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   "source": [
    "# 运算重载\n",
    "\n",
    "[![在线运行](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r1.7/resource/_static/logo_modelarts.png)](https://authoring-modelarts-cnnorth4.huaweicloud.com/console/lab?share-url-b64=aHR0cHM6Ly9taW5kc3BvcmUtd2Vic2l0ZS5vYnMuY24tbm9ydGgtNC5teWh1YXdlaWNsb3VkLmNvbS9ub3RlYm9vay9yMS43L3R1dG9yaWFscy9leHBlcnRzL3poX2NuL29wZXJhdGlvbi9taW5kc3BvcmVfb3Bfb3ZlcmxvYWQuaXB5bmI=&imageid=9d63f4d1-dc09-4873-b669-3483cea777c0) [![下载Notebook](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r1.7/resource/_static/logo_notebook.png)](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/r1.7/tutorials/experts/zh_cn/operation/mindspore_op_overload.ipynb) [![下载样例代码](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r1.7/resource/_static/logo_download_code.png)](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/r1.7/tutorials/experts/zh_cn/operation/mindspore_op_overload.py) [![查看源文件](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/r1.7/resource/_static/logo_source.png)](https://gitee.com/mindspore/docs/blob/r1.7/tutorials/experts/source_zh_cn/operation/op_overload.ipynb)\n",
    "\n",
    "## 概述\n",
    "\n",
    "`mindspore.ops.composite`中提供了一些涉及图变换的组合类算子，例如`MultitypeFuncGraph`、`HyperMap`等。\n",
    "\n",
    "## MultitypeFuncGraph\n",
    "\n",
    "`MultitypeFuncGraph`用于生成重载函数，支持不同类型的输入。用户可以使用`MultitypeFuncGraph`定义一组重载的函数，根据不同类型，采用不同实现。首先初始化一个`MultitypeFuncGraph` 对象，使用带有输入类型的 `register` 作为待注册函数的装饰器，使得该对象支持多种类型的输入。更多使用方法见：[MultitypeFuncGraph](https://www.mindspore.cn/docs/zh-CN/r1.7/api_python/ops/mindspore.ops.MultitypeFuncGraph.html)。\n",
    "\n",
    "代码样例如下："
   ]
  },
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   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-12-31T08:28:36.365991Z",
     "start_time": "2021-12-31T08:28:34.387953Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor [[2.4 4.2]\n",
      " [4.4 6.4]]\n",
      "scalar 3\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from mindspore.ops import MultitypeFuncGraph\n",
    "from mindspore import Tensor\n",
    "import mindspore.ops as ops\n",
    "\n",
    "add = MultitypeFuncGraph('add')\n",
    "@add.register(\"Number\", \"Number\")\n",
    "def add_scalar(x, y):\n",
    "    return ops.scalar_add(x, y)\n",
    "\n",
    "@add.register(\"Tensor\", \"Tensor\")\n",
    "def add_tensor(x, y):\n",
    "    return ops.tensor_add(x, y)\n",
    "\n",
    "tensor1 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))\n",
    "tensor2 = Tensor(np.array([[1.2, 2.1], [2.2, 3.2]]).astype('float32'))\n",
    "print('tensor', add(tensor1, tensor2))\n",
    "print('scalar', add(1, 2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HyperMap\n",
    "\n",
    "`HyperMap`可以对一组或多组输入做指定的运算，可以配合`MultitypeFuncGraph`一起使用。例如定义一组重载的`add`函数后，对多组不同类型的输入进行`add`运算。不同于`Map`，`HyperMap` 能够用于嵌套结构，对序列或嵌套序列中的输入做指定运算。更多使用方法见：[HyperMap](https://www.mindspore.cn/docs/zh-CN/r1.7/api_python/ops/mindspore.ops.HyperMap.html)。\n",
    "\n",
    "代码样例如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-12-31T08:28:36.379981Z",
     "start_time": "2021-12-31T08:28:36.368396Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "output = (Tensor(shape=[], dtype=Float32, value= 4), Tensor(shape=[], dtype=Float32, value= 6), 3)\n"
     ]
    }
   ],
   "source": [
    "from mindspore import dtype as mstype\n",
    "from mindspore import Tensor\n",
    "from mindspore.ops import MultitypeFuncGraph, HyperMap\n",
    "import mindspore.ops as ops\n",
    "\n",
    "add = MultitypeFuncGraph('add')\n",
    "@add.register(\"Number\", \"Number\")\n",
    "def add_scalar(x, y):\n",
    "    return ops.scalar_add(x, y)\n",
    "\n",
    "@add.register(\"Tensor\", \"Tensor\")\n",
    "def add_tensor(x, y):\n",
    "    return ops.tensor_add(x, y)\n",
    "\n",
    "add_map = HyperMap(add)\n",
    "output = add_map((Tensor(1, mstype.float32), Tensor(2, mstype.float32), 1), (Tensor(3, mstype.float32), Tensor(4, mstype.float32), 2))\n",
    "print(\"output =\", output)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "此例子中传入`add_map`的输入包含了两个序列，`HyperMap`会以`operation(args[0][i], args[1][i])`的形式分别从两个序列中取相应的元素作为`add`函数的输入`x`和`y`，例如`add(Tensor(1, mstype.float32), Tensor(3, mstype.float32))`。"
   ]
  }
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