diff --git a/tutorials/fastnlp_tutorial_0.ipynb b/tutorials/fastnlp_tutorial_0.ipynb index 26675ecf..4368652a 100644 --- a/tutorials/fastnlp_tutorial_0.ipynb +++ b/tutorials/fastnlp_tutorial_0.ipynb @@ -86,9 +86,11 @@ "\n", "  具体`driver`与`Trainer`以及`Evaluator`之间的关系请参考`fastNLP 0.8`的框架设计\n", "\n", - "注：在同一脚本中，`Trainer`和`Evaluator`使用的`driver`应当保持一致\n", + "注：这里给出一条建议：**在同一脚本中**，**所有的`Trainer`和`Evaluator`使用的`driver`应当保持一致**\n", "\n", - "  一个不能违背的原则在于：**不要将多卡的`driver`前使用单卡的`driver`**（？？？），这样使用可能会带来很多意想不到的错误" + "  尽量不出现，之前使用单卡的`driver`，后面又使用多卡的`driver`，这是因为，当脚本执行至\n", + "\n", + "  多卡`driver`处时，会重启一个进程执行之前所有内容，如此一来可能会造成一些意想不到的麻烦" ] }, { @@ -167,7 +169,7 @@ "\n", "注：在`fastNLP 0.8`中，**`Trainer`要求模型通过`train_step`来返回一个字典**，**满足如`{\"loss\": loss}`的形式**\n", "\n", - "  此外，这里也可以通过传入`Trainer`的参数`output_mapping`来实现高度化的定制，具体请见这一note（？？？）\n", + "  此外，这里也可以通过传入`Trainer`的参数`output_mapping`来实现输出的转换，详见（trainer的详细讲解，待补充）\n", "\n", "同样，在`fastNLP 0.8`中，**函数`evaluate_step`是`Evaluator`中参数`evaluate_fn`的默认值**\n", "\n", @@ -177,7 +179,7 @@ "\n", "  从模块角度，该字典的键值和`metric`中的`update`函数的签名一致，这样的机制在传参时被称为“**参数匹配**”\n", "\n", - "" + "" ] }, { @@ -216,8 +218,14 @@ "\n", " def __getitem__(self, item):\n", " return {\"x\": self.x[item], \"y\": self.y[item]}\n", - "```\n", - "***\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "f5f1a6aa", + "metadata": {}, + "source": [ "对于后者，首先要明确，在`Trainer`和`Evaluator`中，`metrics`的计算分为`update`和`get_metric`两步\n", "\n", "    **`update`函数**，**针对一个`batch`的预测结果**，计算其累计的评价指标\n", @@ -230,7 +238,9 @@ "\n", "  在此基础上，**`fastNLP 0.8`要求`evaluate_dataloader`生成的每个`batch`传递给对应的`metric`**\n", "\n", - "    **以`{\"pred\": y_pred, \"target\": y_true}`的形式**，对应其`update`函数的函数签名" + "    **以`{\"pred\": y_pred, \"target\": y_true}`的形式**，对应其`update`函数的函数签名\n", + "\n", + "" ] }, { @@ -639,11 +649,11 @@ { "data": { "text/html": [ - "
{'acc#acc': 0.29}\n",
+       "
{'acc#acc': 0.39}\n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[1m{\u001b[0m\u001b[32m'acc#acc'\u001b[0m: \u001b[1;36m0.29\u001b[0m\u001b[1m}\u001b[0m\n"
+       "\u001b[1m{\u001b[0m\u001b[32m'acc#acc'\u001b[0m: \u001b[1;36m0.39\u001b[0m\u001b[1m}\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -652,7 +662,7 @@
     {
      "data": {
       "text/plain": [
-       "{'acc#acc': 0.29}"
+       "{'acc#acc': 0.39}"
       ]
      },
      "execution_count": 9,
@@ -710,7 +720,9 @@
    "source": [
     "通过使用`Trainer`类的`run`函数，进行训练\n",
     "\n",
-    "  还可以通过参数`num_eval_sanity_batch`决定每次训练前运行多少个`evaluate_batch`进行评测，默认为2"
+    "  还可以通过参数`num_eval_sanity_batch`决定每次训练前运行多少个`evaluate_batch`进行评测，默认为2\n",
+    "\n",
+    "  之所以“先评测后训练”，是为了保证训练很长时间的数据，不会在评测阶段出问题，故作此试探性评测"
    ]
   },
   {
@@ -773,6 +785,14 @@
    "source": [
     "trainer.run()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c4e9c619",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
diff --git a/tutorials/fastnlp_tutorial_1.ipynb b/tutorials/fastnlp_tutorial_1.ipynb
index 93e7a664..c378b54a 100644
--- a/tutorials/fastnlp_tutorial_1.ipynb
+++ b/tutorials/fastnlp_tutorial_1.ipynb
@@ -153,7 +153,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2438703969992 2438374526920\n",
+      "1608199516936 1607874531400\n",
       "+-----+------------------------+------------------------+-----+\n",
       "| idx | sentence               | words                  | num |\n",
       "+-----+------------------------+------------------------+-----+\n",
@@ -183,7 +183,7 @@
    "id": "aa277674",
    "metadata": {},
    "source": [
-    "  注二：在`fastNLP 0.8`中，**对`dataset`使用等号**，**其效果是传引用**，**而不是赋值**（？？？）\n",
+    "  注二：**对对象使用等号一般表示传引用**，所以对`dataset`使用等号，是传引用而不是赋值\n",
     "\n",
     "    如下所示，**`dropped`和`dataset`具有相同`id`**，**对`dropped`执行删除操作`dataset`同时会被修改**"
    ]
@@ -198,7 +198,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2438374526920 2438374526920\n",
+      "1607874531400 1607874531400\n",
       "+-----+------------------------+------------------------+-----+\n",
       "| idx | sentence               | words                  | num |\n",
       "+-----+------------------------+------------------------+-----+\n",
@@ -296,9 +296,9 @@
     "\n",
     "在`dataset`模块中，`apply`、`apply_field`、`apply_more`和`apply_field_more`函数可以进行简单的数据预处理\n",
     "\n",
-    "  **`apply`和`apply_more`针对整条实例**，**`apply_field`和`apply_field_more`仅针对实例的部分字段**\n",
+    "  **`apply`和`apply_more`输入整条实例**，**`apply_field`和`apply_field_more`仅输入实例的部分字段**\n",
     "\n",
-    "  **`apply`和`apply_field`仅针对单个字段**，**`apply_more`和`apply_field_more`则可以针对多个字段**\n",
+    "  **`apply`和`apply_field`仅输出单个字段**，**`apply_more`和`apply_field_more`则是输出多个字段**\n",
     "\n",
     "  **`apply`和`apply_field`返回的是个列表**，**`apply_more`和`apply_field_more`返回的是个字典**\n",
     "\n",
@@ -311,14 +311,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "72a0b5f9",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "",
+       "model_id": "8532c5609a394c19b60315663a6f0f4a",
        "version_major": 2,
        "version_minor": 0
       },
@@ -328,42 +328,6 @@
      },
      "metadata": {},
      "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
\n",
-       "
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-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+-----+------------------------------+------------------------------+\n",
-      "| idx | sentence                     | words                        |\n",
-      "+-----+------------------------------+------------------------------+\n",
-      "| 0   | This is an apple .           | ['This', 'is', 'an', 'app... |\n",
-      "| 1   | I like apples .              | ['I', 'like', 'apples', '... |\n",
-      "| 2   | Apples are good for our h... | ['Apples', 'are', 'good',... |\n",
-      "+-----+------------------------------+------------------------------+\n"
-     ]
     }
    ],
    "source": [
@@ -384,57 +348,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "b1a8631f",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+-----+------------------------------+------------------------------+\n",
-      "| idx | sentence                     | words                        |\n",
-      "+-----+------------------------------+------------------------------+\n",
-      "| 0   | This is an apple .           | ['This', 'is', 'an', 'app... |\n",
-      "| 1   | I like apples .              | ['I', 'like', 'apples', '... |\n",
-      "| 2   | Apples are good for our h... | ['Apples', 'are', 'good',... |\n",
-      "+-----+------------------------------+------------------------------+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "dataset = DataSet(data)\n",
     "\n",
@@ -459,57 +376,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "057c1d2c",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+-----+------------------------------+------------------------------+\n",
-      "| idx | sentence                     | words                        |\n",
-      "+-----+------------------------------+------------------------------+\n",
-      "| 0   | This is an apple .           | ['This', 'is', 'an', 'app... |\n",
-      "| 1   | I like apples .              | ['I', 'like', 'apples', '... |\n",
-      "| 2   | Apples are good for our h... | ['Apples', 'are', 'good',... |\n",
-      "+-----+------------------------------+------------------------------+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "dataset = DataSet(data)\n",
     "dataset.apply_field(lambda sent:sent.split(), field_name='sentence', new_field_name='words')\n",
@@ -528,57 +398,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "51e2f02c",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+-----+------------------------+------------------------+-----+\n",
-      "| idx | sentence               | words                  | num |\n",
-      "+-----+------------------------+------------------------+-----+\n",
-      "| 0   | This is an apple .     | ['This', 'is', 'an'... | 5   |\n",
-      "| 1   | I like apples .        | ['I', 'like', 'appl... | 4   |\n",
-      "| 2   | Apples are good for... | ['Apples', 'are', '... | 7   |\n",
-      "+-----+------------------------+------------------------+-----+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "dataset = DataSet(data)\n",
     "dataset.apply_more(lambda ins:{'words': ins['sentence'].split(), 'num': len(ins['sentence'].split())})\n",
@@ -597,57 +420,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "db4295d5",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
\n"
-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+-----+------------------------+------------------------+-----+\n",
-      "| idx | sentence               | words                  | num |\n",
-      "+-----+------------------------+------------------------+-----+\n",
-      "| 0   | This is an apple .     | ['This', 'is', 'an'... | 5   |\n",
-      "| 1   | I like apples .        | ['I', 'like', 'appl... | 4   |\n",
-      "| 2   | Apples are good for... | ['Apples', 'are', '... | 7   |\n",
-      "+-----+------------------------+------------------------+-----+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "dataset = DataSet(data)\n",
     "dataset.apply_field_more(lambda sent:{'words': sent.split(), 'num': len(sent.split())}, \n",
@@ -669,7 +445,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "012f537c",
    "metadata": {},
    "outputs": [],
@@ -700,20 +476,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "a4c1c10d",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "dict_items([('sentence', 'This is an apple .'), ('words', ['This', 'is', 'an', 'apple', '.']), ('num', 5)])\n",
-      "dict_keys(['sentence', 'words', 'num'])\n",
-      "dict_values(['This is an apple .', ['This', 'is', 'an', 'apple', '.'], 5])\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "ins = Instance(sentence=\"This is an apple .\", words=['This', 'is', 'an', 'apple', '.'], num=5)\n",
     "\n",
@@ -732,22 +498,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "55376402",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+--------------------+------------------------+-----+-----+\n",
-      "| sentence           | words                  | num | idx |\n",
-      "+--------------------+------------------------+-----+-----+\n",
-      "| This is an apple . | ['This', 'is', 'an'... | 5   | 0   |\n",
-      "+--------------------+------------------------+-----+-----+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "ins.add_field(field_name='idx', field=0)\n",
     "print(ins)"
@@ -767,44 +521,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "id": "fe15f4c1",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'sentence': ,\n",
-       " 'words': ,\n",
-       " 'num': }"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "dataset.get_all_fields()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "5433815c",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "['num', 'sentence', 'words']"
-      ]
-     },
-     "execution_count": 16,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "dataset.get_field_names()"
    ]
@@ -823,29 +553,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "id": "25ce5488",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "3 False\n",
-      "6 True\n",
-      "+------------------------------+------------------------------+--------+\n",
-      "| sentence                     | words                        | length |\n",
-      "+------------------------------+------------------------------+--------+\n",
-      "| This is an apple .           | ['This', 'is', 'an', 'app... | 5      |\n",
-      "| I like apples .              | ['I', 'like', 'apples', '... | 4      |\n",
-      "| Apples are good for our h... | ['Apples', 'are', 'good',... | 7      |\n",
-      "| This is an apple .           | ['This', 'is', 'an', 'app... | 5      |\n",
-      "| I like apples .              | ['I', 'like', 'apples', '... | 4      |\n",
-      "| Apples are good for our h... | ['Apples', 'are', 'good',... | 7      |\n",
-      "+------------------------------+------------------------------+--------+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(len(dataset), dataset.has_field('length')) \n",
     "if 'num' in dataset:\n",
@@ -877,21 +588,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "id": "3515e096",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Vocabulary([]...)\n",
-      "{'': 0, '': 1}\n",
-      " 0\n",
-      " 1\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from fastNLP.core.vocabulary import Vocabulary\n",
     "\n",
@@ -914,20 +614,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "id": "88c7472a",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "5 Counter({'生活': 1, '就像': 1, '海洋': 1})\n",
-      "6 Counter({'生活': 1, '就像': 1, '海洋': 1, '只有': 1})\n",
-      "6 {'': 0, '': 1, '生活': 2, '就像': 3, '海洋': 4, '只有': 5}\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vocab.add_word_lst(['生活', '就像', '海洋'])\n",
     "print(len(vocab), vocab.word_count)\n",
@@ -950,21 +640,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "id": "3447acde",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      " 0\n",
-      " 1\n",
-      "生活 2\n",
-      "彼岸 1 False\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "print(vocab.to_word(0), vocab.to_index(''))\n",
     "print(vocab.to_word(1), vocab.to_index(''))\n",
@@ -986,21 +665,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "id": "490b101c",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "生活 2\n",
-      "彼岸 12 True\n",
-      "13 Counter({'人': 4, '生活': 2, '就像': 2, '海洋': 2, '只有': 2, '意志': 1, '坚强的': 1, '才': 1, '能': 1, '到达': 1, '彼岸': 1})\n",
-      "13 {'': 0, '': 1, '生活': 2, '就像': 3, '海洋': 4, '只有': 5, '人': 6, '意志': 7, '坚强的': 8, '才': 9, '能': 10, '到达': 11, '彼岸': 12}\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vocab.add_word_lst(['生活', '就像', '海洋', '只有', '意志', '坚强的', '人', '人', '人', '人', '才', '能', '到达', '彼岸'])\n",
     "print(vocab.to_word(2), vocab.to_index('生活'))\n",
@@ -1023,19 +691,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": null,
    "id": "a99ff909",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'positive': 0, 'negative': 1}\n",
-      "ValueError: word `neutral` not in vocabulary\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vocab = Vocabulary(unknown=None, padding=None)\n",
     "\n",
@@ -1058,19 +717,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": null,
    "id": "432f74c1",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'': 0, 'positive': 1, 'negative': 2}\n",
-      "0 \n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vocab = Vocabulary(unknown='', padding=None)\n",
     "\n",
@@ -1096,92 +746,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "id": "3dbd985d",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-       "\n",
-       "\n",
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-       "      \n",
-       "      \n",
-       "    \n",
-       "  \n",
-       "
SentenceIdSentenceSentiment
01A series of escapades demonstrating the adage ...negative
12This quiet , introspective and entertaining in...positive
23Even fans of Ismail Merchant 's work , I suspe...negative
34A positively thrilling combination of ethnogra...neutral
45A comedy-drama of nearly epic proportions root...positive
56The Importance of Being Earnest , so thick wit...neutral
\n",
-       "
"
-      ],
-      "text/plain": [
-       "   SentenceId                                           Sentence Sentiment\n",
-       "0           1  A series of escapades demonstrating the adage ...  negative\n",
-       "1           2  This quiet , introspective and entertaining in...  positive\n",
-       "2           3  Even fans of Ismail Merchant 's work , I suspe...  negative\n",
-       "3           4  A positively thrilling combination of ethnogra...   neutral\n",
-       "4           5  A comedy-drama of nearly epic proportions root...  positive\n",
-       "5           6  The Importance of Being Earnest , so thick wit...   neutral"
-      ]
-     },
-     "execution_count": 24,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
     "\n",
@@ -1199,60 +767,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": null,
    "id": "4f634586",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+------------+------------------------------+-----------+\n",
-      "| SentenceId | Sentence                     | Sentiment |\n",
-      "+------------+------------------------------+-----------+\n",
-      "| 1          | ['a', 'series', 'of', 'es... | negative  |\n",
-      "| 2          | ['this', 'quiet', ',', 'i... | positive  |\n",
-      "| 3          | ['even', 'fans', 'of', 'i... | negative  |\n",
-      "| 4          | ['a', 'positively', 'thri... | neutral   |\n",
-      "| 5          | ['a', 'comedy-drama', 'of... | positive  |\n",
-      "| 6          | ['the', 'importance', 'of... | neutral   |\n",
-      "+------------+------------------------------+-----------+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from fastNLP.core.dataset import DataSet\n",
     "\n",
@@ -1273,7 +791,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": null,
    "id": "46722efc",
    "metadata": {},
    "outputs": [],
@@ -1297,55 +815,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": null,
    "id": "a2de615b",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Counter({'a': 9, 'of': 9, ',': 7, 'the': 6, '.': 5, 'is': 3, 'and': 3, 'good': 2, 'for': 2, 'which': 2, 'this': 2, \"'s\": 2, 'series': 1, 'escapades': 1, 'demonstrating': 1, 'adage': 1, 'that': 1, 'what': 1, 'goose': 1, 'also': 1, 'gander': 1, 'some': 1, 'occasionally': 1, 'amuses': 1, 'but': 1, 'none': 1, 'amounts': 1, 'to': 1, 'much': 1, 'story': 1, 'quiet': 1, 'introspective': 1, 'entertaining': 1, 'independent': 1, 'worth': 1, 'seeking': 1, 'even': 1, 'fans': 1, 'ismail': 1, 'merchant': 1, 'work': 1, 'i': 1, 'suspect': 1, 'would': 1, 'have': 1, 'hard': 1, 'time': 1, 'sitting': 1, 'through': 1, 'one': 1, 'positively': 1, 'thrilling': 1, 'combination': 1, 'ethnography': 1, 'all': 1, 'intrigue': 1, 'betrayal': 1, 'deceit': 1, 'murder': 1, 'shakespearean': 1, 'tragedy': 1, 'or': 1, 'juicy': 1, 'soap': 1, 'opera': 1, 'comedy-drama': 1, 'nearly': 1, 'epic': 1, 'proportions': 1, 'rooted': 1, 'in': 1, 'sincere': 1, 'performance': 1, 'by': 1, 'title': 1, 'character': 1, 'undergoing': 1, 'midlife': 1, 'crisis': 1, 'importance': 1, 'being': 1, 'earnest': 1, 'so': 1, 'thick': 1, 'with': 1, 'wit': 1, 'it': 1, 'plays': 1, 'like': 1, 'reading': 1, 'from': 1, 'bartlett': 1, 'familiar': 1, 'quotations': 1}) \n",
-      "\n",
-      "{'': 0, '': 1, 'a': 2, 'of': 3, ',': 4, 'the': 5, '.': 6, 'is': 7, 'and': 8, 'good': 9, 'for': 10, 'which': 11, 'this': 12, \"'s\": 13, 'series': 14, 'escapades': 15, 'demonstrating': 16, 'adage': 17, 'that': 18, 'what': 19, 'goose': 20, 'also': 21, 'gander': 22, 'some': 23, 'occasionally': 24, 'amuses': 25, 'but': 26, 'none': 27, 'amounts': 28, 'to': 29, 'much': 30, 'story': 31, 'quiet': 32, 'introspective': 33, 'entertaining': 34, 'independent': 35, 'worth': 36, 'seeking': 37, 'even': 38, 'fans': 39, 'ismail': 40, 'merchant': 41, 'work': 42, 'i': 43, 'suspect': 44, 'would': 45, 'have': 46, 'hard': 47, 'time': 48, 'sitting': 49, 'through': 50, 'one': 51, 'positively': 52, 'thrilling': 53, 'combination': 54, 'ethnography': 55, 'all': 56, 'intrigue': 57, 'betrayal': 58, 'deceit': 59, 'murder': 60, 'shakespearean': 61, 'tragedy': 62, 'or': 63, 'juicy': 64, 'soap': 65, 'opera': 66, 'comedy-drama': 67, 'nearly': 68, 'epic': 69, 'proportions': 70, 'rooted': 71, 'in': 72, 'sincere': 73, 'performance': 74, 'by': 75, 'title': 76, 'character': 77, 'undergoing': 78, 'midlife': 79, 'crisis': 80, 'importance': 81, 'being': 82, 'earnest': 83, 'so': 84, 'thick': 85, 'with': 86, 'wit': 87, 'it': 88, 'plays': 89, 'like': 90, 'reading': 91, 'from': 92, 'bartlett': 93, 'familiar': 94, 'quotations': 95} \n",
-      "\n",
-      "Vocabulary(['a', 'series', 'of', 'escapades', 'demonstrating']...)\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from fastNLP.core.vocabulary import Vocabulary\n",
     "\n",
@@ -1368,60 +841,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "id": "2f9a04b2",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+------------+------------------------------+-----------+\n",
-      "| SentenceId | Sentence                     | Sentiment |\n",
-      "+------------+------------------------------+-----------+\n",
-      "| 1          | [2, 14, 3, 15, 16, 5, 17,... | negative  |\n",
-      "| 2          | [12, 32, 4, 33, 8, 34, 35... | positive  |\n",
-      "| 3          | [38, 39, 3, 40, 41, 13, 4... | negative  |\n",
-      "| 4          | [2, 52, 53, 54, 3, 55, 8,... | neutral   |\n",
-      "| 5          | [2, 67, 3, 68, 69, 70, 71... | positive  |\n",
-      "| 6          | [5, 81, 3, 82, 83, 4, 84,... | neutral   |\n",
-      "+------------+------------------------------+-----------+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "vocab.index_dataset(dataset, field_name='Sentence')\n",
     "print(dataset)"
@@ -1437,67 +860,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": null,
    "id": "5f5eed18",
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'negative': 0, 'positive': 1, 'neutral': 2}\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-      ],
-      "text/plain": []
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/html": [
-       "
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-       "
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-      ],
-      "text/plain": [
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "+------------+------------------------------+-----------+\n",
-      "| SentenceId | Sentence                     | Sentiment |\n",
-      "+------------+------------------------------+-----------+\n",
-      "| 1          | [2, 14, 3, 15, 16, 5, 17,... | 0         |\n",
-      "| 2          | [12, 32, 4, 33, 8, 34, 35... | 1         |\n",
-      "| 3          | [38, 39, 3, 40, 41, 13, 4... | 0         |\n",
-      "| 4          | [2, 52, 53, 54, 3, 55, 8,... | 2         |\n",
-      "| 5          | [2, 67, 3, 68, 69, 70, 71... | 1         |\n",
-      "| 6          | [5, 81, 3, 82, 83, 4, 84,... | 2         |\n",
-      "+------------+------------------------------+-----------+\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "target_vocab = Vocabulary(padding=None, unknown=None)\n",
     "\n",
diff --git a/tutorials/figures/T0-fig-parameter-matching.png b/tutorials/figures/T0-fig-parameter-matching.png
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