loss is 0.1552\n",
-      "epoch: 10 step: 339, loss is 0.3564\n",
-      "epoch: 10 step: 340, loss is 0.3401\n",
-      "epoch: 10 step: 341, loss is 0.2185\n",
-      "epoch: 10 step: 342, loss is 0.1962\n",
-      "epoch: 10 step: 343, loss is 0.2351\n",
-      "epoch: 10 step: 344, loss is 0.2256\n",
-      "epoch: 10 step: 345, loss is 0.3031\n",
-      "epoch: 10 step: 346, loss is 0.3497\n",
-      "epoch: 10 step: 347, loss is 0.3768\n",
-      "epoch: 10 step: 348, loss is 0.2074\n",
-      "epoch: 10 step: 349, loss is 0.1948\n",
-      "epoch: 10 step: 350, loss is 0.2780\n",
-      "epoch: 10 step: 351, loss is 0.2888\n",
-      "epoch: 10 step: 352, loss is 0.2742\n",
-      "epoch: 10 step: 353, loss is 0.3123\n",
-      "epoch: 10 step: 354, loss is 0.3578\n",
-      "epoch: 10 step: 355, loss is 0.1633\n",
-      "epoch: 10 step: 356, loss is 0.2015\n",
-      "epoch: 10 step: 357, loss is 0.2081\n",
-      "epoch: 10 step: 358, loss is 0.2807\n",
-      "epoch: 10 step: 359, loss is 0.2153\n",
-      "epoch: 10 step: 360, loss is 0.3053\n",
-      "epoch: 10 step: 361, loss is 0.3514\n",
-      "epoch: 10 step: 362, loss is 0.2499\n",
-      "epoch: 10 step: 363, loss is 0.2624\n",
-      "epoch: 10 step: 364, loss is 0.2889\n",
-      "epoch: 10 step: 365, loss is 0.2481\n",
-      "epoch: 10 step: 366, loss is 0.2942\n",
-      "epoch: 10 step: 367, loss is 0.3332\n",
-      "epoch: 10 step: 368, loss is 0.3419\n",
-      "epoch: 10 step: 369, loss is 0.1517\n",
-      "epoch: 10 step: 370, loss is 0.2912\n",
-      "epoch: 10 step: 371, loss is 0.2824\n",
-      "epoch: 10 step: 372, loss is 0.2197\n",
-      "epoch: 10 step: 373, loss is 0.4275\n",
-      "epoch: 10 step: 374, loss is 0.3104\n",
-      "epoch: 10 step: 375, loss is 0.1147\n",
-      "epoch: 10 step: 376, loss is 0.2216\n",
-      "epoch: 10 step: 377, loss is 0.2799\n",
-      "epoch: 10 step: 378, loss is 0.2447\n",
-      "epoch: 10 step: 379, loss is 0.2776\n",
+      "\n",
+      "...\n",
       "epoch: 10 step: 380, loss is 0.3090\n",
       "epoch: 10 step: 381, loss is 0.2692\n",
       "epoch: 10 step: 382, loss is 0.3088\n",
@@ -5017,13 +866,7 @@
       "epoch: 10 step: 385, loss is 0.2522\n",
       "epoch: 10 step: 386, loss is 0.2532\n",
       "epoch: 10 step: 387, loss is 0.3558\n",
-      "epoch: 10 step: 388, loss is 0.2641\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
+      "epoch: 10 step: 388, loss is 0.2641\n",
       "epoch: 10 step: 389, loss is 0.2334\n",
       "epoch: 10 step: 390, loss is 0.1966\n",
       "Epoch time: 43320.815, per step time: 111.079, avg loss: 0.262\n",
diff --git a/tutorials/source_en/use/custom_operator.md b/tutorials/source_en/use/custom_operator.md
index c6f4296a3df4ed91a1834627fa4e5e79b5b90425..3c375b7d653641e722b84c90ac3392fdffbc4571 100644
--- a/tutorials/source_en/use/custom_operator.md
+++ b/tutorials/source_en/use/custom_operator.md
@@ -77,7 +77,7 @@ The entry function of an operator describes the internal process of compiling th
 4. Call `cce_build_code` to compile and generate an operator binary file.
 > The input parameters of the entry function require the input information of each operator, output information of each operator, operator attributes (optional), and `kernel_name` (name of the generated operator binary file). The input and output information is encapsulated in dictionaries, including the input and output shape and dtype when the operator is called on the network.
 
-For details about TBE operator development, visit the [TBE website](https://www.huaweicloud.com/ascend/tbe). For details about how to debug and optimize the TBE operator, visit the [Mind Studio website](https://www.huaweicloud.com/intl/en-us/ascend/mindstudio).
+For details about TBE operator development, visit the [TBE website](https://www.huaweicloud.com/ascend/dev/operator). For details about how to debug and optimize the TBE operator, visit the [Mind Studio website](https://www.huaweicloud.com/intl/en-us/ascend/mindstudio).
 
 ### Registering the Operator Information
 
diff --git a/tutorials/source_zh_cn/use/custom_operator.md b/tutorials/source_zh_cn/use/custom_operator.md
index 064b271fd8daedef06cebffb2b552f8322daebd1..f5bb7e77831e0d3d50a7f6225c37e70fda02b072 100644
--- a/tutorials/source_zh_cn/use/custom_operator.md
+++ b/tutorials/source_zh_cn/use/custom_operator.md
@@ -77,7 +77,7 @@ class CusSquare(PrimitiveWithInfer):
 4. 调用`cce_build_code`编译生成算子二进制。
 > 入口函数的输入参数有特殊要求，需要依次为：算子每个输入的信息、算子每个输出的信息、算子属性（可选）和`kernel_name`（生成算子二进制的名称）。输入和输出的信息用字典封装传入，其中包含该算子在网络中被调用时传入的实际输入和输出的shape和dtype。
 
-更多关于使用TBE开发算子的内容请参考[TBE文档](https://www.huaweicloud.com/ascend/tbe)，关于TBE算子的调试和性能优化请参考[MindStudio文档](https://www.huaweicloud.com/ascend/mindstudio)。
+更多关于使用TBE开发算子的内容请参考[TBE文档](https://www.huaweicloud.com/ascend/dev/operator)，关于TBE算子的调试和性能优化请参考[MindStudio文档](https://www.huaweicloud.com/ascend/mindstudio)。
 
 ### 注册算子信息