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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 単純なレイヤの実装"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 乗算レイヤーの実装"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "class MulLayer:\n",
    "    def __init__(self):\n",
    "        \"\"\"\n",
    "        入力値の保存をするメンバ変数を初期化します\n",
    "\n",
    "        Attributes\n",
    "        ----------\n",
    "        x : int\n",
    "            入力1\n",
    "        y : int\n",
    "            入力2\n",
    "        \"\"\"\n",
    "        self.x = None\n",
    "        self.y = None\n",
    "\n",
    "    def forward(self, x, y):\n",
    "        \"\"\"\n",
    "        順伝播の計算をします(乗算)\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        x : int\n",
    "            入力1\n",
    "        y : int\n",
    "            入力2\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        out : int\n",
    "            計算結果\n",
    "        \"\"\"\n",
    "        self.x = x\n",
    "        self.y = y                \n",
    "        out = x * y\n",
    "\n",
    "        return out\n",
    "\n",
    "    def backward(self, dout):\n",
    "        \"\"\"\n",
    "        逆伝播の計算をします(乗算)\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        dout : int\n",
    "            逆伝播で上流から伝わってきた微分\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        dx : int\n",
    "            入力2の微分\n",
    "        dy : int\n",
    "            入力1の微分\n",
    "        \"\"\"\n",
    "        dx = dout * self.y\n",
    "        dy = dout * self.x\n",
    "\n",
    "        return dx, dy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "price: 220\n",
      "dApple: 2.2\n",
      "dApple_num: 110\n",
      "dTax: 200\n"
     ]
    }
   ],
   "source": [
    "apple = 100\n",
    "apple_num = 2\n",
    "tax = 1.1\n",
    "\n",
    "mul_apple_layer = MulLayer()\n",
    "mul_tax_layer = MulLayer()\n",
    "\n",
    "# forward\n",
    "apple_price = mul_apple_layer.forward(apple, apple_num)\n",
    "price = mul_tax_layer.forward(apple_price, tax)\n",
    "\n",
    "# backward\n",
    "dprice = 1\n",
    "dapple_price, dtax = mul_tax_layer.backward(dprice)\n",
    "dapple, dapple_num = mul_apple_layer.backward(dapple_price)\n",
    "\n",
    "print(\"price:\", int(price))\n",
    "print(\"dApple:\", dapple)\n",
    "print(\"dApple_num:\", int(dapple_num))\n",
    "print(\"dTax:\", dtax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加算レイヤの実装"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class AddLayer:\n",
    "    def __init__(self):\n",
    "        \"\"\"\n",
    "        何もしない\n",
    "        \"\"\"\n",
    "        pass\n",
    "\n",
    "    def forward(self, x, y):\n",
    "        \"\"\"\n",
    "        順伝播の計算をします(加算)\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        x : int\n",
    "            入力1\n",
    "        y : int\n",
    "            入力2\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        out : int\n",
    "            計算結果\n",
    "        \"\"\"\n",
    "        out = x + y\n",
    "\n",
    "        return out\n",
    "\n",
    "    def backward(self, dout):\n",
    "        \"\"\"\n",
    "        逆伝播の計算をします(乗算)\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        dout : int\n",
    "            逆伝播で上流から伝わってきた微分\n",
    "\n",
    "        Returns\n",
    "        -------\n",
    "        dx : int\n",
    "            入力2の微分\n",
    "        dy : int\n",
    "            入力1の微分\n",
    "        \"\"\"\n",
    "        dx = dout * 1\n",
    "        dy = dout * 1\n",
    "\n",
    "        return dx, dy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "price: 715\n",
      "dApple: 2.2\n",
      "dApple_num: 110\n",
      "dOrange: 3.3000000000000003\n",
      "dOrange_num: 165\n",
      "dTax: 650\n"
     ]
    }
   ],
   "source": [
    "apple = 100\n",
    "apple_num = 2\n",
    "orange = 150\n",
    "orange_num = 3\n",
    "tax = 1.1\n",
    "\n",
    "# layer\n",
    "mul_apple_layer = MulLayer()\n",
    "mul_orange_layer = MulLayer()\n",
    "add_apple_orange_layer = AddLayer()\n",
    "mul_tax_layer = MulLayer()\n",
    "\n",
    "# forward\n",
    "apple_price = mul_apple_layer.forward(apple, apple_num)  # (1)\n",
    "orange_price = mul_orange_layer.forward(orange, orange_num)  # (2)\n",
    "all_price = add_apple_orange_layer.forward(apple_price, orange_price)  # (3)\n",
    "price = mul_tax_layer.forward(all_price, tax)  # (4)\n",
    "\n",
    "# backward\n",
    "dprice = 1\n",
    "dall_price, dtax = mul_tax_layer.backward(dprice)  # (4)\n",
    "dapple_price, dorange_price = add_apple_orange_layer.backward(dall_price)  # (3)\n",
    "dorange, dorange_num = mul_orange_layer.backward(dorange_price)  # (2)\n",
    "dapple, dapple_num = mul_apple_layer.backward(dapple_price)  # (1)\n",
    "\n",
    "print(\"price:\", int(price))\n",
    "print(\"dApple:\", dapple)\n",
    "print(\"dApple_num:\", int(dapple_num))\n",
    "print(\"dOrange:\", dorange)\n",
    "print(\"dOrange_num:\", int(dorange_num))\n",
    "print(\"dTax:\", dtax)"
   ]
  }
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