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   "cell_type": "markdown",
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   "source": [
    "<img width=\"800px\" src=\"../fidle/img/00-Fidle-header-01.svg\"></img>\n",
    "\n",
    "# <!-- TITLE --> [ACTF1] - Activation functions\n",
    "<!-- DESC --> Some activation functions, with their derivatives.\n",
    "<!-- AUTHOR : Jean-Luc Parouty (CNRS/SIMaP) -->\n",
    "\n",
    "## Objectives :\n",
    " - View the main activation functions \n",
    "\n",
    "Les fonctions d'activation dans Keras :  \n",
    "https://www.tensorflow.org/api_docs/python/tf/keras/activations\n",
    "\n",
    "## What we're going to do :\n",
    "\n",
    " - Juste visualiser les principales fonctions d'activation\n"
   ]
  },
  {
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   "execution_count": 1,
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     "iopub.status.idle": "2021-03-01T20:45:24.768123Z",
     "shell.execute_reply": "2021-03-01T20:45:24.768624Z"
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     },
     "metadata": {},
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    },
    {
     "data": {
      "text/markdown": [
       "<br>**FIDLE 2020 - Practical Work Module**"
      ],
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      ]
     },
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     "text": [
      "Version              : 2.0.17\n",
      "Notebook id          : Unknown\n",
      "Run time             : Monday 01 March 2021, 21:45:24\n",
      "TensorFlow version   : 2.4.0\n",
      "Keras version        : 2.4.0\n",
      "Datasets dir         : /gpfswork/rech/mlh/uja62cb/datasets\n",
      "Run dir              : ./run\n",
      "Update keras cache   : False\n",
      "Save figs            : True\n",
      "Path figs            : ./run/figs\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'/gpfswork/rech/mlh/uja62cb/datasets'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import math\n",
    "from math import erfc, sqrt, exp\n",
    "from math import pi as PI\n",
    "from math import e as E\n",
    "import sys\n",
    "\n",
    "sys.path.append('..')\n",
    "import fidle.pwk as ooo\n",
    "\n",
    "ooo.init()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-03-01T20:45:24.778503Z",
     "iopub.status.busy": "2021-03-01T20:45:24.778014Z",
     "iopub.status.idle": "2021-03-01T20:45:24.779674Z",
     "shell.execute_reply": "2021-03-01T20:45:24.780164Z"
    }
   },
   "outputs": [],
   "source": [
    "SELU_A = -sqrt(2/PI)/(erfc(1/sqrt(2))*exp(1/2)-1)\n",
    "SELU_L = (1-erfc(1/sqrt(2))*sqrt(E))*sqrt(2*PI) / (2*erfc(sqrt(2))*E*E+PI*erfc(1/sqrt(2))**2*E-2*(2+PI)*erfc(1/sqrt(2))*sqrt(E)+PI+2)**0.5\n",
    "\n",
    "\n",
    "def heaviside(z):\n",
    "    return np.where(z<0,0,1)\n",
    "\n",
    "def sign(z):\n",
    "    return np.where(z<0,-1,1)\n",
    "#    return np.sign(z)\n",
    "\n",
    "def sigmoid(z):\n",
    "    return 1 / (1 + np.exp(-z))\n",
    "\n",
    "def tanh(z):\n",
    "    return np.tanh(z)\n",
    "\n",
    "def relu(z):\n",
    "    return np.maximum(0, z)\n",
    "\n",
    "def leaky_relu(z,a=0.05):\n",
    "    return np.maximum(a*z, z)\n",
    "\n",
    "def elu(z,a=1):\n",
    "    #y=z.copy()\n",
    "    y=a*(np.exp(z)-1)\n",
    "    y[z>0]=z[z>0]\n",
    "    return y\n",
    "\n",
    "def selu(z):\n",
    "    return SELU_L*elu(z,a=SELU_A)\n",
    "\n",
    "def derivative(f, z, eps=0.000001):\n",
    "    return (f(z + eps) - f(z - eps))/(2 * eps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
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     "iopub.status.idle": "2021-03-01T20:45:27.378536Z",
     "shell.execute_reply": "2021-03-01T20:45:27.379053Z"
    },
    "jupyter": {
     "source_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
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       "<div class=\"comment\">Saved: ./run/figs/Unknown-Heaviside</div>"
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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div class=\"comment\">Saved: ./run/figs/Unknown-Logit</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div class=\"comment\">Saved: ./run/figs/Unknown-Tanh</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div class=\"comment\">Saved: ./run/figs/Unknown-ReLU</div>"
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      "text/plain": [
       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
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hPsfUEzFXnVfLzBma0LYQKRwlHBmYlaf7UD9PN+0Zea+pyQqXwlHCkYFZeR7dtovBocSEtucuqeCM6tMyUZnkIYWjhME5GBoafX8KfY6DQ45Htu0aea9WY2FTOEoYBscNAD+Fs8sv7NjL3gN9AMyZOZ3LztaEtoVM4ShhyEB/409S7ix49YrFTC/J/E26JH8oHCUMafY3vtNzhK0tXQAYibGNUtgUjhKGNFuOm7a24pKvVy+tYlHFzMzUJXlL4ShhSOPOg8cGxk5oe4OuoxYUjhKKNGbk+bdf7+HAkWMALJhTxkUNCzJZmeQphaOEIY2rY1KviLl25RKKi3QdtSgcJRSnGI5vdx7ktV09iW8rMq5ZuSTTlUmeUjhKGFJPyEyhzzG11Xjp8oVUzi7NZFWSxxSOEoZT6HM8cnSAX6ROaKvhO5JC4ShhOIXD6l+82k7fsUSLs27+bM6vr4yjMslTCkcJwxTDMTGh7egh9ZrVdZrQVsZQOEoYphiOr+/u4e29vQDMmFbMh8/XnQVlLIWjhGGK4bgx5TrqDzbWMLs0/Vu5SlgUjhKGMWerT35CZv/hozz1a01oKyencJQwTKHl+LOXd3N8MDH347KauZy5aE6clUmeUjhKGAYmF45DzrH5xdE7C15/YV2cVUkeUzhKGCbZctza0sU7PUcAmF06jSvOqYm7MslTCkcJwyRvy7px3IS2M6ZpQluJpnCUMKROdlsSfeZ574E+nt+xd+T9mtU6pJYTUzhKGCbRctz8YhvJGwtywRnzWDxvdhYKk3ylcJQwTNDneHxwiEd1Z0GZAoWjhGGCWXmeadpDz+GjAMwrn8HFZ1VnqzLJUwpHCcMEN9gaO6FtHSXF+tWXk9NviIThJH2ObV29vNLaDUCRGdeu1IkYmZjCUcJwkj7HTSmDvi8+awHzT9OEtjIxhaOE4QS3Zu0/NsDPU+4suEZ3FpRJUjhKGAZTxzmOhuMTr3Vw+GiiVVlTOZOVZ8zPdmWSpxSOEoaIPkfn3JgrYtasqqdIE9rKJCkcJQxjJp5IXCHT3HGAHXsOAjCtuIirV2hCW5k8haOEYfC9N9hKHb5zxbmLOG3m9GxXJXlM4ShhGHe2+mDfMZ58rWNk0Q06ESNTpHCUMIzrc3zs5d0cG0hMaNuw8DSW1cz1U5fkLYWjhCGl5eiKS9i0dXRs45rV9bqzoEzZ5G7wK5LrUk7ItOw7wu7uPgBmzijhQ42a0FamTi1HCUNKy/GZHftGXn/4/FpKp6sNIFMXeziaWZGZ3WZmTWbWb2a7zOybZjYr7m1LAUkJx1d2Hxh5vWaVTsTIqclGy/GvgW8BrwNfAB4Gvgj8xMzUcpXMSDmsPpb8tT6vrpLTF5T7qkjyXKzHG2Z2LolA/LFz7saU5W8D3wb+E/BgnDVIgUg5Wz2YDEdNaCvpiLvl9nHAgHvGLb8fOAJ8IubtS6FIOawesCLmzprOpWcv9FiQ5Lu4e6ovAoaA51MXOuf6zeyl5Ncn5dW778hsZRKUM/d2MjwR2YAVc80FS5imCW0lDXGHYw2wzzl3NOJr7cAlZjbdOXdsog86r/X5iVYRAWBB5Wx+59KlvsuQPBd3OM4EooIRoD9lnfeEo5mtBdauW7cuptIkRHtKTuPq9y/h7TebaWxspLu7m46O0csI6+rqKCsro7m5eWRZRUUFtbW17Nixg/7+xK9lSUkJy5cvp7Ozk66urpF1ly5NhG5LS8vIsqqqKqqrq2lqamIgeWKotLSUhoYG2tvb6enpGVl32bJl9PX10dY2Oki9pqaGyspKtm/fPrKsvLyc+vp6Wltb6e3tHVmufcrsPjU2NnIi5pw74RfTZWavAgucc++5m5GZ/Qi4CZhxspbj+vXrHcC6iy+JrU4JRMk0emsXc8nll/quRPLHCS+dirvl2AGcY2YzIg6ta0kcck94SA1w3id17kYmltpSEUlH3D3WLyS38f7UhWZWClwAbIl5+yIipyTucHwIcMCt45Z/lkRf4w9j3r4UmJP1IYlMRayH1c65V83su8AtZvZjYDNwNokrZJ5EA8Alw7q7u6msrPRdhgQgG1fk3wrsBNYCa4B9wHeAO5xzQ1nYvhSQjo4OhaNkROzh6JwbBL6ZfIiI5AVdQiAiEkHhKEGpq6vzXYIEQuEoQSkrK/NdggRC4ShBSb3cTCQdCkcRkQgKRxGRCApHCUpFRYXvEiQQCkcJSm1tre8SJBAKRwnKjh07fJcggVA4SlCGJ0EVSZfCUUQkgsJRglJSko25VKQQKBwlKMuXL/ddggRC4ShB6ezs9F2CBELhKEFJvQOdSDoUjiIiERSOIiIRFI4SlOGbuYukS+EoIhJB4ShBaWlp8V2CBELhKCISQeEoIhJB4ShBqaqq8l2CBELhKEGprq72XYIEQuEoQWlqavJdggRC4ShBGRgY8F2CBELhKCISQeEoQSktLfVdggRC4ShBaWho8F2CBELhKEFpb2/3XYIEQuEoQenp6fFdggRC4SgiEkHhKCISQeEoQVm2bJnvEiQQCkcJSl9fn+8SJBAKRwlKW1ub7xIkEApHEZEICkcRkQgKRwlKTU2N7xIkEApHCUplZaXvEiQQCkcJyvbt232XIIFQOIqIRFA4iohEUDhKUMrLy32XIIFQOEpQ6uvrfZcggVA4SlBaW1t9lyCBUDhKUHp7e32XIIFQOIqIRFA4iohEUDhKUBobG32XIIFQOEpQuru7fZcggVA4SlA6Ojp8lyCBUDiKiERQOIqIRIg9HM3sv5rZD82sycwGzczFvU0pXHV1db5LkECUZGEbXwbmAduAWcDiLGxTClRZWZnvEiQQ2TisvhKY45y7HHg5C9uTAtbc3Oy7BAlE7C1H59zOuLchIpJpOiEjIhJB4ShBqaio8F2CBGJSh9VmNhe4dQqf+23nXFqXKpjZWmDtunXr0vkYKTC1tbW+S5BATLbPcS5w5xQ+9wdAWuHonNsAbFi/fr2G/sik7dixg4aGBt9lSAAmFY7JkyoWbyki6evv7/ddggRCfY4iIhEUjhKUkpJsXNcghSD23yQzuwFYkXzbkFx2e/L9fufcvXHXIIVj+fLlvkuQQGTj3+yNwKfGLbs7+dwKKBwlYzo7O6murvZdhgQg9sNq59ynnXN2gsfpcW9fCktXV5fvEiQQ6nMUEYmgcBQRiaBwlKAsXbrUdwkSCIWjiEgEhaMEpaWlxXcJEgiFo4hIBIWjiEgEhaMEpaqqyncJEgiFowRFV8dIpigcJShNTU2+S5BAKBwlKAMDA75LkEAoHEVEIigcJSilpaW+S5BAKBwlKLp/jGSKwlGC0t7e7rsECYTCUYLS09PjuwQJhMJRRCSCwlFEJILCUYKybNky3yVIIBSOEpS+vj7fJUggFI4SlLa2Nt8lSCAUjiIiERSOIiIRFI4SlJqaGt8lSCAUjhKUyspK3yVIIBSOEpTt27f7LkECoXAUEYmgcBQRiaBwlKCUl5f7LkECoXCUoNTX1/suQQKhcJSgtLa2+i5BAqFwlKD09vb6LkECoXAUEYmgcBQRiaBwlKA0Njb6LkECoXCUoHR3d/suQQKhcJSgdHR0+C5BAqFwFBGJoHAUEYmgcJSg1NXV+S5BAqFwlKCUlZX5LkECoXCUoDQ3N/suQQKhcBQRiaBwFBGJoHCUoFRUVPguQQKhcJSg1NbW+i5BAqFwlKDs2LHDdwkSCIWjBKW/v993CRIIhaOISASFowSlpKTEdwkSCIWjBGX58uW+S5BAKBwlKJ2dnb5LkEAoHCUoXV1dvkuQQCgcRUQixBqOZlZrZl82syfN7B0zO2xmr5nZN8xsXpzbFhFJR9wtxxuAu4B3gW8AtwLPJJ+3mdnCmLcvBWbp0qW+S5BAxD3u4Smg3jm3J2XZ/Wb2K+B+4EvJh4hITom15eice21cMA57KPms+2hKRrW0tPguQQLh64TM4uSzxl2ISE7ydTnBnyafvz/Zb1i/fn1MpYhIAXP33XefRX1hUuFoZnNJnESZrG875yLvrm5mfwjcBGxwzj1+km2uBdauW7duCpsVEckMc85NvJLZ6cDbU/jcM51z75k7ysw+A2wANgP/zjl3fAqfmTVmtsU5d6HvOuIS8v6FvG+g/cumSbUcnXM7gcim52SZ2e+TCMafATfmajCKiECWTsiY2c0khu48BnzMOXc0G9sVETlVsYejmX0a+DvgCeC3nXP5MBvpBt8FxCzk/Qt530D7lzWT6nM85Q83+y3gn4GDwB8BfeNWOeSc+5fYChAROUVxD+VZRaJ1Opfo/witwL/EXIOIyJTF2nIUEclXmrJsCsysyMyeNTNnZht915OuUGZNSv5cbjOzJjPrN7NdZvZNM5vlu7Z0mdlZZvZVM3vOzLrMrNfMXjKzPw5h/8Yzs5lm9nbyb+xen7UoHKdmPXCe7yIyKJRZk/4a+BbwOvAF4GHgi8BPzCzff8d/H7gNaAG+Cvx3oBn4GvCMmZV5rC0OXwXm+y4CAOecHpN4kLge/CDw3wAHbPRdUwb26VxgYcTyzyT38X/4rnGS+zAE/J9xy7+Q3Iff9V1jmvt3ITAnYvnXkvt3i+8aM7ivq4CBlL+xe33Wk+//VbPpXuAt4H/6LiRTXBizJn2cxAUK94xbfj9wBPhEtgvKJOfcFufcgYgv5dPPaEJmVkziZ/Yo8GPP5QD+Jp7IK2b2H4DfAi5xzg2apXWxUD7Ip1mTLiLRcnw+daFzrt/MXkp+PUT59DOajNuA5cCNvgsZppbjBMxsDvBt4G+dc8/5ridLpjxrkkc1wD4XfdVVOzDfzKZnuaZYJVtZd5A4BH3QczlpM7MzSPzOfdUlLlXOCQXRckxzVqG/IvFP5MsZLitjfMyalENmAie6HLU/ZZ1j2SknK+4BPgB8xTnX7LmWTPgbEhPbfMt3IakKIhxJDEK/cwrr/wDoNrPLgM8Cn3TO7Y+hrkyZyyns3/iFyVmTvgFsAm7JSGXxOwIsOMHXSlPWCYKZ3U3iZ7PBOfd13/Wky8w+AVwNXO5ybDKagghHd+qzCn0XeBn4lZk1jPvazOSy/c65fWmWmJY09m9EHs+a1AGcY2YzIg6ta0kccgfRajSzu4Dbge8Bn/NbTfrMbAaJ1uJmYE/K31ht8nlOctk+L40T36fvc/kB7CcxpOBkD6/DDTK0nzcDgySCsdR3PVOsfXhIy2+OW14KHAYe8V1jhvbzzuR+fh8o8l1PhvZp7iT+vhzwJR/1FUTLMQ3/GYjqzH8Y2Ar8BfCeSX3zSZ7OmpTqIeArJPpcn0pZ/lkSfY0/9FBTRpnZHSQG6z8A3OycG/JbUcYcJtG/PV4VcB+JYT1/D7ySzaKG6drqU2BmDtjknLvedy3pCGXWJDP7Dol+uH8mcYh2NokrZJ4GPpTPYWJmnycxxrYN+BMSw5ZSdTrnfp71wmKUcueB7zrnvPV9q+VY2EKZNelWYCewFlgD7AO+A9yRz8GYNDxOs47ooVVPAkGFY65Qy1FEJIIGgYuIRFA4iohEUDiKiERQOIqIRFA4iohEUDiKiERQOIqIRFA4iohEUDiKiERQOIqIRPj/hIJbOCwA4MIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div class=\"comment\">Saved: ./run/figs/Unknown-LeakyReLU</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div class=\"comment\">Saved: ./run/figs/Unknown-ELU</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<div class=\"comment\">Saved: ./run/figs/Unknown-SeLU</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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E0lA4SmJ68cnQ44uvjuw1LoTj07vq6fc5A2IsKytgcemMuOxXYk/hKInnxDGo3eM8Ts+A8y+P7HVxbgQ+fNrV69QjJqkoHCXxvBB21LjmPMgviOx1cW7nuLehjcNNHQBkZ6Zz6aq5Md+nxE/Mw9EY8yljzK+NMQeNMdYYczjW+xQP8/tgy9Oh5UhPqSHup9WPhk+7unIu07Izx9havCYek+j+K9ACvA4UxmF/4mVvboM2Z8gv8guhemPkrw0Px9/8wLnF0CcDNwCOAL+P6e4kFr7/2KhPxSMcK621BwGMMbuB6XHYp3hV+Cn1BVdAxgR+RaflR78eSVkxP60eDEaRcZ1ug20vhpYvumpirz/vMnrm6KKIREc8jhxFIvP8Y6G2jYuXw/zFE3t9QRE5X74n5lMkHD7Zwcf+xxkQIyPN8PM7rqRwWnZM9ynxp3CUxOD3wbOPhJYvv2FSb1NfX095eWzniH5sR11wdKALl8+lcLpG+05GCduUxxhzqzFmq9t1SJzsfAVaAkN+TS+ADRF0FxxBa2trFIs6W9+Aj6d2hkb7vk49YpJWwoajtfYea+0Gt+uQOHnmwdDjt1w79MpzAnlxbyMd3c6pf2lBLusXz3K5IomVhA1HSSGN9c4kWuCcrl52vbv1jCG8R8w1mnY1qSkcxX3PPBR6vPo8mDX5Ib+qqqqiUNDITrR2se1QMwAGuGbtvJjtS9yncBR3dXbAc2ENca94x5Terru7e4oFjS58QNsNS0qYXZAbs32J+2J+tdoY80FgQWCxBMgyxnw2sHzEWvvTWNcgCWzzw6EJtMoWwMpzpvR2R48epbq6OgqFDeXz+3liR/iFGLWnTHbxaMrzV8DwYZy/FLjfDCgcU1V/Hzz1QGj52vdCgs7Yt7W2ieaOHgAKp2Vx/tLZLlcksRbzcLTWXhbrfYhHbXkaTgea3hTNgvMvc7WcsQyZdnXNPDLSEzPEJXr0Lyzu8Pvh8ftCy1fdNHTIsUkqKyub8nsM13Kmh5f2haZd1WjfqUHhKO7YvsVpwgOQmweXXBeVty0uLo7K+4R7ckcd/kCXxNUVxcybqbFTUoHCUeLP74cHfx5avvTtkBudeZ53794dlfcZZK0dMm6jjhpTh8JR4u/1F+BYYLCmrGy4+t3u1jOGnUdaON7aBcC07AzeskKjfacKhaPEl98Hvw9roHDFO6GgyL16xvHYtqPBx1esLicnU9OupgqFo8TX1uegIRA42blO850oys+P3oC3Hd39PLcnbNrVdTqlTiUKR4kfvw9+/7PQ8pU3Rj55VoQWLFgw/kYR+sPu0LSrS+bMYMnc6NYqiU3hKPHzwpNwItDLJDcPrnlP1Hdx5MiRqLyPtZZHXw+dUr9NPWJSjsJR4qOnG37349Dy1e+G6dGf86WjoyMq77P/eDuHTgamXc1I4/Lq6LeflMSmcJT4eOzX0B7oDVM4M+rfNUZbePOdt66cy/QcTbuaahSOEnstTfDEb0LL77oFshN3aoGevgGe3d0QXNYpdWpSOErs/fZH0NfrPK5YAhdeGbNdRWNEnj/uOU5X3wAA84qnUT0/cZsaSewoHCW29u92BpgY9L6PxnTknZaWlim/x2PDesQYjfadkhSOEjsD/fDT74SW118Ey9fGdJcNDQ3jbzSGo00dvHHM+W40Pc1w1RqN9p2qFI4SO0/cDw2BpjXZOfBnm9ytJwKPhY32fcGyUoqmaz7qVKVwlNhoOj50cIkbPwTFJe7VE4F+n5+ndtYHlzXtampTOEr0WQs/+44z0jfA/EqnN0wcVFRM/sryS3sbae9yap41I4dzFid2mEtsKRwl+jY/MnSq1Q9+AtLjM2BDbu7kJ716NOyU+tq180lP04WYVKZwlOhqbIBf3RNavupdsDh206UOt3fv3km9rrGti9drm4DAtKvrdCEm1SkcJXr8PvjB10JtGssq4N23uFpSpJ7YUYcNPD5n8SzmFOa5Wo+4T+Eo0fPIr6B2j/M4PR3+6k7IzHK3pgj4/HbInNTqESOgcJRoqdkBD4QNYvuOP4cFS+NeRlHRxHuzvH6wiabTzrSrBXlZXFhVGu2yxIMUjjJ17S3wva+CdcY+ZMlKuO5PXSmlvLx8wq8J7xFz1ZpyMjXtqqBwlKny++B7/xYacSe/AD726bhdnR7uwIEDE9q+rbOXLfsag8sa7VsGKRxlau77gXNKDU6znY/8ExTNcq2cnp6eCW3/5M46fH7nUsyq+UVUlER/jEnxJoWjTN4fHx06FNkN74dV57hXzwRZa88aZEJkkMJRJqdmB/z8u6HldRc6F2FclpGREfG2bxxrpe5UJwB5WRlcomlXJYzCUSau4Qjc/SXw+Zzl+ZXwkX+M6VBkkVq+fHnE2z4aNu3qZdVl5GRFHqyS/Nz/bRZvaT4B//kZ6DrjLBcUwe13Qc7ku+1FU2Nj4/gbAWd6+nnuzePBZQ0yIcMpHCVy7a3wjU9Da7OznJ0Lt38hoUbbaWpqimi7Z3Y30DvgND1aXDqDpZp2VYZROEpkOtrgPz8NJwODyWZkwsc/DwuXuVrWZD22LXzaVY32LWfTlywyvvYW+PqnQgPXmjT42KdgxTpXy5qs/cfbOXDiNACZ6WlcUT3xhuOS/BSOMrbWZvj6/4MTdc6ySYMP/50z5UECqqysHHeb8H7Ub10xh/xcTbsqZ1M4yuiOH4NvfRaaAxc50tKcwSTOv9zduqagp9/HH3aFRvvWIBMyGn3nKCPbtxu+8slQMKanO90CEzwYa2trx3z++T3H6ex1pl0tK85jzYLieJQlHqQjRznby8/AD7/hzB4IkJUNf/0ZWHOeu3VFwZAeMet0IUZGp3CUEJ8P7vs+PPnb0Lr8QvjbL3r2qnS4ulNn2HXUmdc6zWjaVRmbwlEc7S3O6DqDg0gAzJkPf/slKJnjXl0TVFIyepvL8KPG85fOZmZ+TjxKEo9SOArsfAV++HXoaA+tW38RfPjvIXeae3VNQmnpyAPVDvj8PLmzLrisQSZkPArHVNbbA7/5Afzh96F1xsCNH4Trb06IvtITVVNTM2L/6pf3n6St05l2dWZ+NhuXJE6vHklMCsdUtWc7/ORb0BTqX0xBMXzkTlix3rWypmpgYGDE9eE9Yq5ZO590Dwa/xJfCMdW0t8JvfwjPPzF0/boL4C8+6YzknWROtneztTbU5/pajfYtEVA4por+PnjqAXj4XujpCq3Pmw7vuxUuvto5pfa4nJyzL7I8uaOOwGDfrFs0k7lFmnZVxqdwTHbWwusvwH3/O/QUGpyLLn/+N1A4053aYmDJkiVDlv126LSr161TjxiJjMIxWfn9sH0LPPgLODas18ic+XDzx6B6gzu1xVB9ff2QGQi3HWqmsb0bgPzcTC5armlXJTIKx2Tj88G2F+Che6Hu0NDn8qbDOz8Al90AE5hOwEtaW1uHhOPQaVfnkZXhzqyI4j3J+ReSijra4fnH4ZmHoOXk0OeysuHSt8Pbb4bpM9ypzwXtXX28WHMiuKxpV2UiFI5eZi0ceNMJxVeedS66hMvKhsvfAde+F2YUulGhq57eWcdA4ErMivJCFs7WtKsSOYWjF51sgC1Pw0t/OPsiC8D0Arj0OrjqJqdvdAqpqqoCnGlXH9W0qzIFCkcvsNYZhXvbi7BtCxzZP/J2C5bCFe+E8y6FzKz41pgguru7yczMZE99G0ebnUnAcrPSuXRVmcuVidcoHBNVTxfs3QV7tjl9nwfnbhkudxpsvMRpp7h4RVK0VZyKo0ePUl1dPaRHzKWrysjVtKsyQfqNSRS9PXB4n9Otb892OFTjNMcZSXo6rNoAF10Jay9I2aPE0XT29vPsG5p2VaZG4egGvx8a6+FgjXM7VOM0uxktDMGZBnX1Bqfh9uqNTrMcGdHmN47T2+8DYGFJPlVlhe4WJJ6kcIy1M6ed4Ks/7NzqDkH9EejtHv+1FZXODH8r1kPVGh0hRqCsrIz/+e2bwWVNuyqTFfNwNMakAX8LfAxYCDQBvwI+Z63tjPX+Y85aJwBPNgy9NR137s+cjvy95lbA0lWwcj1UrU3KQSBirbUvg30NzriUmelpXLla067K5MTjyPE/gU8AvwW+DqwILK83xlxlrR3jXNJF1jpHdx3tzu10qzNN6Ui3vt6Jv39+ASxaDouXw+IqWFgFed4aWDYR/eLp7cHHFy+fw4w8HW3L5MQ0HI0xq4Dbgfutte8JW38I+DZwM/CLmBVgrdMwurvTuXV1hR4Hb4F1nR1wus0JwjPtzuPBCaamIjPLOSKctxDKF8G8Rc7jGUUpf2U52nr7fbx2LHQyoraNMhWxPnL8M8AA3xy2/nvAV4EPEGk4PvJ/zhFaX1/gPuzW3xv2XE9gXZ8TfL6RBz+NquwcKJkLpeVQUgaz58LsMudWONOTI2p70Za9jXT3OycicwpzWbsweUYbkviLdThuBPzAK+ErrbU9xpjtgecjc/+PollXZLKynd4m+QVOT5OimVA0a9itBHLzdBSYAF45EOpTfvWaeaTp30SmINbhWAY0W2tH+lKuHrjIGJNlre0b4fnoyMh0wit3WtgtsJwXtpyXDzMKYHqhE4YzCp0jQvEEay3bDjUHlzcune1iNZIMYh2OecBoVyt6wrY5KxyNMbcCt27atAmApg2X48/IxGZkUjy3DDKzaGxtw5+RhT8jk4KSEopL53CwroF+k4Y/I5OsGQVULl9BfX09ra2twfeuqqqiu7ubo0dDvSjKysooLi5m9+7d0NUMjc3k5+ezYMECjhw5QkdHR3Db6upqWlpaaGgI9VqpqKggNzeXvXv3BtcVFRVRXl7OgQMH6OlxPm5GRgbLly+nsbGRpqbQ0P2VlZUA1NaGxl4sKSmhtLSUmpqa4NwoOTk5LFmyZOKfKSBZPxN5xbSccX7VcjPT6D11DMoKPf2ZkvHfKdE+U3V1NaMx1tpRn5wqY8wuYLa19qwRRo0xvwL+BMge68jxtttuswB33313zOoU73vglUPc/bjTvvHiqlI+977kG8hXYmLU715ifaWgAZhljMke4blynFPu2J1SS8p4/dCp4OP1i2e5WIkki1iH46uBfZwXvtIYkwOsA7bGeP+SAnx+PzsPh4XjIoWjTF2sw/GXgAXuGLb+ozjfNf48xvuXFLC3oZ2uPuc7pJIZOZQXqzG9TF1ML8hYa3cZY/4L+Lgx5n7gEUI9ZDYTywbgkjK2h12lXlmWr77UEhXx6D54B3AYuBV4O9AMfAenb3Vidh0UTwlvwlM+Xb9SEh0xD0drrQ+nT/XXY70vST09fQO8eSzUrGRpSa6L1UgyUb828bRdR1uCk2gtKJnOjBxNvSrRofEcxdO2D7tKXVGhwSYkOnTkKJ627WDo+8b1i2aRm6vTaokOhaN4VltnL7WNzmDCacawekHxkO5mIlOhcBTP2hF2Sr28vJBp2ZkuViPJRuEonhXehEe9YiTaFI7iSdZaXgv/vjHQn7qoqMitkiTJKBzFk46d6uRkuzODY15WBivKCwEoL9eEWhIdCkfxpK21obH71i2aSUa686t84MABt0qSJKNwFE96LSwcz60sCT4eHARVZKoUjuI5fQM+dh0JXanesLhkjK1FJkfhKJ6z62gLvQPOABPziqcxpygv+FxGhjp9SXQoHMVzRjulBli+fHm8y5EkpXAUz3mtNtSE59zKoe0bGxsb412OJCmFo3hK0+luDjc5M9dlpqexdsHMoc+HzUAnMhUKR/GU18Mafq+qKCInS98xSmwoHMVTXtoXOm3eUKmr1BI7CkfxjN5+35AugxcuO2s69OBk7iJTpXAUz9h2qJnefh8A82dOY97M6S5XJMlM4SiesWVv6JT6ghGOGgFqa2vjVY4kOYWjeILPb3lpfygcL6waORxFokXhKJ5QU99KW2cfAIXTslherqHJJLYUjuIJL+07GXx8wdJS0tPMiNuVlOgKtkSHwlE8YcveE8HHY51Sl5bqdFuiQ+EoCa/u1BmOneoEIDsjjXVjTIlQU1MTr7IkySkcJeH98c3jwcfnLC4hJzN91G0HBgbiUZKkAIWjJLzwcLxk5VwXK5FUonCUhHakqYNDJ52BJrIy0kZt3zgoJycnHmVJClA4SkLb/EboqPG8JbPJyx57oIklS5bEuiRJEQpHSVjWWja/2RBcvmxV2bivqa+vj2VJkkIUjpKwDjZ2UBe4Sp2Tmc7GpbPHfU1ra2usy5IUoXCUhBV+1HjBstIxr1KLRJvCURKStXbIVepLV+kqtcSXwlES0p76No63dgGQl50R8cC2VVVVsSxLUojCURLSE9uPBR9fsnIuWRmRnVJ3d3fHqiRJMQpHSTg9/T42h51SX7N2XsSvPXr0aCxKkhSkcJSE82LNCbp6nW6A5cXTWDlPw5NJ/CkcJeE8ubMu+PjqtfMwZuThyURiSeEoCeVkezfbApNoGeDK1eUTen1Z2fgNxUUioXCUhPLUzjps4PH6xbOYXZA7odcXFxdHvyhJSQpHSRh+a3liR9gp9ZrIL8QM2r17dzRLkhSmcJSE8VptU7Bt4/ScDC5ePsfliiSVKRwlYTy09Ujw8TVr55Ot7oLiIoWjJIQTbV28vD80idYN5y6Y1Pvk5+dHqyRJcQpHSQiPvHY0eCHm3MWzKJ85bVLvs2DB5EJVZDiFo7iub8DHY2HdBW/YMPmAO3LkyPgbiURA4Siue+7N47R39QEwuyCX85dOfnrVjo6OaJUlKU7hKK6y1vLbVw4Hl68/p4L0NPWIEfcpHMVVOw6fYv/xdsCZQOu69fNdrkjEoXAUV/1qy8Hg42vWzqNwWvaU3q+6unqqJYkACkdxUe2J07xW2wRAmoF3X7B4yu/Z0tIy5fcQAYWjuOg3L4WOGi9ePpfy4sk13wnX0NAw/kYiEVA4iisa27p4ZncoyP7koqkfNYpEk8JRXPHrLQfxW6fZ95oFxVSVFbpbkMgwMQ9HY8zHjDE/N8bUGGN8xhg7/qskmZ1s7+bR10PTGfzpxUui9t4VFRVRey9JbRlx2MengJnANmAaMPFxqCSp3Pv8AQb8zv+RK+cVce7iWVF779zciY3/KDKaeJxWXwYUWGsvAXbEYX+SwI63dvF4WFfBD122LKrTIOzduzdq7yWpLeZHjtbaw7Heh3jHL57bjy9w1Li6oph1C2e6XJHIyHRBRuKm7tQZntpZH1yO9lGjSDQpHCVuvv9UTfAK9bqFM1mzIPpHjUVFmsZVoiOi02pjTCFwxwTe99vW2il1VTDG3ArcumnTpqm8jSSIHYdPsWVfY3D5r65cHpP9lJdPbLZCkdFE+p1jIfD5Cbzvz4AphaO19h7gnttuu01NfzzOby33PPlmcPnK1eUsi1G7xgMHDrBkSfSaBknqiigcAxdV9OWQTMrTO+s5cOI0ANkZadxyeVXM9tXT0xOz95bUou8cJaa6egf44TM1weX3XLh4wnNRi7hB4Sgx9ZPN+zjV0QtA8fRs3ndRZUz3l5ERj34Nkgpi/ptkjHkHsDawuCSw7rOB5TZr7XdjXYO4Y//xdh545VBw+aNXrSA3K7a/csuXx+ZCj6SeePw3+x7gL4at+1Lg/gigcExCPr/l2w/vItDem/WLZnF5dVnM99vY2Ehp6eTnoBEZFPPTamvtLdZaM8ptYaz3L+54aOth9gWmP8hMT+P266vj0uC7qakp5vuQ1KDvHCXqGlo6+cEfQn2c/+wtS6IykK1IPCkcJap8fsvXHthBT78PgIpZ0zWQrXiSwlGi6r4tB3mzrhWA9DTDP960jqyM9Ljtv7IytlfDJXUoHCVqDjae5ifPhk6n3//WpSydW+BiRSKTp3CUqOjuG+Ar928LDmK7rKyAmy+O/1FcbW1t3PcpyUnhKFNmreVbD+/iaPMZwOkieOeN68hI16+XeJd+e2XKHnn96JCZBG+/fjUVs6a7WJHI1CkcZUr2NbTx34+HRtx527r5XL3WvWmCSkpKXNu3JBeFo0xa8+ke7vrVVvp9fgAWzc7ntretcrUm9Y6RaFE4yqT09A3w+V++GhxUYnpOBv/83nPJzoxfs52R1NTUjL+RSAQUjjJhfmv59wd2BMdoTDOGz773XMpnut8LZmBgwO0SJEkoHGVCrLXc/dgbvFBzIrju9uurWb8oenNPiyQChaNMyI+f3ceDW48El991/iKuP6fCxYqGysnJcbsESRIKR4nYfVsOcu/zB4LLl60q49arV7hY0dk0f4xEi8JRInLfloN876k9weXzlpRw541rSUuweafr6+vH30gkAgpHGde9zx8YEoyr5hfxmfeem5A9YFpbW90uQZKEJtyQUVlr+fGz+4acSldXFPOlmzeS43KTHZFYUzjKiAZ8fr758C6e3FEXXLdu4Uy+8KcbyInxPDAiiUC/5XKWzt5+vnzf67x+sDm4buOSkoRo5D2eqqrYzYktqUXhKEMcaz7DF3/9WnCEHYBr183jE9evTsjvGIfr7u4mMzPT7TIkCST+b7vEzZa9jXziBy8MCcYPXrKUT96wxhPBCHD06FG3S5AkoSNHod/n58fP7OXXWw4G12VnpHHHDWu4YnW5i5WJuEfhmOLqTp3hK/dvC/aTBigtyOVzf3IuSzTFgaQwhWOK8vktD7x6mB89s5fewEyB4Fx4ufPGdRTkZblY3eSVlZW5XYIkCYVjCjp8soNvPrSTPfVtwXWZ6Wn81ZXLuem8hZgE6/UyEcXFxW6XIElC4ZhCTnf38bPN+3lw6xH81gbXL5qdz503rqVyjvdPo3fv3k11dbXbZUgSUDimAJ/fz0OvHeWnm/fR0d0fXJ+RZnj/W5fyvosryfTI1WiReFE4JjGf3/LHNxv4+R/3c+xU55Dn1i6cyW3XrmLh7HyXqhNJbArHJOTz+3l2dwO/eP4AdcNCcW5RHh+9agUXVZV6+rvF0eTnK+wlOhSOSaSzt5+ndtTxu1cP09DSNeS5vKwMbn5LJe86fxFZGYndBXAqFixY4HYJkiQUjkngaPMZfv/qYZ7aWUd3n2/Ic3nZGdx03kLedf4iZuR6s3nORBw5ckQBKVGhcPSoju5+/vhmA0/vqueNY2ePYTg9J4N3nbeIm85fxPSc1Olr3NHR4XYJkiQUjh7S1TvA1tomNr/RwMv7Twbniw5XMWs679y4kKvWlJOrocVEJk1/PQnuVEcPrxw4yYt7G9l2sHnEQExPM5y/dDY3blzI2oUzk/JCi0i8KRwTTGdPPzuPtLDtUDPbDjUPGSFnuGVzC7hqTTmXriqjcFp2HKtMXGoALtGicHSRtZbG9m5q6tuoqW9jT10r+xrah/ReGW5x6Qwuqirl0pVzqShRs5XhWlpa1IVQokLhGCd+aznR2sWhkx0cOtnB/oY2ahraaOvsG/N1melprJhXyIXLSrmwag5zi/LiVLE3NTQ0KBwlKhSOUdbT7+N4SycNrV00tHRSd6qTQyc7ONLUQU+/b9zXG2DJ3ALWLZzJ+sWzWDW/WJNZibhA4TgB1lq6egdoOt1Dc0cPzae7aT7dw8nT3TS0dNHQ2smpjt4JvWdedgZVZYUsL3duK+cVMcOjw4WJJJOUDkdrLb0Dfjp7+uno7qetq5f2zj7auvpo7+yjvauXts4+2rv6aO3s5VRHz1mNrCeiIC+LRaX5LJo9g8Wl+VSVFTJ/1nTSdHU5aioqKtwuQZKEZ8LR57f0Dfjo7Q/cBvxhj537vn4/vQM+evp99PX76OodoLN3gM7efjp7nPvgup5+OnsH8PlHv/gxGelphtLCXMqKplFWnEdZ0TQWlOSzaHY+RdN1RTnWcnNz3S5BkoRnwvH6f3nE7RIAZ26Vkhm5zJqR49zynfu5RdMoK8pjdkGuZyajSkZ79+5Vcx6JCs+EY6xkpqcxLSeD6TmZFE7LpiAvi4K8LArzsiiclkVBXjYF05zlmTNyyM/JVCNrkRTgmXA0QFZmOjmZ6WRlpJGdmU52Rrpzn5lOdmBd+DZ5WRnk5WQyLTvDuQUfZzItJ4O87IykHqFGRCbPM+H46Gev1xGbjKuoqMjtEiRJeObLMQWjRKK8XPNsS3R4JhxFInHgwAG3S5AkoXCUpNLT0+N2CZIkFI4iIiNQOEpSycjwzDVGSXAKR0kqy5cvd7sESRIKR0kqjY2NbpcgSULhKEmlqanJ7RIkSSgcRURGENNwNMaUG2M+ZYzZbIw5bozpNMa8YYz5mjFmZiz3LSIyFbE+cnwHcBdwCvgacAfwYuB+mzFmToz3LymmsrLS7RIkScS63cNzwAJr7Ymwdd8zxrwMfA/4h8BNRCShxPTI0Vr7xrBgHPTLwL0G3pOoqq2tdbsESRJuXZCZF7hXuwsRSUhudSf4QuD+x5G+4LbbbotRKSKSwuzdd9894pBfEYWjMaYQ5yJKpL5trW0Z5b3+HvgT4B5r7R/G2OetwK2bNm2awG5FRKLDWDv+BFPGmIXAoQm871Jr7VljRxljPgLcAzwCvMta2z+B94wbY8xWa+0Gt+uIlWT+fMn82UCfL54iOnK01h7Gmalg0owxH8YJxieA9yRqMIqIQJwuyBhj/hKn6c5TwE3W2t547FdEZLJiHo7GmFuA7wPPADdaa70wGuk9bhcQY8n8+ZL5s4E+X9xE9J3jpN/cmHcCvwVOA/8IdA/b5Iy19ncxK0BEZJJi3ZTnHJyj00JG/h/hCPC7GNcgIjJhMT1yFBHxKg1ZNgHGmDRjzBZjjDXGPOR2PVOVLKMmBf5dPmmMqTHG9Bhjjhljvm6MmeZ2bVNljFlmjPmiMeYlY0yTMabDGLPdGPOZZPh8wxlj8owxhwJ/Y991sxaF48TcBqx2u4goSpZRk/4T+AbwJnA78GvgE8CDxhiv/45/GPgkUAt8EbgT2At8GXjRGJPrYm2x8EVglttFAGCt1S2CG05/8NPA3wEWeMjtmqLwmVYBc0ZY/5HAZ/wPt2uM8DP4gd8MW3974DO83+0ap/j5NgAFI6z/cuDzfdztGqP4Wc8BBsL+xr7rZj1e/181nr4LHAS+5XYh0WKTY9SkP8PpoPDNYeu/B3QBH4h3QdFkrd1qrW0f4Skv/RuNyxiTjvNv9hhwv8vlAO4NPOEpxpj3Au8ELrLW+oyZUmchL/DSqEkbcY4cXwlfaa3tMcZsDzyfjLz0bxSJTwLLgfe4XcggHTmOwxhTAHwb+B9r7Utu1xMnEx41yUVlQLMduddVPTDLGJMV55piKnCU9TmcU9BfuFzOlBljFuH8zn3ROl2VE0JKHDlOcVShf8f5T+RTUS4ratwYNSmB5AGjdUftCdumLz7lxMU3gQuAT1tr97pcSzT8N87ANt9wu5BwKRGOOI3QPz+B7X8GtBhj3gJ8FPigtbYtBnVFSyGT+HzDVwZGTfoa8DDw8ahUFntdwOxRnssJ2yYpGGO+hPNvc4+19itu1zNVxpgPANcAl9gEG4wmJcLRTn5Uof8CdgAvG2OWDHsuL7CuzVrbPMUSp2QKny/Iw6MmNQArjTHZI5xal+OccifFUaMx5i7gs8APgb92t5qpM8Zk4xwtPgKcCPsbKw/cFwTWNbtycOL25ftEvgFtOE0Kxrq52twgSp/zLwEfTjDmuF3PBGsfbNLy1mHrc4BO4FG3a4zS5/x84HP+GEhzu54ofabCCP6+LPAPbtSXEkeOU/AhYKQv838NvAZ8FThrUF8v8eioSeF+CXwa5zvX58LWfxTnu8afu1BTVBljPofTWP+nwF9aa/3uVhQ1nTjfbw9XAtyN06znf4Gd8SxqkPpWT4IxxgIPW2tvcLuWqUiWUZOMMd/B+R7utzinaCtwesi8AFzh5TAxxvwNThvbo8A/4zRbCtdorX0y7oXFUNjMA/9lrXXtu28dOaa2ZBk16Q7gMHAr8HagGfgO8DkvB2PAYDvNCkZuWrUZSKpwTBQ6chQRGYEagYuIjEDhKCIyAoWjiMgIFI4iIiNQOIqIjEDhKCIyAoWjiMgIFI4iIiNQOIqIjEDhKCIygv8PYQaJ22Z8Rg0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 360x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pw=5\n",
    "ph=5\n",
    "\n",
    "z = np.linspace(-5, 5, 200)\n",
    "\n",
    "\n",
    "# ------ Heaviside\n",
    "#\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "fig.set_size_inches(pw,ph)\n",
    "ax.set_xlim(-5, 5)\n",
    "ax.set_ylim(-2, 2)\n",
    "ax.axhline(y=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.axvline(x=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.plot(0, 0, \"rx\", markersize=10)\n",
    "ax.plot(z, sign(z),                linewidth=2, linestyle='-',  color='steelblue', label=\"Heaviside\")\n",
    "ax.plot(z, derivative(np.sign, z),   label=\"dHeaviside/dx\")\n",
    "ax.plot(z, sign(z),                  label=\"Heaviside\")\n",
    "ax.set_title(\"Heaviside\")\n",
    "ooo.save_fig('Heaviside')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "# ----- Logit/Sigmoid\n",
    "#\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "fig.set_size_inches(pw,ph)\n",
    "ax.set_xlim(-5, 5)\n",
    "ax.set_ylim(-2, 2)\n",
    "ax.axhline(y=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.axvline(x=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.plot(z, sigmoid(z),             label=\"Sigmoid\")\n",
    "ax.plot(z, derivative(sigmoid, z), label=\"dSigmoid/dx\")\n",
    "ax.set_title(\"Logit\")\n",
    "ooo.save_fig('Logit')\n",
    "plt.show()\n",
    "\n",
    "# ----- Tanh\n",
    "#\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "fig.set_size_inches(pw,ph)\n",
    "ax.set_xlim(-5, 5)\n",
    "ax.set_ylim(-2, 2)\n",
    "ax.axhline(y=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.axvline(x=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.plot(z, tanh(z),             label=\"Tanh\")\n",
    "ax.plot(z, derivative(tanh, z), label=\"dTanh/dx\")\n",
    "ax.set_title(\"Tanh\")\n",
    "ooo.save_fig('Tanh')\n",
    "plt.show()\n",
    "\n",
    "# ----- Relu\n",
    "#\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "fig.set_size_inches(pw,ph)\n",
    "ax.set_xlim(-5, 5)\n",
    "ax.set_ylim(-2, 2)\n",
    "ax.axhline(y=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.axvline(x=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.plot(z, relu(z),             label=\"ReLU\")\n",
    "ax.plot(z, derivative(relu, z), label=\"dReLU/dx\")\n",
    "ax.set_title(\"ReLU\")\n",
    "ooo.save_fig('ReLU')\n",
    "plt.show()\n",
    "\n",
    "# ----- Leaky Relu\n",
    "#\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "fig.set_size_inches(pw,ph)\n",
    "ax.set_xlim(-5, 5)\n",
    "ax.set_ylim(-2, 2)\n",
    "ax.axhline(y=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.axvline(x=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.plot(z, leaky_relu(z),              label=\"Leaky ReLU\")\n",
    "ax.plot(z, derivative( leaky_relu, z), label=\"dLeakyReLU/dx\")\n",
    "ax.set_title(\"Leaky ReLU (α=0.05)\")\n",
    "ooo.save_fig('LeakyReLU')\n",
    "plt.show()\n",
    "\n",
    "# ----- Elu\n",
    "#\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "fig.set_size_inches(pw,ph)\n",
    "ax.set_xlim(-5, 5)\n",
    "ax.set_ylim(-2, 2)\n",
    "ax.axhline(y=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.axvline(x=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.plot(z, elu(z),              label=\"ReLU\")\n",
    "ax.plot(z, derivative( elu, z), label=\"dExpReLU/dx\")\n",
    "ax.set_title(\"ELU (α=1)\")\n",
    "ooo.save_fig('ELU')\n",
    "plt.show()\n",
    "\n",
    "# ----- Selu\n",
    "#\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "fig.set_size_inches(pw,ph)\n",
    "ax.set_xlim(-5, 5)\n",
    "ax.set_ylim(-2, 2)\n",
    "ax.axhline(y=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.axvline(x=0, linewidth=1, linestyle='--', color='lightgray')\n",
    "ax.plot(z, selu(z),              label=\"SeLU\")\n",
    "ax.plot(z, derivative( selu, z), label=\"dSeLU/dx\")\n",
    "ax.set_title(\"ELU (SELU)\")\n",
    "ooo.save_fig('SeLU')\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "<img width=\"80px\" src=\"../fidle/img/00-Fidle-logo-01.svg\"></img>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}