language_model.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "language_model.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/abarankab/tinkoff_notebooks/blob/master/language_model.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8o6FTmaHwlPH",
        "colab_type": "code",
        "outputId": "e6250c2c-aa0a-4c43-b16c-a0f0ead304e4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 55
        }
      },
      "source": [
        "# http://pytorch.org/\n",
        "from os.path import exists\n",
        "from wheel.pep425tags import get_abbr_impl, get_impl_ver, get_abi_tag\n",
        "platform = '{}{}-{}'.format(get_abbr_impl(), get_impl_ver(), get_abi_tag())\n",
        "cuda_output = !ldconfig -p|grep cudart.so|sed -e 's/.*\\.\\([0-9]*\\)\\.\\([0-9]*\\)$/cu\\1\\2/'\n",
        "accelerator = cuda_output[0] if exists('/dev/nvidia0') else 'cpu'\n",
        "\n",
        "!pip install -q http://download.pytorch.org/whl/{accelerator}/torch-0.4.1-{platform}-linux_x86_64.whl torchvision\n",
        "import torch"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "tcmalloc: large alloc 1073750016 bytes == 0x57902000 @  0x7f42439842a4 0x591a07 0x5b5d56 0x502e9a 0x506859 0x502209 0x502f3d 0x506859 0x504c28 0x502540 0x502f3d 0x506859 0x504c28 0x502540 0x502f3d 0x506859 0x504c28 0x502540 0x502f3d 0x507641 0x502209 0x502f3d 0x506859 0x504c28 0x502540 0x502f3d 0x507641 0x504c28 0x502540 0x502f3d 0x507641\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qiizRVVPwuKE",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import torch\n",
        "from torchvision import models, transforms\n",
        "import numpy as np\n",
        "from matplotlib import pyplot\n",
        "%matplotlib inline\n",
        "from PIL import Image, ImageFilter, ImageChops\n",
        "import numpy as np\n",
        "from matplotlib import animation\n",
        "from matplotlib.animation import FuncAnimation\n",
        "from IPython.display import HTML, display\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "from scipy import stats"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8YgfuhFLwvLI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from __future__ import print_function\n",
        "\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "import torch.optim as optim\n",
        "\n",
        "import time\n",
        "\n",
        "from PIL import Image\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "import torchvision.transforms as transforms\n",
        "import torchvision.models as models\n",
        "\n",
        "import copy\n",
        "import cv2"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uC2lScfIVKlr",
        "colab_type": "code",
        "outputId": "54a5c750-71b4-4029-d989-2ebd0376e276",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        }
      },
      "source": [
        "!apt-get install -y -qq software-properties-common python-software-properties module-init-tools\n",
        "!add-apt-repository -y ppa:alessandro-strada/ppa 2>&1 > /dev/null\n",
        "!apt-get update -qq 2>&1 > /dev/null\n",
        "!apt-get -y install -qq google-drive-ocamlfuse fuse\n",
        "!apt-get install unzip"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "E: Package 'python-software-properties' has no installation candidate\n",
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "unzip is already the newest version (6.0-21ubuntu1).\n",
            "The following package was automatically installed and is no longer required:\n",
            "  libnvidia-common-410\n",
            "Use 'apt autoremove' to remove it.\n",
            "0 upgraded, 0 newly installed, 0 to remove and 38 not upgraded.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9GeokEJiVLXd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from google.colab import auth\n",
        "auth.authenticate_user()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u8BxEYMZVMoi",
        "colab_type": "code",
        "outputId": "26c67ca3-85c5-4da7-c647-475ea57311f3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 107
        }
      },
      "source": [
        "from oauth2client.client import GoogleCredentials\n",
        "creds = GoogleCredentials.get_application_default()\n",
        "import getpass\n",
        "!google-drive-ocamlfuse -headless -id={creds.client_id} -secret={creds.client_secret} < /dev/null 2>&1 | grep URL\n",
        "vcode = getpass.getpass()\n",
        "!echo {vcode} | google-drive-ocamlfuse -headless -id={creds.client_id} -secret={creds.client_secret}"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Please, open the following URL in a web browser: https://accounts.google.com/o/oauth2/auth?client_id=32555940559.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive&response_type=code&access_type=offline&approval_prompt=force\n",
            "··········\n",
            "Please, open the following URL in a web browser: https://accounts.google.com/o/oauth2/auth?client_id=32555940559.apps.googleusercontent.com&redirect_uri=urn%3Aietf%3Awg%3Aoauth%3A2.0%3Aoob&scope=https%3A%2F%2Fwww.googleapis.com%2Fauth%2Fdrive&response_type=code&access_type=offline&approval_prompt=force\n",
            "Please enter the verification code: Access token retrieved correctly.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ROWSSSnvVN2L",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!mkdir -p my_drive\n",
        "!google-drive-ocamlfuse my_drive -o \"nonempty\""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fHgIUQPLw1-T",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xt5vLMpF2-VV",
        "colab_type": "code",
        "outputId": "259e0fa5-2648-46a8-ba0d-5c1248b58ac5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        }
      },
      "source": [
        "!wget https://github.com/fluentpython/example-code/raw/master/attic/sequences/war-and-peace.txt\n",
        "!mv ./war-and-peace.txt ./data.txt"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2018-12-08 18:00:07--  https://github.com/fluentpython/example-code/raw/master/attic/sequences/war-and-peace.txt\n",
            "Resolving github.com (github.com)... 192.30.253.113, 192.30.253.112\n",
            "Connecting to github.com (github.com)|192.30.253.113|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://raw.githubusercontent.com/fluentpython/example-code/master/attic/sequences/war-and-peace.txt [following]\n",
            "--2018-12-08 18:00:08--  https://raw.githubusercontent.com/fluentpython/example-code/master/attic/sequences/war-and-peace.txt\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.0.133, 151.101.64.133, 151.101.128.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.0.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 3291641 (3.1M) [text/plain]\n",
            "Saving to: ‘war-and-peace.txt’\n",
            "\n",
            "war-and-peace.txt   100%[===================>]   3.14M  --.-KB/s    in 0.1s    \n",
            "\n",
            "2018-12-08 18:00:09 (28.2 MB/s) - ‘war-and-peace.txt’ saved [3291641/3291641]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ASKxHSzZ2PM2",
        "colab_type": "code",
        "outputId": "eac56ed6-aff5-469a-eb65-65ab63a26d41",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        }
      },
      "source": [
        "file = open('data.txt', 'r')\n",
        "raw_data = file.read()\n",
        "print(raw_data[:100])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "﻿The Project Gutenberg EBook of War and Peace, by Leo Tolstoy\n",
            "\n",
            "This eBook is for the use of anyone a\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RFoF2Ny74srF",
        "colab_type": "code",
        "outputId": "9e769a40-6bc6-469c-948c-6605a9d9ac34",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1639
        }
      },
      "source": [
        "from_alpha = {}\n",
        "to_alpha = {}\n",
        "\n",
        "for char in raw_data:\n",
        "  if not from_alpha.get(char):\n",
        "    from_alpha[char] = len(from_alpha)\n",
        "    to_alpha[len(to_alpha)] = char\n",
        "    print(\"Encoded {} as {}\".format(char, str(from_alpha[char])))\n",
        "    \n",
        "raw_data = [from_alpha[char] for char in raw_data]\n",
        "print(raw_data[:1000])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Encoded ﻿ as 0\n",
            "Encoded T as 1\n",
            "Encoded h as 2\n",
            "Encoded e as 3\n",
            "Encoded   as 4\n",
            "Encoded P as 5\n",
            "Encoded r as 6\n",
            "Encoded o as 7\n",
            "Encoded j as 8\n",
            "Encoded c as 9\n",
            "Encoded t as 10\n",
            "Encoded G as 11\n",
            "Encoded u as 12\n",
            "Encoded n as 13\n",
            "Encoded b as 14\n",
            "Encoded g as 15\n",
            "Encoded E as 16\n",
            "Encoded B as 17\n",
            "Encoded k as 18\n",
            "Encoded f as 19\n",
            "Encoded W as 20\n",
            "Encoded a as 21\n",
            "Encoded d as 22\n",
            "Encoded , as 23\n",
            "Encoded y as 24\n",
            "Encoded L as 25\n",
            "Encoded l as 26\n",
            "Encoded s as 27\n",
            "Encoded \n",
            " as 28\n",
            "Encoded i as 29\n",
            "Encoded w as 30\n",
            "Encoded m as 31\n",
            "Encoded v as 32\n",
            "Encoded . as 33\n",
            "Encoded Y as 34\n",
            "Encoded p as 35\n",
            "Encoded - as 36\n",
            "Encoded : as 37\n",
            "Encoded A as 38\n",
            "Encoded M as 39\n",
            "Encoded D as 40\n",
            "Encoded J as 41\n",
            "Encoded 1 as 42\n",
            "Encoded 0 as 43\n",
            "Encoded 2 as 44\n",
            "Encoded 9 as 45\n",
            "Encoded [ as 46\n",
            "Encoded # as 47\n",
            "Encoded 6 as 48\n",
            "Encoded ] as 49\n",
            "Encoded U as 50\n",
            "Encoded 5 as 51\n",
            "Encoded 3 as 52\n",
            "Encoded * as 53\n",
            "Encoded S as 54\n",
            "Encoded R as 55\n",
            "Encoded O as 56\n",
            "Encoded F as 57\n",
            "Encoded H as 58\n",
            "Encoded I as 59\n",
            "Encoded C as 60\n",
            "Encoded N as 61\n",
            "Encoded K as 62\n",
            "Encoded V as 63\n",
            "Encoded / as 64\n",
            "Encoded 8 as 65\n",
            "Encoded X as 66\n",
            "Encoded 7 as 67\n",
            "Encoded \" as 68\n",
            "Encoded ' as 69\n",
            "Encoded ! as 70\n",
            "Encoded ? as 71\n",
            "Encoded ; as 72\n",
            "Encoded x as 73\n",
            "Encoded ( as 74\n",
            "Encoded ) as 75\n",
            "Encoded z as 76\n",
            "Encoded q as 77\n",
            "Encoded Q as 78\n",
            "Encoded ê as 79\n",
            "Encoded à as 80\n",
            "Encoded Z as 81\n",
            "Encoded 4 as 82\n",
            "Encoded é as 83\n",
            "Encoded ä as 84\n",
            "Encoded = as 85\n",
            "Encoded % as 86\n",
            "Encoded @ as 87\n",
            "Encoded $ as 88\n",
            "[0, 1, 2, 3, 4, 5, 6, 7, 8, 3, 9, 10, 4, 11, 12, 10, 3, 13, 14, 3, 6, 15, 4, 16, 17, 7, 7, 18, 4, 7, 19, 4, 20, 21, 6, 4, 21, 13, 22, 4, 5, 3, 21, 9, 3, 23, 4, 14, 24, 4, 25, 3, 7, 4, 1, 7, 26, 27, 10, 7, 24, 28, 28, 1, 2, 29, 27, 4, 3, 17, 7, 7, 18, 4, 29, 27, 4, 19, 7, 6, 4, 10, 2, 3, 4, 12, 27, 3, 4, 7, 19, 4, 21, 13, 24, 7, 13, 3, 4, 21, 13, 24, 30, 2, 3, 6, 3, 4, 21, 10, 4, 13, 7, 4, 9, 7, 27, 10, 4, 21, 13, 22, 4, 30, 29, 10, 2, 4, 21, 26, 31, 7, 27, 10, 28, 13, 7, 4, 6, 3, 27, 10, 6, 29, 9, 10, 29, 7, 13, 27, 4, 30, 2, 21, 10, 27, 7, 3, 32, 3, 6, 33, 4, 4, 34, 7, 12, 4, 31, 21, 24, 4, 9, 7, 35, 24, 4, 29, 10, 23, 4, 15, 29, 32, 3, 4, 29, 10, 4, 21, 30, 21, 24, 4, 7, 6, 4, 6, 3, 36, 12, 27, 3, 4, 29, 10, 28, 12, 13, 22, 3, 6, 4, 10, 2, 3, 4, 10, 3, 6, 31, 27, 4, 7, 19, 4, 10, 2, 3, 4, 5, 6, 7, 8, 3, 9, 10, 4, 11, 12, 10, 3, 13, 14, 3, 6, 15, 4, 25, 29, 9, 3, 13, 27, 3, 4, 29, 13, 9, 26, 12, 22, 3, 22, 4, 30, 29, 10, 2, 4, 10, 2, 29, 27, 28, 3, 17, 7, 7, 18, 4, 7, 6, 4, 7, 13, 26, 29, 13, 3, 4, 21, 10, 4, 30, 30, 30, 33, 15, 12, 10, 3, 13, 14, 3, 6, 15, 33, 7, 6, 15, 28, 28, 28, 1, 29, 10, 26, 3, 37, 4, 20, 21, 6, 4, 21, 13, 22, 4, 5, 3, 21, 9, 3, 28, 28, 38, 12, 10, 2, 7, 6, 37, 4, 25, 3, 7, 4, 1, 7, 26, 27, 10, 7, 24, 28, 28, 1, 6, 21, 13, 27, 26, 21, 10, 7, 6, 27, 37, 4, 25, 7, 12, 29, 27, 3, 4, 21, 13, 22, 4, 38, 24, 26, 31, 3, 6, 4, 39, 21, 12, 22, 3, 28, 28, 5, 7, 27, 10, 29, 13, 15, 4, 40, 21, 10, 3, 37, 4, 41, 21, 13, 12, 21, 6, 24, 4, 42, 43, 23, 4, 44, 43, 43, 45, 4, 46, 16, 17, 7, 7, 18, 4, 47, 44, 48, 43, 43, 49, 28, 28, 25, 21, 27, 10, 4, 50, 35, 22, 21, 10, 3, 22, 37, 4, 39, 21, 6, 9, 2, 4, 42, 51, 23, 4, 44, 43, 42, 52, 28, 28, 25, 21, 13, 15, 12, 21, 15, 3, 37, 4, 16, 13, 15, 26, 29, 27, 2, 28, 28, 28, 53, 53, 53, 4, 54, 1, 38, 55, 1, 4, 56, 57, 4, 1, 58, 59, 54, 4, 5, 55, 56, 41, 16, 60, 1, 4, 11, 50, 1, 16, 61, 17, 16, 55, 11, 4, 16, 17, 56, 56, 62, 4, 20, 38, 55, 4, 38, 61, 40, 4, 5, 16, 38, 60, 16, 4, 53, 53, 53, 28, 28, 38, 13, 4, 38, 13, 7, 13, 24, 31, 7, 12, 27, 4, 63, 7, 26, 12, 13, 10, 3, 3, 6, 23, 4, 21, 13, 22, 4, 40, 21, 32, 29, 22, 4, 20, 29, 22, 15, 3, 6, 28, 28, 28, 28, 28, 28, 20, 38, 55, 4, 38, 61, 40, 4, 5, 16, 38, 60, 16, 28, 28, 17, 24, 4, 25, 3, 7, 4, 1, 7, 26, 27, 10, 7, 24, 64, 1, 7, 26, 27, 10, 7, 29, 28, 28, 60, 56, 61, 1, 16, 61, 1, 54, 28, 28, 17, 56, 56, 62, 4, 56, 61, 16, 37, 4, 42, 65, 43, 51, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 59, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 59, 63, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 63, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 63, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 63, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 63, 59, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 59, 66, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 59, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 59, 63, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 63, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 63, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 63, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 63, 59, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 59, 66, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 66, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 66, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 66, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 66, 59, 59, 59, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 66, 59, 63, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 66, 63, 28, 28, 60, 58, 38, 5, 1, 16, 55, 4, 66, 66, 63, 59, 28, 28, 60, 58]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qX43DKEu8O2f",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "chunk_size = 70\n",
        "hidden_size = 300\n",
        "num_layers = 1\n",
        "ntoken = len(from_alpha)\n",
        "ninp = hidden_size\n",
        "batch_size = 64"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zXNrnuW-5hMf",
        "colab_type": "code",
        "outputId": "0e204f43-7223-4160-f6fa-cd87de01c457",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 90
        }
      },
      "source": [
        "data = [raw_data[i:i+chunk_size] for i in range(0, len(raw_data), chunk_size)][:-1]\n",
        "data = [data[i:i+batch_size] for i in range(0, len(data), batch_size)][:-1]\n",
        "                                                \n",
        "for chunk in data[0][:3]:\n",
        "  print(len(chunk), chunk)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "70 [0, 1, 2, 3, 4, 5, 6, 7, 8, 3, 9, 10, 4, 11, 12, 10, 3, 13, 14, 3, 6, 15, 4, 16, 17, 7, 7, 18, 4, 7, 19, 4, 20, 21, 6, 4, 21, 13, 22, 4, 5, 3, 21, 9, 3, 23, 4, 14, 24, 4, 25, 3, 7, 4, 1, 7, 26, 27, 10, 7, 24, 28, 28, 1, 2, 29, 27, 4, 3, 17]\n",
            "70 [7, 7, 18, 4, 29, 27, 4, 19, 7, 6, 4, 10, 2, 3, 4, 12, 27, 3, 4, 7, 19, 4, 21, 13, 24, 7, 13, 3, 4, 21, 13, 24, 30, 2, 3, 6, 3, 4, 21, 10, 4, 13, 7, 4, 9, 7, 27, 10, 4, 21, 13, 22, 4, 30, 29, 10, 2, 4, 21, 26, 31, 7, 27, 10, 28, 13, 7, 4, 6, 3]\n",
            "70 [27, 10, 6, 29, 9, 10, 29, 7, 13, 27, 4, 30, 2, 21, 10, 27, 7, 3, 32, 3, 6, 33, 4, 4, 34, 7, 12, 4, 31, 21, 24, 4, 9, 7, 35, 24, 4, 29, 10, 23, 4, 15, 29, 32, 3, 4, 29, 10, 4, 21, 30, 21, 24, 4, 7, 6, 4, 6, 3, 36, 12, 27, 3, 4, 29, 10, 28, 12, 13, 22]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rQNoMKPkALIn",
        "colab_type": "code",
        "outputId": "994192f1-55b2-49a0-c1cc-772037da9025",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "data = torch.Tensor(data).float().type(torch.LongTensor).to(device)\n",
        "print(data.shape)\n",
        "data = data.transpose(1, 2)\n",
        "print(data.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "torch.Size([720, 64, 70])\n",
            "torch.Size([720, 70, 64])\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Txh9-6VC6t4t",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class LM(nn.Module):\n",
        "  def __init__(self):\n",
        "    super().__init__()\n",
        "    self.encoder = nn.Embedding(ntoken, ninp)\n",
        "    self.rnn = nn.RNN(input_size=ninp, hidden_size=hidden_size)\n",
        "    self.decoder = nn.Linear(hidden_size, ntoken)\n",
        "    self.norm = nn.LayerNorm(ntoken)\n",
        "    self.init_weights()\n",
        "    \n",
        "    \n",
        "  def forward(self, input, hidden):\n",
        "    emb = self.encoder(input)\n",
        "    output, hidden = self.rnn(emb, hidden)\n",
        "    decoded = self.decoder(output.view(output.size(0) * output.size(1), output.size(2)))\n",
        "    decoded = self.norm(decoded)\n",
        "    return decoded.view(output.size(0), output.size(1), decoded.size(1)), hidden\n",
        "  \n",
        "  \n",
        "  def init_hidden(self, batch_size):\n",
        "    weight = next(self.parameters())\n",
        "    return weight.new_zeros(1, batch_size, hidden_size)\n",
        "  \n",
        "  def init_weights(self):\n",
        "    initrange = 0.1\n",
        "    self.encoder.weight.data.uniform_(-initrange, initrange)\n",
        "    self.decoder.bias.data.zero_()\n",
        "    self.decoder.weight.data.uniform_(-initrange, initrange)\n",
        "  \n",
        "  \n",
        "model = LM().train().to(device)\n",
        "criterion = nn.CrossEntropyLoss().to(device)\n",
        "optimizer = torch.optim.Adam(model.parameters(), lr=0.01)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IpEf_jp1AgO7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def train(debug=False):\n",
        "  first = True\n",
        "  model.train()\n",
        "  total_loss = .0\n",
        "  start = time.time()\n",
        "  hidden = model.init_hidden(batch_size)\n",
        "  history = []\n",
        "  \n",
        "  for i, batch in enumerate(data):\n",
        "    optimizer.zero_grad()\n",
        "    \n",
        "    hidden.detach_()\n",
        "    output, hidden = model(batch, hidden)\n",
        "    \n",
        "    loss = criterion(output.contiguous().view(-1, ntoken), batch.contiguous().view(-1))\n",
        "    loss.backward()\n",
        "    total_loss += loss.item()\n",
        "    history.append(loss.item())\n",
        "    \n",
        "    optimizer.step()\n",
        "    \n",
        "    if debug and i % 100 == 0:\n",
        "      print(total_loss / 100)\n",
        "      print(time.time() - start, 's')\n",
        "      total_loss = 0\n",
        "      start = time.time()\n",
        "      \n",
        "  return history"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RCM2TK51V9Mx",
        "colab_type": "code",
        "outputId": "9d828b1e-0be6-4ec5-ea69-6299cca79a05",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 263
        }
      },
      "source": [
        "!ls ./my_drive/"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            " aishutin-subm-9.h5\t        Screencastify\n",
            " brainstorm.odt\t\t       'SIS P.zip'\n",
            " cnn_part1.ipynb\t        traffic_signs_hakaton\n",
            "'Colab Notebooks'\t        vgg.h5\n",
            " convolutional_networks.ipynb  'Европа.18 века. Музыка.7z'\n",
            " cooking\t\t       'Консультация по сочинениям.odt'\n",
            " data\t\t\t       'Копия aishutin-subm-9.h5'\n",
            " gamenode.odt\t\t       'Мещанин STAGE_1_5 действия.docx'\n",
            " good2.jpg\t\t       'Мещанин STAGE_1_5 действия.docx.odt'\n",
            " good.jpg\t\t       'Мещанин STAGE_1_5 действия.odt'\n",
            " hackaton31aug\t\t       'Новый документ.odt'\n",
            " hackEducationCity\t       'Новый документ.odt (186fd346)'\n",
            " LM1\t\t\t       'ПЗ 2019.odt'\n",
            "'Map.io API.odt'\t       'Прикрутить frame requests.odt'\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dTU8B-0CKyVq",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "model = torch.load('my_drive/LM1/model.pt')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A6RyTI3VA8bA",
        "colab_type": "code",
        "outputId": "d687e7c5-6de6-433d-f639-4655621cae8f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 61380
        }
      },
      "source": [
        "for epoch in range(5000):\n",
        "  history = train(debug=True)\n",
        "  \n",
        "  if epoch % 5 == 0:\n",
        "    plt.plot(history)\n",
        "    plt.show()\n",
        "    print(sample('T'))\n",
        "    print(sample('m'))\n",
        "    print(sample('O'))\n",
        "    torch.save(model, './my_drive/LM1/model.pt')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.002982373237609863\n",
            "0.031273841857910156 s\n",
            "0.01244683716504369\n",
            "1.9045765399932861 s\n",
            "0.0005397929932223633\n",
            "1.7322139739990234 s\n",
            "0.0005962274302146398\n",
            "1.7228155136108398 s\n",
            "0.00044345391608658247\n",
            "1.7253530025482178 s\n",
            "0.0002668677346082404\n",
            "1.72403883934021 s\n",
            "0.00019595154721173457\n",
            "1.7300059795379639 s\n",
            "0.0002618234877445502\n",
            "1.726574420928955 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD4CAYAAAAXUaZHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e0084b400>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/torch/serialization.py:241: UserWarning: Couldn't retrieve source code for container of type LM. It won't be checked for correctness upon loading.\n",
            "  \"type \" + obj.__name__ + \". It won't be checked \"\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "0.00021037651225924492\n",
            "0.017345666885375977 s\n",
            "0.0003024727735464694\n",
            "1.735746145248413 s\n",
            "0.00011362054079654627\n",
            "1.736034870147705 s\n",
            "0.00013125612516887486\n",
            "1.7408075332641602 s\n",
            "0.00010333421676477883\n",
            "1.7351584434509277 s\n",
            "9.079445553652476e-05\n",
            "1.7272841930389404 s\n",
            "6.965905129618477e-05\n",
            "1.7391455173492432 s\n",
            "0.00011691734067426296\n",
            "1.7399797439575195 s\n",
            "9.183403104543685e-05\n",
            "0.017306804656982422 s\n",
            "0.0001156891202845145\n",
            "1.734057903289795 s\n",
            "5.6281751894857735e-05\n",
            "1.7366104125976562 s\n",
            "6.655535489699104e-05\n",
            "1.7354686260223389 s\n",
            "4.951178700139281e-05\n",
            "1.7339341640472412 s\n",
            "5.430178727692692e-05\n",
            "1.7392075061798096 s\n",
            "3.8040013168938455e-05\n",
            "1.7320139408111572 s\n",
            "7.031026489130454e-05\n",
            "1.7376911640167236 s\n",
            "6.095697171986103e-05\n",
            "0.016994953155517578 s\n",
            "6.184017845953349e-05\n",
            "1.7315149307250977 s\n",
            "3.3780645044316773e-05\n",
            "1.73472261428833 s\n",
            "4.229659634802374e-05\n",
            "1.7370293140411377 s\n",
            "2.893925346143078e-05\n",
            "1.7372665405273438 s\n",
            "3.7668550939997656e-05\n",
            "1.734055757522583 s\n",
            "2.355306487515918e-05\n",
            "1.731400728225708 s\n",
            "4.503388423472643e-05\n",
            "1.736649751663208 s\n",
            "5.103889852762222e-05\n",
            "0.016986846923828125 s\n",
            "3.3633225666562796e-05\n",
            "1.735943078994751 s\n",
            "2.0493117826845264e-05\n",
            "1.7346091270446777 s\n",
            "2.9661217122338713e-05\n",
            "1.737720012664795 s\n",
            "1.8318797865504168e-05\n",
            "1.73500394821167 s\n",
            "2.803344417770859e-05\n",
            "1.7340068817138672 s\n",
            "1.5455192715307932e-05\n",
            "1.7449951171875 s\n",
            "3.0402142756429383e-05\n",
            "1.735551118850708 s\n",
            "4.2959842830896376e-05\n",
            "0.017566442489624023 s\n",
            "2.557264169809059e-05\n",
            "1.7291667461395264 s\n",
            "1.3817448743793648e-05\n",
            "1.7289440631866455 s\n",
            "2.2902170439920155e-05\n",
            "1.737333059310913 s\n",
            "1.2393099868859281e-05\n",
            "1.738997220993042 s\n",
            "2.1749998850282282e-05\n",
            "1.7391436100006104 s\n",
            "1.0637477025738917e-05\n",
            "1.7377886772155762 s\n",
            "1.763932825269876e-05\n",
            "1.7366077899932861 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAD4CAYAAAAAczaOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nWwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e03519a20>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "3.633647691458464e-05\n",
            "0.026390552520751953 s\n",
            "1.9609068058343837e-05\n",
            "1.8704869747161865 s\n",
            "9.332231138614589e-06\n",
            "1.7275309562683105 s\n",
            "1.7278811747019062e-05\n",
            "1.7356414794921875 s\n",
            "8.71424485467287e-06\n",
            "1.7295572757720947 s\n",
            "1.58179074378495e-05\n",
            "1.7315540313720703 s\n",
            "7.3640559457999185e-06\n",
            "1.7294175624847412 s\n",
            "8.738518795325945e-06\n",
            "1.727665662765503 s\n",
            "3.0279394704848527e-05\n",
            "0.017789840698242188 s\n",
            "1.608515541647648e-05\n",
            "1.7248656749725342 s\n",
            "6.409979296222445e-06\n",
            "1.7398340702056885 s\n",
            "1.432507887329848e-05\n",
            "1.736940860748291 s\n",
            "5.346040679796715e-06\n",
            "1.7277700901031494 s\n",
            "1.1918270088244753e-05\n",
            "1.733569622039795 s\n",
            "4.855200668316684e-06\n",
            "1.7257907390594482 s\n",
            "5.03875637150486e-06\n",
            "1.7286310195922852 s\n",
            "1.4586884062737227e-05\n",
            "0.017441511154174805 s\n",
            "1.1466767095953401e-05\n",
            "1.72493314743042 s\n",
            "4.101934171103494e-06\n",
            "1.7306640148162842 s\n",
            "1.0418063895940577e-05\n",
            "1.7311170101165771 s\n",
            "3.445001582349505e-06\n",
            "1.728682518005371 s\n",
            "6.141307037523802e-06\n",
            "1.7314653396606445 s\n",
            "3.12434776333248e-06\n",
            "1.730048656463623 s\n",
            "3.1060139849614645e-06\n",
            "1.7295143604278564 s\n",
            "3.84911458240822e-06\n",
            "0.01843547821044922 s\n",
            "4.773723223934212e-06\n",
            "1.7176008224487305 s\n",
            "2.2855698955481785e-06\n",
            "1.733410120010376 s\n",
            "5.880584629949226e-06\n",
            "1.7246227264404297 s\n",
            "2.0051194178449807e-06\n",
            "1.7328417301177979 s\n",
            "2.285446441874228e-06\n",
            "1.7188639640808105 s\n",
            "1.6517000540261506e-06\n",
            "1.72621488571167 s\n",
            "1.8258839827467454e-06\n",
            "1.7276060581207275 s\n",
            "1.1006987188011408e-06\n",
            "0.017590045928955078 s\n",
            "1.8962451451898232e-06\n",
            "1.735841989517212 s\n",
            "1.3212199769441213e-06\n",
            "1.7279160022735596 s\n",
            "1.926145388324585e-06\n",
            "1.6893436908721924 s\n",
            "1.1733685198578315e-06\n",
            "1.6915006637573242 s\n",
            "1.2209830526899168e-06\n",
            "1.6924657821655273 s\n",
            "9.136072259252614e-07\n",
            "1.7293031215667725 s\n",
            "1.0485351049283054e-06\n",
            "1.7320375442504883 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAD4CAYAAAD2FnFTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e03775278>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "7.357991125900299e-07\n",
            "0.026331424713134766 s\n",
            "1.164021235808832e-06\n",
            "1.863328218460083 s\n",
            "7.99191848841474e-07\n",
            "1.722397804260254 s\n",
            "1.0336924776765954e-06\n",
            "1.7254443168640137 s\n",
            "7.20607383755123e-07\n",
            "1.7264666557312012 s\n",
            "7.394530936721821e-07\n",
            "1.7255682945251465 s\n",
            "5.65250005024609e-07\n",
            "1.7382457256317139 s\n",
            "6.459695930516318e-07\n",
            "1.7292444705963135 s\n",
            "4.905887908535078e-07\n",
            "0.01765727996826172 s\n",
            "7.383312521369589e-07\n",
            "1.7248363494873047 s\n",
            "4.801345724558814e-07\n",
            "1.7296762466430664 s\n",
            "6.594093767375853e-07\n",
            "1.727193832397461 s\n",
            "4.4881871673396746e-07\n",
            "1.7285645008087158 s\n",
            "4.610206369193293e-07\n",
            "1.7249493598937988 s\n",
            "3.5562259640187224e-07\n",
            "1.7276437282562256 s\n",
            "4.0212060369526626e-07\n",
            "1.720733642578125 s\n",
            "3.345076402183622e-07\n",
            "0.017220735549926758 s\n",
            "4.64392557262272e-07\n",
            "1.7187092304229736 s\n",
            "2.8754344967296673e-07\n",
            "1.7224242687225342 s\n",
            "4.193069698033014e-07\n",
            "1.729759693145752 s\n",
            "2.7639312421001706e-07\n",
            "1.7160661220550537 s\n",
            "2.8389053639443775e-07\n",
            "1.718165636062622 s\n",
            "2.209650635620619e-07\n",
            "1.7196002006530762 s\n",
            "2.647340295425238e-07\n",
            "1.7197456359863281 s\n",
            "2.2966094547882677e-07\n",
            "0.017353057861328125 s\n",
            "3.117769965399475e-07\n",
            "1.7193386554718018 s\n",
            "1.7854997125255068e-07\n",
            "1.7184932231903076 s\n",
            "2.6457863057771645e-07\n",
            "1.721724033355713 s\n",
            "1.6818089129344571e-07\n",
            "1.723332405090332 s\n",
            "1.7513973432414787e-07\n",
            "1.734710454940796 s\n",
            "1.3254795732109416e-07\n",
            "1.7203781604766846 s\n",
            "1.610666507190217e-07\n",
            "1.7258472442626953 s\n",
            "1.5997673472156748e-07\n",
            "0.016896963119506836 s\n",
            "1.897364847280869e-07\n",
            "1.71921968460083 s\n",
            "1.1602682768341311e-07\n",
            "1.729090690612793 s\n",
            "1.7880967902783596e-07\n",
            "1.723311424255371 s\n",
            "1.1879844251438953e-07\n",
            "1.7175495624542236 s\n",
            "1.192327060550724e-07\n",
            "1.7235794067382812 s\n",
            "9.495445677742965e-08\n",
            "1.725590705871582 s\n",
            "1.1683148958496758e-07\n",
            "1.7247002124786377 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAD4CAYAAAD7CAEUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/QQ10gAYAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e03793da0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.1451755199232139e-07\n",
            "0.026484012603759766 s\n",
            "1.3408277652615652e-07\n",
            "1.868983268737793 s\n",
            "8.595202622529995e-08\n",
            "1.7418861389160156 s\n",
            "1.3074704561688576e-07\n",
            "1.7334556579589844 s\n",
            "8.93260751055891e-08\n",
            "1.7331905364990234 s\n",
            "8.950276058072859e-08\n",
            "1.741248607635498 s\n",
            "7.339247641624524e-08\n",
            "1.734182596206665 s\n",
            "8.341031456637893e-08\n",
            "1.7429146766662598 s\n",
            "8.191381311917212e-08\n",
            "0.01707315444946289 s\n",
            "7.461224297955482e-08\n",
            "1.738037109375 s\n",
            "3.504114488350751e-08\n",
            "1.7368535995483398 s\n",
            "7.179379357680205e-08\n",
            "1.7369141578674316 s\n",
            "3.7763800078138845e-08\n",
            "1.7391612529754639 s\n",
            "3.8229993180038944e-08\n",
            "1.7384798526763916 s\n",
            "2.6268618649183394e-08\n",
            "1.7358050346374512 s\n",
            "3.546902085815873e-08\n",
            "1.7306413650512695 s\n",
            "5.670104656019248e-08\n",
            "0.018830537796020508 s\n",
            "3.980951660764731e-08\n",
            "1.7321672439575195 s\n",
            "1.8658382661129736e-08\n",
            "1.739086389541626 s\n",
            "4.130814782232761e-08\n",
            "1.7339837551116943 s\n",
            "2.1606683762165346e-08\n",
            "1.7318906784057617 s\n",
            "2.2434763005119152e-08\n",
            "1.734020709991455 s\n",
            "1.5431216935368753e-08\n",
            "1.7321746349334717 s\n",
            "2.2217631481247224e-08\n",
            "1.7288525104522705 s\n",
            "4.075680408277549e-08\n",
            "0.01743030548095703 s\n",
            "2.398448323948088e-08\n",
            "1.7330799102783203 s\n",
            "1.2031623466413066e-08\n",
            "1.7385072708129883 s\n",
            "2.670500947488108e-08\n",
            "1.737675666809082 s\n",
            "1.3772930497202296e-08\n",
            "1.7246012687683105 s\n",
            "1.39049121933299e-08\n",
            "1.730987787246704 s\n",
            "8.016824833423365e-09\n",
            "1.7327313423156738 s\n",
            "1.3334410783327755e-08\n",
            "1.7373714447021484 s\n",
            "2.9600091693282593e-08\n",
            "0.017709970474243164 s\n",
            "1.3093863362456658e-08\n",
            "1.7357494831085205 s\n",
            "5.266496215794447e-09\n",
            "1.7336187362670898 s\n",
            "1.7474804734352035e-08\n",
            "1.7375776767730713 s\n",
            "7.659196931686373e-09\n",
            "1.7374694347381592 s\n",
            "8.502177063218763e-09\n",
            "1.7360742092132568 s\n",
            "5.045107527856807e-09\n",
            "1.7328753471374512 s\n",
            "8.597970107826481e-09\n",
            "1.7324223518371582 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZMAAAD4CAYAAAApWAtMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nYUomIiIyYf8fc4VfYYd3Lh8AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e035291d0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "2.0320926523709205e-08\n",
            "0.02238297462463379 s\n",
            "7.214290788926103e-09\n",
            "1.7552189826965332 s\n",
            "2.4288893282764513e-09\n",
            "1.6853525638580322 s\n",
            "1.1382358252320923e-08\n",
            "1.680290937423706 s\n",
            "4.3277229422322704e-09\n",
            "1.6760849952697754 s\n",
            "5.040849983262152e-09\n",
            "1.6817076206207275 s\n",
            "2.316066242402659e-09\n",
            "1.695866346359253 s\n",
            "5.0557511768745125e-09\n",
            "1.71341872215271 s\n",
            "1.3568571830546716e-08\n",
            "0.01808309555053711 s\n",
            "4.3149505743467205e-09\n",
            "1.716578483581543 s\n",
            "1.5263046848623674e-09\n",
            "1.7139782905578613 s\n",
            "8.62564367654084e-09\n",
            "1.7209587097167969 s\n",
            "3.2122646775878396e-09\n",
            "1.7102079391479492 s\n",
            "3.821083497113076e-09\n",
            "1.7208008766174316 s\n",
            "1.6625438717388085e-09\n",
            "1.7119052410125732 s\n",
            "3.916876613607734e-09\n",
            "1.7121422290802002 s\n",
            "1.0543635653448291e-08\n",
            "0.017802715301513672 s\n",
            "3.5996948591354715e-09\n",
            "1.7089998722076416 s\n",
            "1.0899135244324398e-09\n",
            "1.724210262298584 s\n",
            "6.997159468502545e-09\n",
            "1.713104486465454 s\n",
            "2.8141907487677644e-09\n",
            "1.7082605361938477 s\n",
            "3.4506832538583332e-09\n",
            "1.7100863456726074 s\n",
            "1.3219459024660375e-09\n",
            "1.7189464569091797 s\n",
            "3.459198150423948e-09\n",
            "1.709334373474121 s\n",
            "8.549009180569556e-09\n",
            "0.017823219299316406 s\n",
            "3.744448972831105e-09\n",
            "1.7100307941436768 s\n",
            "9.345156967710544e-10\n",
            "1.7140228748321533 s\n",
            "6.049871415503283e-09\n",
            "1.71575927734375 s\n",
            "2.795032141011955e-09\n",
            "1.7115025520324707 s\n",
            "3.633754583898252e-09\n",
            "1.7121024131774902 s\n",
            "1.283628620896149e-09\n",
            "1.7169015407562256 s\n",
            "3.6827156629781753e-09\n",
            "1.7097020149230957 s\n",
            "7.763504754620953e-09\n",
            "0.017787694931030273 s\n",
            "5.277139774328976e-09\n",
            "1.7122080326080322 s\n",
            "8.451087285532566e-10\n",
            "1.710571527481079 s\n",
            "6.267002625182094e-09\n",
            "1.7117128372192383 s\n",
            "3.2250370038400257e-09\n",
            "1.7188160419464111 s\n",
            "4.798173917908155e-09\n",
            "1.727304220199585 s\n",
            "1.424125292970313e-09\n",
            "1.722801685333252 s\n",
            "4.693865821719934e-09\n",
            "1.7166686058044434 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAEDCAYAAAD3FPVyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e0084bc88>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "8.014695822566863e-09\n",
            "0.026140689849853516 s\n",
            "8.189252395096602e-09\n",
            "1.9133985042572021 s\n",
            "7.769891395559281e-10\n",
            "1.735276460647583 s\n",
            "7.0588929196313545e-09\n",
            "1.734086275100708 s\n",
            "1.248504449338772e-08\n",
            "1.7335584163665771 s\n",
            "5.877443830237805e-09\n",
            "1.7319386005401611 s\n",
            "1.6774450334322565e-09\n",
            "1.7318542003631592 s\n",
            "6.247843981066481e-09\n",
            "1.7334849834442139 s\n",
            "8.493661880493163e-09\n",
            "0.0179290771484375 s\n",
            "7.393104772684955e-09\n",
            "1.7379140853881836 s\n",
            "1.7860106484024474e-09\n",
            "1.74027419090271 s\n",
            "5.366546787649584e-09\n",
            "1.7365741729736328 s\n",
            "4.517180632324091e-09\n",
            "1.736217975616455 s\n",
            "6.017940422931023e-09\n",
            "1.738401174545288 s\n",
            "3.0504806311504317e-09\n",
            "1.7384107112884521 s\n",
            "6.63740304024385e-09\n",
            "1.7378501892089844 s\n",
            "0.014060883522033692\n",
            "0.017935991287231445 s\n",
            "0.09424751132901292\n",
            "1.7310044765472412 s\n",
            "0.0015240607917075977\n",
            "1.738823413848877 s\n",
            "0.001743647764524212\n",
            "1.738154411315918 s\n",
            "0.001266897581226658\n",
            "1.7301883697509766 s\n",
            "0.0005291628846316598\n",
            "1.733182668685913 s\n",
            "0.00034374454102362504\n",
            "1.7310385704040527 s\n",
            "0.0005841730886459118\n",
            "1.728417158126831 s\n",
            "0.0007730066776275635\n",
            "0.017848730087280273 s\n",
            "0.0007098296179901809\n",
            "1.7246067523956299 s\n",
            "0.00024290563844260758\n",
            "1.7320609092712402 s\n",
            "0.0004410216883843532\n",
            "1.7307116985321045 s\n",
            "0.0004251454715631553\n",
            "1.733656883239746 s\n",
            "0.00017523297854495467\n",
            "1.7375173568725586 s\n",
            "9.745241070049815e-05\n",
            "1.7299678325653076 s\n",
            "0.00023086222137862932\n",
            "1.7372899055480957 s\n",
            "0.0002455516904592514\n",
            "0.017383098602294922 s\n",
            "0.00020048024081916081\n",
            "1.7328712940216064 s\n",
            "6.170141026814236e-05\n",
            "1.7374489307403564 s\n",
            "0.0001727855375611398\n",
            "1.7395198345184326 s\n",
            "0.00014805203709329363\n",
            "1.73183012008667 s\n",
            "7.823906089470256e-05\n",
            "1.7366056442260742 s\n",
            "3.5123256202496124e-05\n",
            "1.7345051765441895 s\n",
            "8.177891386367264e-05\n",
            "1.734785556793213 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX0AAAD4CAYAAAAAczaOAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nmUvvAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e00584048>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "0.00010575577616691589\n",
            "0.02542853355407715 s\n",
            "0.00014432362011575605\n",
            "1.876213550567627 s\n",
            "4.526665474259062e-05\n",
            "1.7212779521942139 s\n",
            "0.00010277094928824226\n",
            "1.718297004699707 s\n",
            "8.039619715418666e-05\n",
            "1.7229175567626953 s\n",
            "5.442714237688051e-05\n",
            "1.7248058319091797 s\n",
            "2.293612168614345e-05\n",
            "1.7185778617858887 s\n",
            "5.3462940486497245e-05\n",
            "1.720716953277588 s\n",
            "9.702815674245358e-05\n",
            "0.017433881759643555 s\n",
            "0.00012137691648604232\n",
            "1.7215404510498047 s\n",
            "3.0227466304495465e-05\n",
            "1.7172200679779053 s\n",
            "5.961279399343766e-05\n",
            "1.7277474403381348 s\n",
            "4.527269779828202e-05\n",
            "1.7254981994628906 s\n",
            "4.3638878196361475e-05\n",
            "1.721226692199707 s\n",
            "1.5904921483524958e-05\n",
            "1.7344157695770264 s\n",
            "5.5962809001357526e-05\n",
            "1.7204029560089111 s\n",
            "7.602919824421405e-05\n",
            "0.016945838928222656 s\n",
            "4.364569224890147e-05\n",
            "1.7210197448730469 s\n",
            "1.207677699312626e-05\n",
            "1.716961145401001 s\n",
            "3.607254925100278e-05\n",
            "1.6876728534698486 s\n",
            "2.1006414581279387e-05\n",
            "1.6879923343658447 s\n",
            "2.75698265477331e-05\n",
            "1.6807401180267334 s\n",
            "9.102512690333242e-06\n",
            "1.7161741256713867 s\n",
            "3.907354970124288e-05\n",
            "1.7236335277557373 s\n",
            "5.570980254560709e-05\n",
            "0.0177457332611084 s\n",
            "1.8426632182126922e-05\n",
            "1.720245599746704 s\n",
            "7.095277305779746e-06\n",
            "1.7194483280181885 s\n",
            "2.5016721156134736e-05\n",
            "1.7199041843414307 s\n",
            "8.306279794396686e-06\n",
            "1.7242062091827393 s\n",
            "2.1350367551349335e-05\n",
            "1.7198264598846436 s\n",
            "5.652848074078065e-06\n",
            "1.7279236316680908 s\n",
            "2.1363264088449797e-05\n",
            "1.720649242401123 s\n",
            "3.429078031331301e-05\n",
            "0.01740407943725586 s\n",
            "1.4550650730598136e-05\n",
            "1.712956190109253 s\n",
            "4.688596081905416e-06\n",
            "1.7146542072296143 s\n",
            "1.9540271739515448e-05\n",
            "1.7238750457763672 s\n",
            "5.3388007995636145e-06\n",
            "1.7227270603179932 s\n",
            "1.685519755938003e-05\n",
            "1.7203195095062256 s\n",
            "4.242232839715143e-06\n",
            "1.7249882221221924 s\n",
            "1.7141393593647082e-05\n",
            "1.7231829166412354 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAD4CAYAAAAO9oqkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e004dd5c0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.4407207490876317e-05\n",
            "0.02612471580505371 s\n",
            "9.229807926658395e-06\n",
            "1.8782799243927002 s\n",
            "3.0198288868632518e-06\n",
            "1.7257208824157715 s\n",
            "1.6813081830377997e-05\n",
            "1.7359704971313477 s\n",
            "3.640811351033335e-06\n",
            "1.730332374572754 s\n",
            "1.0546393759796047e-05\n",
            "1.7303411960601807 s\n",
            "2.9037839351531147e-06\n",
            "1.7294392585754395 s\n",
            "3.718744462730683e-06\n",
            "1.727658987045288 s\n",
            "4.795885470230132e-06\n",
            "0.017060041427612305 s\n",
            "5.435293269329123e-06\n",
            "1.730485439300537 s\n",
            "1.9044386510813637e-06\n",
            "1.7285921573638916 s\n",
            "1.2490607888366867e-05\n",
            "1.7292084693908691 s\n",
            "2.2819531898221614e-06\n",
            "1.726855754852295 s\n",
            "3.99377414510127e-06\n",
            "1.7280988693237305 s\n",
            "1.7326378389270758e-06\n",
            "1.7291419506072998 s\n",
            "1.6859652691891824e-06\n",
            "1.7319865226745605 s\n",
            "2.2382353199645875e-06\n",
            "0.01729273796081543 s\n",
            "2.768382414615189e-06\n",
            "1.7277050018310547 s\n",
            "1.2007270498770594e-06\n",
            "1.7291882038116455 s\n",
            "8.224920659927192e-06\n",
            "1.7288494110107422 s\n",
            "1.4100883691980925e-06\n",
            "1.731666088104248 s\n",
            "1.6762954908244865e-06\n",
            "1.7315239906311035 s\n",
            "9.847006640484324e-07\n",
            "1.7296218872070312 s\n",
            "1.0997535852652618e-06\n",
            "1.7385618686676025 s\n",
            "1.6511561989318579e-06\n",
            "0.017249345779418945 s\n",
            "1.3005211923200477e-06\n",
            "1.7363440990447998 s\n",
            "7.67475788734373e-07\n",
            "1.7349143028259277 s\n",
            "3.573547028850044e-06\n",
            "1.7374026775360107 s\n",
            "9.001812782116758e-07\n",
            "1.7300770282745361 s\n",
            "7.286401745432158e-07\n",
            "1.7312085628509521 s\n",
            "5.622995732323943e-07\n",
            "1.733928918838501 s\n",
            "7.213396733618537e-07\n",
            "1.7310161590576172 s\n",
            "5.674319618265145e-07\n",
            "0.017498016357421875 s\n",
            "8.090202319976925e-07\n",
            "1.7297773361206055 s\n",
            "4.979882905331578e-07\n",
            "1.7332937717437744 s\n",
            "8.477866637690568e-07\n",
            "1.7418768405914307 s\n",
            "5.774540615277602e-07\n",
            "1.7361969947814941 s\n",
            "4.972911318645856e-07\n",
            "1.7379651069641113 s\n",
            "3.7818934188749155e-07\n",
            "1.7364130020141602 s\n",
            "4.875074530730217e-07\n",
            "1.724869966506958 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAD4CAYAAAD2FnFTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e0039db00>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "3.997981548309326e-07\n",
            "0.02647709846496582 s\n",
            "5.205741987879264e-07\n",
            "1.8616878986358643 s\n",
            "3.234403475005365e-07\n",
            "1.7192397117614746 s\n",
            "4.5162120244413017e-07\n",
            "1.7319154739379883 s\n",
            "3.7604144509373327e-07\n",
            "1.726801872253418 s\n",
            "3.306620884302447e-07\n",
            "1.726372241973877 s\n",
            "2.496072220736778e-07\n",
            "1.7244269847869873 s\n",
            "3.254062335145136e-07\n",
            "1.7368104457855225 s\n",
            "2.7173438866157084e-07\n",
            "0.01793503761291504 s\n",
            "3.720340986035353e-07\n",
            "1.7235147953033447 s\n",
            "2.1808913828635922e-07\n",
            "1.7273643016815186 s\n",
            "3.09748309916813e-07\n",
            "1.7281956672668457 s\n",
            "2.5477154068198617e-07\n",
            "1.7240405082702637 s\n",
            "2.2670733059726445e-07\n",
            "1.73002290725708 s\n",
            "1.7071196140250322e-07\n",
            "1.7211823463439941 s\n",
            "2.2328645030711413e-07\n",
            "1.7222356796264648 s\n",
            "1.9021757907466963e-07\n",
            "0.018049001693725586 s\n",
            "2.4772115992277576e-07\n",
            "1.7230603694915771 s\n",
            "1.508614849399237e-07\n",
            "1.7368783950805664 s\n",
            "2.2675523062787305e-07\n",
            "1.7284133434295654 s\n",
            "1.7886289526813926e-07\n",
            "1.7252869606018066 s\n",
            "1.6060897458203272e-07\n",
            "1.723447561264038 s\n",
            "1.198266235391543e-07\n",
            "1.7164342403411865 s\n",
            "1.580949345481031e-07\n",
            "1.726794958114624 s\n",
            "1.36145526994369e-07\n",
            "0.018726825714111328 s\n",
            "1.748715112626087e-07\n",
            "1.7228643894195557 s\n",
            "1.05589628560665e-07\n",
            "1.7264561653137207 s\n",
            "1.589687805392259e-07\n",
            "1.7358417510986328 s\n",
            "1.2563807732846044e-07\n",
            "1.72597074508667 s\n",
            "1.0971937843606838e-07\n",
            "1.7296411991119385 s\n",
            "8.219267613185366e-08\n",
            "1.703547716140747 s\n",
            "1.0973002243730435e-07\n",
            "1.684964895248413 s\n",
            "9.908420906867832e-08\n",
            "0.017836809158325195 s\n",
            "1.2278556791756045e-07\n",
            "1.6864368915557861 s\n",
            "7.041437314114773e-08\n",
            "1.693359136581421 s\n",
            "1.0589297424701272e-07\n",
            "1.695242166519165 s\n",
            "8.652465670166976e-08\n",
            "1.6852333545684814 s\n",
            "7.552972810742631e-08\n",
            "1.7244679927825928 s\n",
            "5.6941594408499444e-08\n",
            "1.7357556819915771 s\n",
            "7.839288052480242e-08\n",
            "1.736076831817627 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAD4CAYAAAD7CAEUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e0050b908>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "7.369049853878096e-08\n",
            "0.02558279037475586 s\n",
            "8.718456591338963e-08\n",
            "1.87229323387146 s\n",
            "4.9657055534169106e-08\n",
            "1.7195408344268799 s\n",
            "7.965309320567826e-08\n",
            "1.7190866470336914 s\n",
            "6.304681303248572e-08\n",
            "1.7245795726776123 s\n",
            "5.479582728007415e-08\n",
            "1.7231347560882568 s\n",
            "4.1895678926096025e-08\n",
            "1.7229344844818115 s\n",
            "5.733115308714787e-08\n",
            "1.7197980880737305 s\n",
            "5.620079264190281e-08\n",
            "0.017609834671020508 s\n",
            "6.378974275023097e-08\n",
            "1.7207627296447754 s\n",
            "3.4609011336783624e-08\n",
            "1.7185423374176025 s\n",
            "6.12331283988965e-08\n",
            "1.7240853309631348 s\n",
            "4.4841851325472245e-08\n",
            "1.720949411392212 s\n",
            "3.9077230846729094e-08\n",
            "1.7286779880523682 s\n",
            "2.9255236793090943e-08\n",
            "1.7218265533447266 s\n",
            "4.257261728923823e-08\n",
            "1.7214250564575195 s\n",
            "4.167641691310564e-08\n",
            "0.01715874671936035 s\n",
            "4.712598647316213e-08\n",
            "1.7173523902893066 s\n",
            "2.4416616986044914e-08\n",
            "1.7257325649261475 s\n",
            "4.157849717856266e-08\n",
            "1.7214021682739258 s\n",
            "3.3561672543314105e-08\n",
            "1.7263131141662598 s\n",
            "2.776299210083266e-08\n",
            "1.7209200859069824 s\n",
            "2.1357621506901127e-08\n",
            "1.720705509185791 s\n",
            "3.1684126100550714e-08\n",
            "1.717879056930542 s\n",
            "3.277191126471735e-08\n",
            "0.019397974014282227 s\n",
            "3.57095684755393e-08\n",
            "1.7253048419952393 s\n",
            "1.7945255530449345e-08\n",
            "1.722163200378418 s\n",
            "3.142442002612711e-08\n",
            "1.7193121910095215 s\n",
            "2.5489500434794365e-08\n",
            "1.7199475765228271 s\n",
            "2.11937087790659e-08\n",
            "1.7219953536987305 s\n",
            "1.6076224249594874e-08\n",
            "1.7294940948486328 s\n",
            "2.3916363616205415e-08\n",
            "1.7206196784973145 s\n",
            "2.7130756734550232e-08\n",
            "0.016920804977416992 s\n",
            "2.7135014328827367e-08\n",
            "1.7195172309875488 s\n",
            "1.2985297643819394e-08\n",
            "1.722954273223877 s\n",
            "2.5176576059493528e-08\n",
            "1.722503900527954 s\n",
            "1.8737145879299533e-08\n",
            "1.7205283641815186 s\n",
            "1.5905925265791153e-08\n",
            "1.7242765426635742 s\n",
            "1.1795333458852752e-08\n",
            "1.7256853580474854 s\n",
            "1.8236892402878624e-08\n",
            "1.7182364463806152 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZMAAAD4CAYAAAApWAtMAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nERkzJRMRERmz/w9QfX3Y1Z4b/gAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e0037b2e8>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "2.0635980035876855e-08\n",
            "0.022464752197265625 s\n",
            "2.0608305906222312e-08\n",
            "1.7825288772583008 s\n",
            "9.936945788435736e-09\n",
            "1.7302567958831787 s\n",
            "2.120222379442538e-08\n",
            "1.7343382835388184 s\n",
            "1.453288981378975e-08\n",
            "1.7374355792999268 s\n",
            "1.2998070175740395e-08\n",
            "1.7314934730529785 s\n",
            "9.35154308545627e-09\n",
            "1.731274127960205 s\n",
            "1.4656356429609828e-08\n",
            "1.745408058166504 s\n",
            "1.648919919716718e-08\n",
            "0.017724990844726562 s\n",
            "1.6559447475472667e-08\n",
            "1.736133337020874 s\n",
            "7.561275051637396e-09\n",
            "1.727729320526123 s\n",
            "1.504378658978567e-08\n",
            "1.7327148914337158 s\n",
            "1.2114644146743459e-08\n",
            "1.7286803722381592 s\n",
            "1.0779925891934993e-08\n",
            "1.7322866916656494 s\n",
            "7.797564867129125e-09\n",
            "1.728799819946289 s\n",
            "1.2319003031002751e-08\n",
            "1.7321958541870117 s\n",
            "1.3766543816018384e-08\n",
            "0.0169069766998291 s\n",
            "1.3996447985054061e-08\n",
            "1.7365350723266602 s\n",
            "6.258487778021405e-09\n",
            "1.734147310256958 s\n",
            "1.2521233004880728e-08\n",
            "1.7304515838623047 s\n",
            "9.919916075795676e-09\n",
            "1.73207688331604 s\n",
            "8.942825501234708e-09\n",
            "1.7270820140838623 s\n",
            "6.177595804901514e-09\n",
            "1.7337934970855713 s\n",
            "1.0120017226444845e-08\n",
            "1.7338008880615234 s\n",
            "1.1625033948803321e-08\n",
            "0.017178773880004883 s\n",
            "1.0709677363829328e-08\n",
            "1.731149435043335 s\n",
            "5.021691405482365e-09\n",
            "1.7350878715515137 s\n",
            "1.0701162603821146e-08\n",
            "1.7349259853363037 s\n",
            "8.148806608376802e-09\n",
            "1.7300896644592285 s\n",
            "7.454838191200963e-09\n",
            "1.739530324935913 s\n",
            "4.889709680488963e-09\n",
            "1.7362301349639893 s\n",
            "8.474503288558033e-09\n",
            "1.739739179611206 s\n",
            "9.621892331779236e-09\n",
            "0.017904996871948242 s\n",
            "8.90663699570915e-09\n",
            "1.7335045337677002 s\n",
            "3.987125088561472e-09\n",
            "1.7312798500061035 s\n",
            "8.838517486786657e-09\n",
            "1.7394382953643799 s\n",
            "6.690621479621406e-09\n",
            "1.7368583679199219 s\n",
            "6.1477935175968665e-09\n",
            "1.7334926128387451 s\n",
            "3.961580222755501e-09\n",
            "1.7304027080535889 s\n",
            "6.973743511690111e-09\n",
            "1.739387035369873 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZMAAAD6CAYAAABkkKpHAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrvbyAgAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e00274da0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "7.959349090924661e-09\n",
            "0.019506216049194336 s\n",
            "6.935426208470874e-09\n",
            "1.7280166149139404 s\n",
            "3.212264683832844e-09\n",
            "1.7159509658813477 s\n",
            "6.58418459920096e-09\n",
            "1.7005126476287842 s\n",
            "5.547489478896495e-09\n",
            "1.6781940460205078 s\n",
            "5.123870761569727e-09\n",
            "1.67681884765625 s\n",
            "3.3229590207239924e-09\n",
            "1.6712875366210938 s\n",
            "5.9604646179822755e-09\n",
            "1.7145540714263916 s\n",
            "7.2504792569816345e-09\n",
            "0.017905235290527344 s\n",
            "6.04774273382791e-09\n",
            "1.7155494689941406 s\n",
            "2.522553773504077e-09\n",
            "1.7098093032836914 s\n",
            "7.169587322719551e-09\n",
            "1.7097241878509521 s\n",
            "4.3575253283467675e-09\n",
            "1.7159044742584229 s\n",
            "3.846628385956174e-09\n",
            "1.7246530055999756 s\n",
            "2.7183976264444353e-09\n",
            "1.7101616859436035 s\n",
            "4.896095946588241e-09\n",
            "1.7114572525024414 s\n",
            "5.907245963499008e-09\n",
            "0.01731562614440918 s\n",
            "4.823718827151602e-09\n",
            "1.7237615585327148 s\n",
            "2.0584890347841165e-09\n",
            "1.7132306098937988 s\n",
            "4.234058582353039e-09\n",
            "1.7133548259735107 s\n",
            "3.946679019428689e-09\n",
            "1.721848726272583 s\n",
            "3.6805868545985996e-09\n",
            "1.7128195762634277 s\n",
            "2.324581193091646e-09\n",
            "1.715273380279541 s\n",
            "4.317079404930757e-09\n",
            "1.7219500541687012 s\n",
            "5.53258814761648e-09\n",
            "0.018227815628051758 s\n",
            "4.031828508554991e-09\n",
            "1.7094576358795166 s\n",
            "1.679573788659905e-09\n",
            "1.7107148170471191 s\n",
            "4.272375855179922e-09\n",
            "1.7136080265045166 s\n",
            "3.3314739553147453e-09\n",
            "1.717376947402954 s\n",
            "3.1058278150697393e-09\n",
            "1.7152056694030762 s\n",
            "1.99462690947394e-09\n",
            "1.711059331893921 s\n",
            "3.816826009278573e-09\n",
            "1.7199625968933105 s\n",
            "4.8386198159278134e-09\n",
            "0.0182039737701416 s\n",
            "3.5677637985620512e-09\n",
            "1.7117047309875488 s\n",
            "1.4858586756816283e-09\n",
            "1.716951608657837 s\n",
            "3.929649159684079e-09\n",
            "1.7188549041748047 s\n",
            "2.8695379818144406e-09\n",
            "1.7207305431365967 s\n",
            "2.6843377676222247e-09\n",
            "1.7177507877349854 s\n",
            "1.7774957043747986e-09\n",
            "1.7130482196807861 s\n",
            "3.2271658401139547e-09\n",
            "1.7166414260864258 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAEDCAYAAAD3FPVyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ntIiIwxTSIiIOU0iLiDhMIS0i4rD/Dw7rsTK0QmOmAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e001f7128>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "4.406486198149651e-09\n",
            "0.02647709846496582 s\n",
            "2.803547081292601e-09\n",
            "1.8849101066589355 s\n",
            "1.2325389336931281e-09\n",
            "1.728752851486206 s\n",
            "3.1398875584287554e-09\n",
            "1.7309825420379639 s\n",
            "2.503395123421015e-09\n",
            "1.735053539276123 s\n",
            "2.3522547479282173e-09\n",
            "1.7281475067138672 s\n",
            "1.5667507016758896e-09\n",
            "1.7302427291870117 s\n",
            "2.8035471145992918e-09\n",
            "1.7306036949157715 s\n",
            "3.955193790261547e-09\n",
            "0.017273902893066406 s\n",
            "2.5033951149555644e-09\n",
            "1.7301476001739502 s\n",
            "1.070754892251724e-09\n",
            "1.7329211235046387 s\n",
            "2.758843593853033e-09\n",
            "1.736962080001831 s\n",
            "2.2436891591870458e-09\n",
            "1.7386300563812256 s\n",
            "2.145767241112928e-09\n",
            "1.7355468273162842 s\n",
            "1.370906858172427e-09\n",
            "1.735752820968628 s\n",
            "2.454434147591833e-09\n",
            "1.7299904823303223 s\n",
            "3.6922949675499695e-09\n",
            "0.017805099487304688 s\n",
            "2.1031925032111156e-09\n",
            "1.743062973022461 s\n",
            "8.876834810267464e-10\n",
            "1.7399001121520996 s\n",
            "2.5310687119806106e-09\n",
            "1.7354164123535156 s\n",
            "1.905219940145919e-09\n",
            "1.7331933975219727 s\n",
            "1.9350222539571416e-09\n",
            "1.7281525135040283 s\n",
            "1.1154583787198468e-09\n",
            "1.733424425125122 s\n",
            "2.179827074677565e-09\n",
            "1.7380077838897705 s\n",
            "3.3783061326175812e-09\n",
            "0.01766681671142578 s\n",
            "1.764723252112299e-09\n",
            "1.7361962795257568 s\n",
            "7.663454494599708e-10\n",
            "1.7419660091400146 s\n",
            "2.360769708470434e-09\n",
            "1.7386696338653564 s\n",
            "1.6455139782711737e-09\n",
            "1.7319304943084717 s\n",
            "1.6817024978132977e-09\n",
            "1.732299566268921 s\n",
            "1.0260514114734941e-09\n",
            "1.7320551872253418 s\n",
            "1.8967049834894835e-09\n",
            "1.7366836071014404 s\n",
            "3.0409012197196716e-09\n",
            "0.017321109771728516 s\n",
            "1.4922448839105317e-09\n",
            "1.7340216636657715 s\n",
            "7.280281758004215e-10\n",
            "1.7349903583526611 s\n",
            "1.9754682506478717e-09\n",
            "1.7368392944335938 s\n",
            "1.5028885576306993e-09\n",
            "1.7309963703155518 s\n",
            "1.5241759337980555e-09\n",
            "1.7309961318969727 s\n",
            "9.238720156956592e-10\n",
            "1.7379777431488037 s\n",
            "1.8253923009248218e-09\n",
            "1.7284705638885498 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e002747f0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "2.8972115728720384e-09\n",
            "0.02619457244873047 s\n",
            "1.3751643290760284e-09\n",
            "1.8640658855438232 s\n",
            "6.364924697022101e-10\n",
            "1.7291591167449951 s\n",
            "1.8072980197125777e-09\n",
            "1.7244884967803955 s\n",
            "1.3666493710318138e-09\n",
            "1.7247042655944824 s\n",
            "1.3677137446210796e-09\n",
            "1.7258777618408203 s\n",
            "8.408512584823225e-10\n",
            "1.7393362522125244 s\n",
            "1.5060816606349281e-09\n",
            "1.725151777267456 s\n",
            "2.706689485876268e-09\n",
            "0.017565011978149414 s\n",
            "1.3325895913129938e-09\n",
            "1.7270774841308594 s\n",
            "5.641153992541614e-10\n",
            "1.727616786956787 s\n",
            "1.6497714555585574e-09\n",
            "1.7250308990478516 s\n",
            "1.2942723121023292e-09\n",
            "1.7260992527008057 s\n",
            "1.2591481526880166e-09\n",
            "1.7249493598937988 s\n",
            "7.684741859526057e-10\n",
            "1.7310707569122314 s\n",
            "1.5007598312688497e-09\n",
            "1.7263152599334717 s\n",
            "2.6375056449978728e-09\n",
            "0.017581939697265625 s\n",
            "1.213380292769406e-09\n",
            "1.7218244075775146 s\n",
            "5.130257020591334e-10\n",
            "1.7209949493408203 s\n",
            "1.5390771126999603e-09\n",
            "1.6853680610656738 s\n",
            "1.1835779609170593e-09\n",
            "1.687788724899292 s\n",
            "1.1537756286483791e-09\n",
            "1.6874029636383057 s\n",
            "7.131270163274195e-10\n",
            "1.6874887943267822 s\n",
            "1.366649378942153e-09\n",
            "1.682325839996338 s\n",
            "2.4735928150221297e-09\n",
            "0.016901016235351562 s\n",
            "1.1090721659112735e-09\n",
            "1.6943914890289307 s\n",
            "4.896095903705877e-10\n",
            "1.7253522872924805 s\n",
            "1.4645712984040493e-09\n",
            "1.717026710510254 s\n",
            "1.1005571959321614e-09\n",
            "1.7259223461151123 s\n",
            "1.1271664174250518e-09\n",
            "1.7288954257965088 s\n",
            "6.322349951903838e-10\n",
            "1.7322807312011719 s\n",
            "1.2389251359545827e-09\n",
            "1.728339672088623 s\n",
            "2.4608203830212005e-09\n",
            "0.017678499221801758 s\n",
            "1.0366950875528858e-09\n",
            "1.7276034355163574 s\n",
            "4.5980726767758106e-10\n",
            "1.7293426990509033 s\n",
            "1.417739067116619e-09\n",
            "1.7249372005462646 s\n",
            "1.0090215037117378e-09\n",
            "1.7214758396148682 s\n",
            "1.0515962547974488e-09\n",
            "1.7230610847473145 s\n",
            "5.939177234737247e-10\n",
            "1.723677158355713 s\n",
            "1.2336032879922688e-09\n",
            "1.7199265956878662 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e00174438>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "2.3746065380692015e-09\n",
            "0.02598857879638672 s\n",
            "9.877341303199395e-10\n",
            "1.9015636444091797 s\n",
            "4.5129231809881707e-10\n",
            "1.7366247177124023 s\n",
            "1.3166240524220551e-09\n",
            "1.7420833110809326 s\n",
            "9.664467516545816e-10\n",
            "1.7339601516723633 s\n",
            "1.019665178958462e-09\n",
            "1.7395439147949219 s\n",
            "5.556004514795099e-10\n",
            "1.7397525310516357 s\n",
            "1.1005572025934996e-09\n",
            "1.7342743873596191 s\n",
            "2.3501259249769646e-09\n",
            "0.0171506404876709 s\n",
            "9.579318056840425e-10\n",
            "1.7345693111419678 s\n",
            "4.2787620641027147e-10\n",
            "1.7394962310791016 s\n",
            "1.231474542340294e-09\n",
            "1.7401132583618164 s\n",
            "9.302582182346697e-10\n",
            "1.7337400913238525 s\n",
            "9.558030576728437e-10\n",
            "1.7388889789581299 s\n",
            "5.619866627615266e-10\n",
            "1.7360143661499023 s\n",
            "1.13461699799422e-09\n",
            "1.7319483757019043 s\n",
            "2.29265012308133e-09\n",
            "0.01709580421447754 s\n",
            "9.089708517817652e-10\n",
            "1.7353789806365967 s\n",
            "4.065888351001412e-10\n",
            "1.7347230911254883 s\n",
            "1.2133802985980768e-09\n",
            "1.734238862991333 s\n",
            "8.663960993082753e-10\n",
            "1.7364768981933594 s\n",
            "9.398375226676859e-10\n",
            "1.7320477962493896 s\n",
            "5.534717134603184e-10\n",
            "1.73954439163208 s\n",
            "1.0217939090673145e-09\n",
            "1.732036828994751 s\n",
            "2.2245305331125566e-09\n",
            "0.01746964454650879 s\n",
            "8.461730961750736e-10\n",
            "1.7328691482543945 s\n",
            "4.172325221429851e-10\n",
            "1.7382876873016357 s\n",
            "1.1654836802599267e-09\n",
            "1.7403051853179932 s\n",
            "8.887478340768862e-10\n",
            "1.7367711067199707 s\n",
            "9.323869523680806e-10\n",
            "1.7321231365203857 s\n",
            "5.279268644464707e-10\n",
            "1.7362611293792725 s\n",
            "1.0494675167782575e-09\n",
            "1.734346628189087 s\n",
            "2.230916749113021e-09\n",
            "0.017453670501708984 s\n",
            "8.483018339167092e-10\n",
            "1.7319326400756836 s\n",
            "3.640140863736541e-10\n",
            "1.7385318279266357 s\n",
            "1.1271664264456138e-09\n",
            "1.7383739948272705 s\n",
            "8.44044351355766e-10\n",
            "1.73551344871521 s\n",
            "9.079064756944977e-10\n",
            "1.7449228763580322 s\n",
            "4.938670666865264e-10\n",
            "1.7352080345153809 s\n",
            "1.0303088771035362e-09\n",
            "1.7398991584777832 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e001c3a58>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "2.2000500621288667e-09\n",
            "0.025907516479492188 s\n",
            "8.73846687371449e-10\n",
            "1.8773479461669922 s\n",
            "3.5549913721122375e-10\n",
            "1.734494686126709 s\n",
            "1.0973641066669427e-09\n",
            "1.7372093200683594 s\n",
            "8.302075688026989e-10\n",
            "1.7299768924713135 s\n",
            "8.781041514749344e-10\n",
            "1.7367849349975586 s\n",
            "5.002532790787662e-10\n",
            "1.7340896129608154 s\n",
            "9.866697660287916e-10\n",
            "1.73386549949646 s\n",
            "2.176633842054798e-09\n",
            "0.017759323120117188 s\n",
            "8.131776686737257e-10\n",
            "1.7325968742370605 s\n",
            "3.363405010059495e-10\n",
            "1.7311902046203613 s\n",
            "1.055853730558276e-09\n",
            "1.7339529991149902 s\n",
            "8.408512419677549e-10\n",
            "1.7298145294189453 s\n",
            "8.749110307071372e-10\n",
            "1.7408366203308105 s\n",
            "4.938670662701927e-10\n",
            "1.7310187816619873 s\n",
            "9.451593924181267e-10\n",
            "1.7270557880401611 s\n",
            "2.1415097251065164e-09\n",
            "0.01770782470703125 s\n",
            "7.908259283539998e-10\n",
            "1.7273943424224854 s\n",
            "3.448554503071577e-10\n",
            "1.7323548793792725 s\n",
            "1.0760767112094616e-09\n",
            "1.7268540859222412 s\n",
            "8.238213601574618e-10\n",
            "1.7275538444519043 s\n",
            "8.429799935871784e-10\n",
            "1.7348809242248535 s\n",
            "4.789659047155226e-10\n",
            "1.7420222759246826 s\n",
            "9.483524747444515e-10\n",
            "1.734123706817627 s\n",
            "2.1207544875778693e-09\n",
            "0.017791032791137695 s\n",
            "8.035983491139209e-10\n",
            "1.7276554107666016 s\n",
            "3.299542900014885e-10\n",
            "1.7396881580352783 s\n",
            "1.0909778774825796e-09\n",
            "1.734541416168213 s\n",
            "7.972121331134563e-10\n",
            "1.7275378704071045 s\n",
            "8.280788170444974e-10\n",
            "1.736518144607544 s\n",
            "4.810946407918237e-10\n",
            "1.7088699340820312 s\n",
            "9.377088104611798e-10\n",
            "1.6879844665527344 s\n",
            "2.1473637445978967e-09\n",
            "0.016747236251831055 s\n",
            "7.610236019139904e-10\n",
            "1.6812992095947266 s\n",
            "3.405979755177757e-10\n",
            "1.7107346057891846 s\n",
            "1.0505318688569521e-09\n",
            "1.7246134281158447 s\n",
            "7.844397144352034e-10\n",
            "1.7172331809997559 s\n",
            "8.216926186688234e-10\n",
            "1.7182857990264893 s\n",
            "4.661934813188217e-10\n",
            "1.723222255706787 s\n",
            "9.994421988623881e-10\n",
            "1.7168402671813965 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n29v3l80ZigAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e0021ebe0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "2.125012059650544e-09\n",
            "0.02549600601196289 s\n",
            "7.801822382580426e-10\n",
            "1.8339052200317383 s\n",
            "3.405979757953315e-10\n",
            "1.711597204208374 s\n",
            "1.0175364328901538e-09\n",
            "1.7102789878845215 s\n",
            "7.674098052856682e-10\n",
            "1.7074229717254639 s\n",
            "8.142420365730984e-10\n",
            "1.7115767002105713 s\n",
            "4.768371675289984e-10\n",
            "1.7099921703338623 s\n",
            "9.88798490308973e-10\n",
            "1.7088651657104492 s\n",
            "2.1239476666323753e-09\n",
            "0.01840972900390625 s\n",
            "7.461224392490972e-10\n",
            "1.7122986316680908 s\n",
            "3.363404996181707e-10\n",
            "1.7127296924591064 s\n",
            "1.0452100486502137e-09\n",
            "1.7117464542388916 s\n",
            "7.49315535314432e-10\n",
            "1.7118957042694092 s\n",
            "8.057270915740045e-10\n",
            "1.7010350227355957 s\n",
            "4.768371654473302e-10\n",
            "1.7046279907226562 s\n",
            "9.23871997793313e-10\n",
            "1.7103512287139893 s\n",
            "2.109046448595109e-09\n",
            "0.01889777183532715 s\n",
            "7.354787590063694e-10\n",
            "1.7140467166900635 s\n",
            "3.4272671145529896e-10\n",
            "1.707780361175537 s\n",
            "1.0430812968920122e-09\n",
            "1.7172720432281494 s\n",
            "7.684741745728197e-10\n",
            "1.7067770957946777 s\n",
            "7.886971845061374e-10\n",
            "1.710036277770996 s\n",
            "4.693865864047187e-10\n",
            "1.7121570110321045 s\n",
            "9.228076273959385e-10\n",
            "1.7090184688568115 s\n",
            "2.1138362171768676e-09\n",
            "0.018657445907592773 s\n",
            "7.376074982745618e-10\n",
            "1.7067110538482666 s\n",
            "3.4166234411103777e-10\n",
            "1.7066676616668701 s\n",
            "1.0521284354858552e-09\n",
            "1.7090144157409668 s\n",
            "7.461224424409885e-10\n",
            "1.710977554321289 s\n",
            "7.780535107859699e-10\n",
            "1.7155613899230957 s\n",
            "4.757727976867354e-10\n",
            "1.7072584629058838 s\n",
            "9.015202527551391e-10\n",
            "1.7084059715270996 s\n",
            "2.0957418200850953e-09\n",
            "0.0187070369720459 s\n",
            "7.408005990583444e-10\n",
            "1.7021031379699707 s\n",
            "3.5124166242184175e-10\n",
            "1.7137937545776367 s\n",
            "1.0569181001229833e-09\n",
            "1.7156109809875488 s\n",
            "7.429293329141995e-10\n",
            "1.7155210971832275 s\n",
            "7.950833922493183e-10\n",
            "1.7098968029022217 s\n",
            "4.6193600507227206e-10\n",
            "1.7149293422698975 s\n",
            "9.37708783885216e-10\n",
            "1.704270362854004 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e00737048>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "2.119690236668248e-09\n",
            "0.02613353729248047 s\n",
            "7.429293405469828e-10\n",
            "1.890103816986084 s\n",
            "3.3314739543433e-10\n",
            "1.7216711044311523 s\n",
            "1.0159398940168263e-09\n",
            "1.720228672027588 s\n",
            "7.599592275614464e-10\n",
            "1.7263600826263428 s\n",
            "7.908259386235627e-10\n",
            "1.725365161895752 s\n",
            "4.683222186441239e-10\n",
            "1.7272169589996338 s\n",
            "9.382410003089259e-10\n",
            "1.7170543670654297 s\n",
            "2.016446387642645e-09\n",
            "0.017331838607788086 s\n",
            "7.365431321793014e-10\n",
            "1.72810959815979 s\n",
            "3.6294971972328225e-10\n",
            "1.72772216796875 s\n",
            "1.0042318288744355e-09\n",
            "1.7319326400756836 s\n",
            "7.450580723905587e-10\n",
            "1.738349437713623 s\n",
            "7.807144325466808e-10\n",
            "1.739288091659546 s\n",
            "4.5448542582149363e-10\n",
            "1.7407586574554443 s\n",
            "8.95666225075864e-10\n",
            "1.7409496307373047 s\n",
            "1.9158635211624642e-09\n",
            "0.017709970474243164 s\n",
            "7.035476943390018e-10\n",
            "1.7320516109466553 s\n",
            "3.6188535092185334e-10\n",
            "1.736525535583496 s\n",
            "9.467559173442775e-10\n",
            "1.743208646774292 s\n",
            "7.248350651634094e-10\n",
            "1.7382407188415527 s\n",
            "7.477189886001545e-10\n",
            "1.7415580749511719 s\n",
            "4.3639115973603816e-10\n",
            "1.7363770008087158 s\n",
            "8.057270833167208e-10\n",
            "1.7408819198608398 s\n",
            "1.737581811767086e-09\n",
            "0.01749706268310547 s\n",
            "6.801315863280699e-10\n",
            "1.7380223274230957 s\n",
            "3.672071942351085e-10\n",
            "1.7376070022583008 s\n",
            "8.781041651445553e-10\n",
            "1.7429118156433105 s\n",
            "6.992902164271175e-10\n",
            "1.741250991821289 s\n",
            "7.024833171415113e-10\n",
            "1.7334372997283936 s\n",
            "4.257474727625832e-10\n",
            "1.7488362789154053 s\n",
            "7.727316472111445e-10\n",
            "1.7372221946716309 s\n",
            "1.6359346943772834e-09\n",
            "0.017551422119140625 s\n",
            "6.450074207381418e-10\n",
            "1.7324731349945068 s\n",
            "3.5443477028329616e-10\n",
            "1.7360200881958008 s\n",
            "8.45108712108078e-10\n",
            "1.741774320602417 s\n",
            "6.524579852784651e-10\n",
            "1.7417223453521729 s\n",
            "6.545867266977146e-10\n",
            "1.7384545803070068 s\n",
            "3.853014626797879e-10\n",
            "1.7401111125946045 s\n",
            "7.344143890253285e-10\n",
            "1.7404615879058838 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e0012fac8>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.563025335826751e-09\n",
            "0.026927947998046875 s\n",
            "6.109476251986434e-10\n",
            "1.9005722999572754 s\n",
            "3.3208302913090295e-10\n",
            "1.7132320404052734 s\n",
            "7.998730624375616e-10\n",
            "1.7114362716674805 s\n",
            "6.024326673625957e-10\n",
            "1.721843957901001 s\n",
            "6.407499394955885e-10\n",
            "1.7209219932556152 s\n",
            "3.6827156310592633e-10\n",
            "1.6743721961975098 s\n",
            "7.392040268783262e-10\n",
            "1.6789824962615967 s\n",
            "1.505017337422032e-09\n",
            "0.016822099685668945 s\n",
            "5.779521898563456e-10\n",
            "1.6804149150848389 s\n",
            "3.214393411166139e-10\n",
            "1.6752405166625977 s\n",
            "7.764569579654657e-10\n",
            "1.6752734184265137 s\n",
            "5.758234544739338e-10\n",
            "1.687065839767456 s\n",
            "6.146728977890481e-10\n",
            "1.7123477458953857 s\n",
            "3.618853521708543e-10\n",
            "1.7148773670196533 s\n",
            "6.615051333092037e-10\n",
            "1.7135968208312988 s\n",
            "1.4682966309464973e-09\n",
            "0.017352819442749023 s\n",
            "5.87531506501815e-10\n",
            "1.7077736854553223 s\n",
            "3.076025480858169e-10\n",
            "1.7149684429168701 s\n",
            "7.604914089437421e-10\n",
            "1.7071032524108887 s\n",
            "5.53471715056264e-10\n",
            "1.7128047943115234 s\n",
            "5.93917725416615e-10\n",
            "1.7212886810302734 s\n",
            "3.5549913908472507e-10\n",
            "1.7149732112884521 s\n",
            "6.652304139487253e-10\n",
            "1.7129437923431396 s\n",
            "1.4345027921081055e-09\n",
            "0.01742720603942871 s\n",
            "5.428280309971445e-10\n",
            "1.718372106552124 s\n",
            "2.9057264948340046e-10\n",
            "1.7009813785552979 s\n",
            "7.663454439782447e-10\n",
            "1.704881191253662 s\n",
            "5.524073345974934e-10\n",
            "1.7045881748199463 s\n",
            "5.875315044895357e-10\n",
            "1.7147655487060547 s\n",
            "3.4272671534107956e-10\n",
            "1.699343204498291 s\n",
            "6.615051242886417e-10\n",
            "1.7251343727111816 s\n",
            "1.4259879321798507e-09\n",
            "0.01747274398803711 s\n",
            "5.385705490607018e-10\n",
            "1.7189598083496094 s\n",
            "2.8525080679464577e-10\n",
            "1.7111780643463135 s\n",
            "7.535730396635021e-10\n",
            "1.7094590663909912 s\n",
            "5.428280182295797e-10\n",
            "1.709559440612793 s\n",
            "5.465533046977722e-10\n",
            "1.7130489349365234 s\n",
            "3.3421176513781515e-10\n",
            "1.7143840789794922 s\n",
            "6.529901715873754e-10\n",
            "1.715116262435913 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nqZCLiHhOhVxExHMq5CIinvv/kDwyqMrUrwAAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e00277668>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.396185638213865e-09\n",
            "0.02567005157470703 s\n",
            "5.337808961503043e-10\n",
            "1.9130818843841553 s\n",
            "2.6396343291712477e-10\n",
            "1.7314093112945557 s\n",
            "7.562339361666392e-10\n",
            "1.739772081375122 s\n",
            "5.311199690466451e-10\n",
            "1.7340867519378662 s\n",
            "5.502786055294751e-10\n",
            "1.732471227645874 s\n",
            "3.267611839441464e-10\n",
            "1.7187576293945312 s\n",
            "6.141407149495848e-10\n",
            "1.7148778438568115 s\n",
            "1.3980482549413863e-09\n",
            "0.017910480499267578 s\n",
            "5.343130794061013e-10\n",
            "1.734123945236206 s\n",
            "2.6822090631872797e-10\n",
            "1.719635009765625 s\n",
            "7.306890872221805e-10\n",
            "1.7311558723449707 s\n",
            "5.199440935438337e-10\n",
            "1.735175609588623 s\n",
            "5.683728687005951e-10\n",
            "1.7369418144226074 s\n",
            "3.235680792051943e-10\n",
            "1.7394156455993652 s\n",
            "6.35428088618939e-10\n",
            "1.7369089126586914 s\n",
            "1.3706407742120064e-09\n",
            "0.017914533615112305 s\n",
            "5.066394954261755e-10\n",
            "1.7246143817901611 s\n",
            "2.6609216947914847e-10\n",
            "1.731917381286621 s\n",
            "7.408006151565783e-10\n",
            "1.7464394569396973 s\n",
            "5.194119123697049e-10\n",
            "1.7405786514282227 s\n",
            "5.502785940109111e-10\n",
            "1.7345149517059326 s\n",
            "3.1931060351375606e-10\n",
            "1.7373647689819336 s\n",
            "6.056257667585996e-10\n",
            "1.7404778003692627 s\n",
            "1.3727694181397964e-09\n",
            "0.018390893936157227 s\n",
            "5.343130791979345e-10\n",
            "1.7385549545288086 s\n",
            "2.597059571562976e-10\n",
            "1.7372996807098389 s\n",
            "7.269637904844251e-10\n",
            "1.7327678203582764 s\n",
            "4.933348811408945e-10\n",
            "1.7381105422973633 s\n",
            "5.641153995317172e-10\n",
            "1.7351574897766113 s\n",
            "3.1292439195418354e-10\n",
            "1.736649751663208 s\n",
            "6.327671722705653e-10\n",
            "1.7368295192718506 s\n",
            "1.371705167230175e-09\n",
            "0.01764822006225586 s\n",
            "5.199440984010595e-10\n",
            "1.7348260879516602 s\n",
            "2.575772196922177e-10\n",
            "1.7346217632293701 s\n",
            "7.434615168638858e-10\n",
            "1.7311749458312988 s\n",
            "4.975923508648839e-10\n",
            "1.730046272277832 s\n",
            "5.566648117460993e-10\n",
            "1.7377841472625732 s\n",
            "3.182462356837723e-10\n",
            "1.7266812324523926 s\n",
            "5.960464614929162e-10\n",
            "1.7137329578399658 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e003ff630>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.3602631554476829e-09\n",
            "0.0198822021484375 s\n",
            "5.343130737162083e-10\n",
            "1.750622034072876 s\n",
            "2.650278015797758e-10\n",
            "1.7180263996124268 s\n",
            "7.498477086476108e-10\n",
            "1.7194671630859375 s\n",
            "4.954636157600279e-10\n",
            "1.7250189781188965 s\n",
            "5.532056136098307e-10\n",
            "1.7255213260650635 s\n",
            "3.0760254912665096e-10\n",
            "1.7255325317382812 s\n",
            "6.112137027058928e-10\n",
            "1.7269034385681152 s\n",
            "1.3677137644663162e-09\n",
            "0.0170133113861084 s\n",
            "5.295234159485851e-10\n",
            "1.7242605686187744 s\n",
            "2.448047952546828e-10\n",
            "1.729842185974121 s\n",
            "7.314873689406864e-10\n",
            "1.7311670780181885 s\n",
            "5.30055599273771e-10\n",
            "1.7246193885803223 s\n",
            "5.561326234249098e-10\n",
            "1.7276129722595215 s\n",
            "3.0653817977011055e-10\n",
            "1.7278478145599365 s\n",
            "5.915228828978769e-10\n",
            "1.6848227977752686 s\n",
            "1.367181567957232e-09\n",
            "0.016901731491088867 s\n",
            "5.252659467103183e-10\n",
            "1.688971996307373 s\n",
            "2.575772195534398e-10\n",
            "1.6800386905670166 s\n",
            "7.171183941806492e-10\n",
            "1.7246012687683105 s\n",
            "5.103647764820307e-10\n",
            "1.7165007591247559 s\n",
            "5.68372864259703e-10\n",
            "1.7305421829223633 s\n",
            "2.980232307464581e-10\n",
            "1.7209129333496094 s\n",
            "6.093510552390713e-10\n",
            "1.7250444889068604 s\n",
            "1.3637223617024573e-09\n",
            "0.01731562614440918 s\n",
            "5.108969653583317e-10\n",
            "1.7281086444854736 s\n",
            "2.597059563930193e-10\n",
            "1.7239668369293213 s\n",
            "7.309551994932883e-10\n",
            "1.7360939979553223 s\n",
            "5.151544428538824e-10\n",
            "1.7293109893798828 s\n",
            "5.550682630889314e-10\n",
            "1.722926378250122 s\n",
            "3.0228070553584005e-10\n",
            "1.7280831336975098 s\n",
            "6.085527960025816e-10\n",
            "1.7204079627990723 s\n",
            "1.3682459609754005e-09\n",
            "0.01704692840576172 s\n",
            "5.210084680351557e-10\n",
            "1.7248375415802002 s\n",
            "2.479979017977474e-10\n",
            "1.7261264324188232 s\n",
            "7.378735925739343e-10\n",
            "1.7206716537475586 s\n",
            "5.167509915110502e-10\n",
            "1.733626365661621 s\n",
            "5.747590856031159e-10\n",
            "1.7300777435302734 s\n",
            "2.9483012531361653e-10\n",
            "1.7277607917785645 s\n",
            "6.322349947740503e-10\n",
            "1.7306292057037354 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAIABJREFUeJzt3Xl83PV95/GXpNFhyZItWeNDBmwD\n5gsGwk04Eo7AkoSwTdN4k27ZJmTh0RxkH7TdpUubpo+kSUuThnoDbLohScnSHGVzcCUQ3JAECCbB\nGDAO2B+D8S0fY93nHJrZP+Y38owYSWN5RjNf/H4+Hn54NOdbmpnPfObzu6pSqRQiIuKv6nIHEBGR\no6NCLiLiORVyERHPqZCLiHhOhVxExHMq5CIinguV64Gdc2cADwFrzOzuI7zt+4Bbs846FzjVzDqL\nGFFExAtV5ViP3DnXBPwEeA14+UgL+YT7Ohn4ipn9frHyiYj4pFwdeRS4FvifmTOcc6uAu4EUMADc\nYGa9BdzX54DPlyCjiIgXyjIjN7OEmY1MOPsu4ONmdhWwFrh5uvtxznUAi83sxRLEFBHxQtlm5Hlc\nCHzDOQdQD6x3zp0LfG3C9R4ys9uD0x8FvjN7EUVEKk8lFfJh4Eozmzi0v2iK27wP+MPSRRIRqXyV\ntPrhRuA9AM65P3TOXVXAbU40sz2ljSUiUtnKtdbKecAdwHIgDuwFPgP8A5AERoA/MrPuKe5jAfBr\nMzut5IFFRCpYWQq5iIgUTyWNVkREZAZmfWFnJDIw468Ara2N9PQMFzNOyfiSVTmLz5esyll8pcwa\nDjdXTXaZVx15KFRT7ggF8yWrchafL1mVs/jKlbWgQu6cO8M5t8059+kprnO7c+5XRUsmIiIFmbaQ\nB/tFuQt4YorrrAIuK2IuEREpUCEdeWa/KFPtWfAO0qsPiojILJt2YaeZJYBEsOn8mzjnbgCeBHYU\nM5iIiBTmqNZacc61AR8DrgaWFnKb1tbGo1ogEA43z/i2s82XrMpZfL5kVc7iK0fWo1398F1AGHia\n9I6uTnLOrTGzP5vsBkezak443EwkMjDj288mX7IqZ/H5klU5i6+UWaf6gDiqQm5mPwR+COCcWw58\ne6oiLiIixTdtIZ+4XxTn3GrgYWC7mT1Q2niHdfWN8uhzu7nq7A7q6/xZr1REpNQKWdi5AbiigOvt\nKOR6M/W8HeSHv3id49sbOfPEBaV6GBER73izZWcy2LlXMqmdfImIZPOmkGeojIuI5PKmkFcR7C9G\nlVxEJIc3hVxERPLzrpCn1JKLiOTwppBXTbonXhGRY5s3hXycGnIRkRzeFHI15CIi+XlTyDPUkIuI\n5PKnkGtILiKSlz+FPJBSSy4iksObQn64H1clFxHJ5k0h19JOEZH8/CnkAY1WRERyeVPI1ZCLiOTn\nTSEXEZH8vCnkVVr9UEQkL28KeYZG5CIiubwr5CIiksu7Qp7SaisiIjmmPfgygHPuDOAhYI2Z3T3h\nsiuB24ExwICbzCxZ7KAakYuI5DdtR+6cawLuAp6Y5Cr3AKvN7FKgGXhP8eIdpjouIpJfIaOVKHAt\n0DnJ5eeZ2Z7gdARYUIxgk9FkRUQk17SF3MwSZjYyxeX9AM65JcA1wKPFi5dFsxURkbwKmpFPxzm3\nEHgE+JSZdU113dbWRkKhmiN+jOa59en/mxsIh5tnEnPWKWdx+ZIT/MmqnMVXjqxHXcidcy3AY8Bn\nzGztdNfv6Rme0eMMDkYB6B8YIRIZmNF9zKZwuFk5i8iXnOBPVuUsvlJmneoDohirH95Bem2WnxXh\nvqanGbmISI5pO3Ln3Hmki/VyIO6cWw08DGwHHgc+Aqx0zt0U3OR7ZnZP0ZNqRC4ikte0hdzMNgBX\nTHGV+qKlKYAachGRXN5s2TnekKuSi4jk8KeQa/VDEZG8vCnkGSm15CIiObwr5CIiksu7Qq5N9EVE\ncnlTyDUhFxHJz5tCLiIi+flTyNWSi4jk5U8hD2hGLiKSy5tCXqWWXEQkL28KeYbWIxcRyeVNIR/f\nsFN1XEQkhzeFXERE8vOukKshFxHJ5U0h1z6zRETy86aQi4hIft4Ucq1+KCKSnzeFPCOlLYJERHL4\nU8jVkIuI5OVPIQ+oHxcRyTXtwZcBnHNnAA8Ba8zs7gmXXQ38PTAGPGpmXyh6SnTMThGRyUzbkTvn\nmoC7gCcmucqdwAeBS4FrnHOrihcvi0YrIiJ5FTJaiQLXAp0TL3DOnQh0m9luM0sCjwJXFTdiLjXk\nIiK5ph2tmFkCSDjn8l28GIhk/XwQOGmq+2ttbSQUqjmSjADMa+kDoHluPeFw8xHfvhyUs7h8yQn+\nZFXO4itH1oJm5Edg2gFIT8/wjO64v38UgIGBUSKRgRndx2wKh5uVs4h8yQn+ZFXO4itl1qk+II52\nrZVO0l15xlLyjGCKQZvoi4jkd1SF3Mx2AC3OueXOuRBwHbC2GMEmoxm5iEiuaUcrzrnzgDuA5UDc\nObcaeBjYbmYPAJ8Evh9c/X4z21qirCIikkchCzs3AFdMcflTwMVFzDQlbaEvIpLLmy07qzQkFxHJ\ny59CXu4AIiIVyptCnqG9H4qI5PKukIuISC7vCrn6cRGRXN4Uci3rFBHJz5tCPk4tuYhIDo8KuVpy\nEZF8PCrkaWrIRURyeVPIx2fkWv1QRCSHP4W83AFERCqUN4U8Q/24iEgufwq5WnIRkbz8KeQBjchF\nRHJ5U8ir1JKLiOTlTSEXEZH8/CnkashFRPLyp5AHUlpvRUQkhzeFfLwhVx0XEcnhTSEXEZH8pj34\nMoBzbg1wEel++BYzW5912c3AfwHGgOfN7E9LETSzib4achGRXNN25M65y4GVZnYxcCNwZ9ZlLcCt\nwDvN7B3AKufcRaWJqqWdIiL5FDJauQp4EMDMNgOtQQEHiAX/5jrnQkAj0F2KoBk6ZqeISK5CRiuL\ngQ1ZP0eC8/rNbNQ593ngDWAE+Dcz2zrVnbW2NhIK1Rxx0PldwwA0NdUTDjcf8e3LQTmLy5ec4E9W\n5Sy+cmQtaEY+wfiMI+jM/wo4BegHfuGcO8vMNk52456e4Rk8JPT1jQAwNBQlEhmY0X3MpnC4WTmL\nyJec4E9W5Sy+Umad6gOikNFKJ+kOPKMD2BecPg14w8wOmVkMeBo4b4Y5p6QJuYhIfoUU8rXAagDn\n3LlAp5llPnJ2AKc55+YEP58PvFbskNk0IhcRyTXtaMXM1jnnNjjn1gFJ4Gbn3A1An5k94Jz7R+CX\nzrkEsM7Mni5JUq1+KCKSV0EzcjO7bcJZG7Mu+zrw9WKGEhGRwnmzZef4bmw1WxERyeFNIdfSThGR\n/Pwp5AH14yIiubwp5GrIRUTy86aQj1NLLiKSw5tCro5cRCQ/bwp5hhpyEZFc/hTyKvXkIiL5+FPI\nA9qNrYhILm8KufpxEZH8/CnkquQiInl5U8gzNFkREcnlXSEXEZFc3hVyNeQiIrm8KeRVGpKLiOTl\nTSE/TD25iEg2Dwu5iIhk866Qa60VEZFc3hRyjchFRPLzp5Br204RkbwKOviyc24NcBHpJY23mNn6\nrMuOB74P1AEvmNknShE0Q6MVEZFc03bkzrnLgZVmdjFwI3DnhKvcAdxhZhcCY865E4ofE+1sRURk\nEoWMVq4CHgQws81Aq3OuBcA5Vw28E3g4uPxmM9tVoqwApLT6oYhIjkJGK4uBDVk/R4Lz+oEwMACs\ncc6dCzxtZn851Z21tjYSCtUccdCu4TgAjXPqCIebj/j25aCcxeVLTvAnq3IWXzmyFjQjn6Bqwuml\nwFeBHcBPnXPvM7OfTnbjnp7hGTwk9Aa3Gx6OEYkMzOg+ZlM43KycReRLTvAnq3IWXymzTvUBUcho\npZN0B57RAewLTh8CdprZNjMbA54ATp9hzqlpRi4iklchhXwtsBogGJ90mtkAgJklgDeccyuD654H\nWCmCZmhCLiKSa9rRipmtc85tcM6tA5LAzc65G4A+M3sA+FPg28GCz03AI6UIOr4euSq5iEiOgmbk\nZnbbhLM2Zl32OvCOYoYSEZHC+bNl53hDrpZcRCSbN4VcRETy866QaxN9EZFc3hRy7f1QRCQ/bwq5\niIjk500h125sRUTy86aQZ2hGLiKSy79CrtUPRURyeFfIRUQklzeFfHytFTXkIiI5vCnkIiKSn3eF\nXA25iEgubwp5lbYIEhHJy5tCPk4tuYhIDm8KufpxEfHZC1sjRHpHSnLf3hTyDK1HLiK+GRyJc/eP\nN/HwM9tLcv/+FHIdIEhEPBVPJAEYGytNBfOnkIuIeCoV7FukVOtseFPIx39/teQi4plkMlPIS1PJ\nvSnk2iG5iPgqGfxfXaI6VtDBl51za4CLSPfDt5jZ+jzXuR242MyuKGrCCdSQi4hvyj5acc5dDqw0\ns4uBG4E781xnFXBZ8eMdpn5cRHyV2f12OUcrVwEPApjZZqDVOdcy4Tp3AJ8pcrb8tENyEfFMZkZe\nXaKOtJDRymJgQ9bPkeC8fgDn3A3Ak8COQh6wtbWRUKjmiEICjAZDpoY5dYTDzUd8+3JQzuLyJSf4\nk1U5iy9f1uFgtcPGxtLUr4Jm5BOMf6Y459qAjwFXA0sLuXFPz/AMHhJ6eoYAGBmJEYkMzOg+ZlM4\n3KycReRLTvAnq3IW32RZu7vS9Ss6mpjx7zLVB0Aho5VO0h14RgewLzj9LiAMPA08AJwbLBgVEZFA\nstwLO4G1wGoA59y5QKeZDQCY2Q/NbJWZXQR8AHjBzP6sNFHTNCIXEd9k6lZ1iYbk0xZyM1sHbHDO\nrSO9xsrNzrkbnHMfKEmiSVTpEEEi4qlSd+QFzcjN7LYJZ23Mc50dwBVHHyk/rX4oIr6qhNUPK4pG\nKyLim0qYkVcGteQi4qnMlp2l2kTfn0IeUEMuIr7RaCWghlxEfPWNR14BSrdlpzeFfJxa8lmXSqV4\nfstBBoZj5Y4i4qWu/iigjly7sS2jl7d18bUHf8c/3f+mlZVE5AioIw/omJ2zL3PA2J0H/NhMWqRS\nHfMduY4QJCK+0+qHIiKeK9sm+pVCG+iLHNsGhmM8s2nf+MY1vsjOW1Wi9e9mshvb8tCyTpFj2p0/\neplte/uprqri4jMWT3+DCpE5qARoYec4zz6MRaRItu3tByDSN1LmJEcmld2Ra2GnWnIR8U8yefj0\nMT8jP0wtuYj4I2dGfqyPVrQ9kIj4KKnRypupHxcRn2Qv7DzmO/JxquRyjNobGWSXtq71TlYd125s\nRY51n/3Wc3zu3vXljiFHKKcjL9FjeFPIM7MlNeQi4pPULKwz7U0hFxHxUfbCzlKV9IK27HTOrQEu\nCnLcYmbrsy67ErgdGAMMuMnMknnvqAhm49NNRKRYsmfkpapf03bkzrnLgZVmdjFwI3DnhKvcA6w2\ns0uBZuA9RU+JVj8UET+lkqXvyAsZrVwFPAhgZpuBVudcS9bl55nZnuB0BFhQ3IgiIv7KGa2UqJIX\nMlpZDGzI+jkSnNcPYGb9AM65JcA1wGenurPW1kZCoZojD1pfC0B9fS3hcPMR374c3io5585tKPi6\npeTL3xNKm7WY9+3L3zQ7Z1NTfUXnnphteOxw9Z47tzTZZ7L3wzcNOZxzC4FHgE+ZWddUN+7pGZ7B\nQ0LfYPqYd6OjcSKRyl+XNhxufsvkHBwcHT9drt/Jl78nlD5rse7bl7/pxJxDQ9GKzZ3vb9rVNTR+\nemBgdMbZp/oAKGS00km6A8/oAPZlfgjGLI8Bf21ma2eUsBBa/VAE0AJ/32SvR16qp66QQr4WWA3g\nnDsX6DSz7I+UO4A1ZvazEuQTkQl8O7DCsS53Rl6a527a0YqZrXPObXDOrQOSwM3OuRuAPuBx4CPA\nSufcTcFNvmdm9xQ76OFjdupFLMe2ZBJqtAWINypmPXIzu23CWRuzTtcXL84UtPqhCKCO3DeprK1q\nyjlaqSh6Cc8+1Y3yy/5Knj1zlcqX88Fbrg2CKoUa8vLRwrXym405q5RGskI2CKoseg3POjWA5Zd9\nuDA9H36ZjQ2CvCnkpTqyhkxPHWD5JTVa8dZsfJvyppBn6CU8+7Rwrfyyi/eYCrlXdPDlPNQdzj7V\njfJLaUZ+mGe/fvbzddlZHSV5DO8Kucy+Y75wVIDsLvxYH6349g0xk/dDV57MnPqZ7BVlet4Uco3I\ny8ez981bUnbt9q2QFZtvv39mtFKqsQr4VMjLHeAY5lMHmEql3pLfILKfA4+ejpLw7enNvB5LWMf9\nKeQZvj2JbwUpj4aSX/i/z/PF+zZMf0XPaIOgw3z7/TPfIErZkZdmYFMS6snL5Ug+PFOpVFlXFd2x\nvzJ3b3q0kpqRj/NvtJLpyDVaKdiB7mH+/O5f88r27nJHecsotHAkxpJ84o4nue9nW0qc6NiTsx65\nZ4Ws2Hz79WejI/emkBf6YfbYb3fROxjjGz95tbSBjiGFvnEGhuPEE0l+9VJnaQMdg3LWWvGtkhWZ\nb99IEsERgmpLuMtKbwp5xnQLssYL/jH+Yi+mQgvHWPaWD2VwJOtaF2uBaDwxVpT7mU7OWivl/TOX\nnW8fZNF4+jVSG1IhlzIq9I0Ti5e3wiTGDj/+VFs/Do7EufFLv+ThX28/qsd7cWuEj3/lSdZvOXhU\n91OIlDrycb79+rGgkNfVHvmxigvlXSEv+DnUiudFU+gbJzZL3enkj3+4kMcTk3+ovNHZB8CDR1nI\nf75hDwBrn9t1VPdTCO1r5TDfPsgyDU59rTryI6/Lnj3ZlazQMUS5O/Ls4h2bopAX22y80lTID/Pt\n98+8LtWRA1VHsfphND5GV9/o9FeUvAp932S+QpZLPKcjnzxLserAbH7p08LOw3z79aMJzcjfZLon\nMd9766s/2Mit/7yO3sFoSTKNRBNlL2KlVGhHHq2gjnyq0Uo0VpznajaHd6mc/ZF7VsmKzLffXzPy\nbAW+axJB55L9VG/Z1QvAwZ6RIodKr6lx85qn+Mr9LxX9vitFwaOVrC64HG+2Qgv5aCxRnAcMWvJD\nfaPcvOZJntt8oDj3m0fuaKVkD1N2v3pxL197YNOU4xPfdsEwPiMvd0funFvjnHvWObfOOXfBhMuu\nds49F1z+2dLEPLxV1OBIfPy8VCpFz0CUf7r/Jb72wCYSY8k3dcbZT3r/UKwoWfoGo+OFwoIPidf3\n9B3VC2xvZLBo3xgKyRFPJPnRk9vYfWD6LSGnKhz7u4d56fVDJFOpnL99NDZGX/D79AxEeXpj53iu\nzP5Q8uUsJPvgSJydebbgnK6Qp1IpNr3RxZ6DQ5PedyqVYuvu3ik/CCbqH4oxEh3j/zz0ypTXy/e7\nJcaSbN7Zk/O3GRiOvem62YXtf/1gI1/67gtHPCtOpVIMjsSn/BtPddm+riHWrt/Nge7hI3rcqUTj\nY2zd3Tv+uPc9bjxvEfZ1Tf4c2e5e+gajROPp11i+v0Pmd81ek6lYBkfibN/Xz2gswQY7yMDw1HVl\nNmbkVdO9cZxzlwO3mtl1zrnTgH8xs4uzLn8VeDewF3gS+LiZTbo1TiQyMONq99UfvczG1w7xnref\nQHVVFY/+ZmfO5Y31IYajh7ut05a1smN/PyPRwwXm8rM7OLGjhTl1IV54LcKuA4OcvHQescQYHQua\nGByJU11dxc+f34M7YT79QzESY0lO7GihuqqKUKiap17qZEFLA9dfcwrfeOTV8Q+Xay44ns07e3jv\n20/g9JUL6dzfx3A0wbOvHODyszuoBkKhajram+gdjLHrwABz6kL0Dka573Ebz7igpZ6brlvFSGyM\nUHUV3/33rRwIvk1cfnYHZ6xoo6E+xOBwnKY5IfoGY+yJDLJ1dy/b96UL3CnHz+ekpS0sW9RMLJ6k\nq3+UQ30jXHDqQroHojz49PbxD7aTl87j9b19XHZWB/u6hsZ/7+6BKO+/dAXfWbuVnUHB/4+XLKe7\nf5Tq6iqefnnfeOa62uqchZ31tTVE42O0z2vgULB8oqkhxCfefwYb7OD4RkNnnNhGW3MDo7EEz21O\nr8b3tpMWcPX5x1FbU01dbQ2v7+3j5Te6WbZwLt39o/zm1XTn+/vvXMGpJ7TyzKZ9LGydw3ObD7L7\n4OB4husuWU5DXQ0j0QQbLMLQaJyB4cONAMBx4bnsiQyyZEEjZ53czpMv7R1/vbzjzCX0DcWoC1Wz\nfEkzOw8MsnLpPFJAqKaKHz/5Rs7rDeCi0xcxEhtjz4EBlrQ3cfHpi5nXVEdzYx1r/t9LdLQ38e4L\nT+CplzrpG4rx+t70GjTnrGynrbmBJ17YM/4aWLGkhebGOjoPDWG7e9/0fgjVVLOobQ4nLJxLeP4c\nVixpoa62hsb6EAPD6edvXlMdz76yn/6h2Pg3U4Bli5o5f9UiWptq+dWLnZy9sp3ammp++uwOlobn\ncqhvhCULmnjn25bwwtYIyxY182+/eH389tf/h1PYeWCAxvoQQyNxrjr/ODZYhJdeO8SZJy4g0jfC\naGyMkzpaOOPEBezcP0DvYJRYPElNdRXt8xtobqxj847u8ddC5nUIcPbJ7Vx9/nH84oW9dA9EufLs\nDu59bPIths9Z2c4rO7qZU59+P2R720kLOPeUMN9+bAvh+Q1cd8ly1j63m7NXthOqqeaRZ3Zw/qlh\nlixo4kDPMIMjcU5eOo/mObW0NNVTVQX/utZY0tbIactaefDX20mloL6uZnxMd80Fx7P74CC1tTVc\ncvoi4okkyxY301gf4jPf/C3R2Bj33HoFoaPYKCgcbp50LlFIIf9bYJeZfTP4eQtwoZn1O+dOBO4z\ns3cEl/0lMGhmd012f0dTyLcdGOTv7n1upjcXESmbf7ntXUd1+6kKeSE7zVoMZO9OLhKc1x/8H8m6\n7CBw0lR31traSCg0s68Y7e1z+dQH38au/QOctqKNU5e3EY2NMTQa59Rlbeza38+mbV2c6xZyqG+E\n9a8e4PJzlhKLJ4klxti2p5dQTTX9QzF6B6OsWtHGgnlzGEum6BuMMjAUI9I7gu3sYV/XEH90jaM2\nVE1LUz2bd3TTOxClvq6GC09fzK79A+w5OMCitkZi8SR9g1EO9gyzYctBTlvexqK2Rmpqqth7cJBQ\nqJqWpjpamxsYiSbY3zXEgnlzaGwI0dhQy8uvR6gL1XDtJcvZsa+fA93D1NfV0DsQJVRTTX3wlWxu\nYy29g1HWvbyPs08JMxJN0D5/Di2NdSxpb+L1Pb2kUtDSVEc0NkYylaKlqY5d+9PdYWIsSf9QjJrq\nKt7Y28eyJS0Mj8ZpbKhl/tx6GhtCLF/Swqvbu3ltTy9dvSOceXI7sfgY55+2iCXtTew+MEhNdRX7\nu4Y4YXEL9bU1tLU08Nyr+zn/tEW8vifd9S1f3MJZp4TZuquHB371OiuPn89obIyNr0VoqA9x3MK5\nzGuqZ25jLaGaanbu7+dDV53Cs5v2sb9raPxr8b5DQ5xyQivdfaNBRzfGlp09/N5lJxKLJxmNJRiN\nJjjpuPm0tTTw+G920FAXYiSaoLqqiqHROCPRBAtbG1m1oo1Lz+qgqqqKx9btYEVHC6cub+OXG3YT\njY2xbHELyztaCFVX88zLndQE+8bYfXCAjva5jI0lqa6pItIzQjQ+RmN9KP3N5KW9pFJwzinhdEfc\nEGLfoSEWtjVy0tL5HOob4WD3MC1NdYRqqonGx3jbye3EEknOOrmdnfsH2Lyjm9FYgsVtTbzz7KX8\n+Jev8UZnH8lkirmNdRzoHua4hXOJJ5LU1VZz5kntfOPBTZx+YjuXntVBY0OIgz3DbNvTx7a9fZzn\nFtI/HGNwOMapy9u46Iwl/PZ3+2lrqWdf1zDnn7aQex7YxJz6ECuWzmNxWxNjyXS3/NyrB0gmU8Fz\n3EwqlR4BXXzmEha0zOH5LQfoHUiPF5cunEtDXQ0HuoeJJ5IsbJ3Dq9u7aWmqY2FrI3sjgyxe0MiS\nBU0MjsZprK+laU4tsfgYB3uG2XNwkHNOCdN5aIjh0ThuWRttLQ38btshDvWmv4WefPx8orExuvtH\nefsZS5hTV8PmHd10Hhrilg+fw8BwjKdf2suh3vS3gKXhubQ211MbSv+tX9vdy2h0jEN9IySTKepq\nq+nqG+Xtpy9mJJrg0XU7cCe0snThXE5Y1MyKpfPYuquHh57cRmNDiIb6EOH5czh+UTMj0QQnLGrm\nzJPb6YwM0T6/ge/8bAu7Dwzwn685lW17eyEFi9oaeW13Lwd6hqmvrWHl8fMJh5tnVPcKUUhHfg/w\nUzN7KPj518B/NbOtzrlLSI9dPhBcdhNwopn91WT3dzQdeTjcTCTix97tfMmqnMXnS1blLL5SZp2q\nIy9kYNNJuvPO6AD2TXLZ0uA8ERGZJYUU8rXAagDn3LlAp5kNAJjZDqDFObfcORcCrguuLyIis2Ta\nGbmZrXPObXDOrQOSwM3OuRuAPjN7APgk8P3g6veb2daSpRURkTcp6AhBZnbbhLM2Zl32FHAxIiJS\nFv5s2SkiInmpkIuIeE6FXETEcyrkIiKem3aDIBERqWzqyEVEPKdCLiLiORVyERHPqZCLiHhOhVxE\nxHMq5CIinlMhFxHxXEE7zaoEzrk1wEVACrjFzNaXORLOuTOAh4A1Zna3c+544F+BGtL7bP9jM4s6\n564H/pT03iPvMbNvzXLOLwPvJP183w6sr7SczrlG4NvAIqAB+ALpnbNVVM4JmecAvwuyPlFpWZ1z\nVwA/ADJHhd4EfLnScgZZrwf+AkgAfwO8XKE5bwT+OOus84FLgX8mXZteNrNPBte9FfhPwfmfN7NH\nS5XLiw2CpjsAdJkyNQE/AV4j/eTd7Zy7F3jUzH7gnPt7YDdwH/ACcCEQI11ELzOz7lnKeSXpv921\nzrkFwIuki06l5fwwsMzMvuycWwb8O/BMpeWckPnvgGuA/w1cXmlZg0L+aTNbnXVeJb5GFwDPAucB\nc4HPA7WVljNP7suBDwGrgL8ws/XOue+R/gDaAvyQ9J5h5wFPA6eb2dhk93c0fBmtXAU8CGBmm4FW\n51xLeSMRBa4l94hIVwAPB6cfAa4G3g6sN7M+MxshXZwuncWcT5HuCgB6gaZKzGlm95vZl4Mfjwf2\nVGLODOfcqaTfwD8NzrqCCs06wRVUXs6rgZ+b2YCZ7TOzP6nQnBP9DfAlYEXWhCCT9UrgMTOLmVkE\n2En69VISvoxWpjoAdFmYWQLluDyxAAACkklEQVRIOOeyz24ys2hw+iCwhPwHqF4yKyGBoAMYCn68\nEXgUeHel5cwIDmByHOmjTf28UnMCdwCfBj4a/Fxxz31glXPuYaCNdKdbiTmXA41Bzlbgc1RmznHO\nuQtIf0tIAD15MnWRP+umUuTxpSOfaNKDkFaQyTKWJbtz7v2kC/mnJ1xUUTnN7BLg94DvTMhQMTmd\ncx8BnjWz7ZNcpVKyvka6eL+f9AfOt8ht3iolZxWwAPgD4AbgXir0uc9yE+llOhOVJasvhXyqA0BX\nksFgARgcPhB12Q9Q7Zx7N/AZ4L1m1leJOZ1z5wULizGzl0gXnIFKyxl4H/B+59xvSL+hP0sF/k3N\nbG8wskqZ2TZgP+mxZEXlBA4A68wsEeQcoHKf+4wrgHWku+4FWeeXJasvhXzSA0BXmJ8DHwxOfxD4\nGfBb4ALn3Hzn3FzSM72nZyuQc24e8I/AdVkLhSouJ3AZ8N+DzItIL/SqxJyY2YfN7AIzuwj4Jum1\nViouq3Pueufc/whOLya9RtC9lZaT9Pv7Xc656mDBZ8U+9wDOuQ5gMJh/x4Etzrl3BBf/QZD1F8D7\nnHN1wfWXAq+WKpMXa60AOOf+gfSbPQncbGYbp7lJqfOcR3pOuhyIA3uB60l/3WogvXDjY2YWd86t\nBm4lvRrSXWb23VnM+SekZ47ZB8X+KOkCVEk555D+6n88MIf0SOB50msqVEzOiZxznwN2AI9TYVmd\nc83A94D5QB3pv+mLlZYzyPpx0qM/gC+SXiOl4nIGWc8Dvmhm7w1+XgV8nXRj/Fsz+/Pg/P9Guiak\ngL82sydKlcmbQi4iIvn5MloREZFJqJCLiHhOhVxExHMq5CIinlMhFxHxnAq5iIjnVMhFRDz3/wEA\n+yOyu8EXeAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e03525128>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.3740999804667809e-09\n",
            "0.021664857864379883 s\n",
            "5.162188074225859e-10\n",
            "1.792726993560791 s\n",
            "2.554484827832493e-10\n",
            "1.7346277236938477 s\n",
            "7.527747337976454e-10\n",
            "1.7327184677124023 s\n",
            "5.231372020991775e-10\n",
            "1.7291054725646973 s\n",
            "5.595918305817404e-10\n",
            "1.7304000854492188 s\n",
            "2.980232306076802e-10\n",
            "1.734710931777954 s\n",
            "5.883297787140362e-10\n",
            "1.7371628284454346 s\n",
            "1.3745989235758316e-09\n",
            "0.017379045486450195 s\n",
            "5.273946773742822e-10\n",
            "1.733325719833374 s\n",
            "2.5864158842425764e-10\n",
            "1.7366359233856201 s\n",
            "7.487833493524665e-10\n",
            "1.7287547588348389 s\n",
            "5.316521495962734e-10\n",
            "1.7347757816314697 s\n",
            "5.739608121418938e-10\n",
            "1.739771842956543 s\n",
            "3.0440944299992003e-10\n",
            "1.7306609153747559 s\n",
            "6.205269361542198e-10\n",
            "1.7302582263946533 s\n",
            "1.382487084811146e-09\n",
            "0.017136812210083008 s\n",
            "5.348452566944495e-10\n",
            "1.7423737049102783 s\n",
            "2.607703257495597e-10\n",
            "1.7406220436096191 s\n",
            "7.279949242738893e-10\n",
            "1.7322227954864502 s\n",
            "5.353774409216916e-10\n",
            "1.7299399375915527 s\n",
            "5.657119475643846e-10\n",
            "1.7408485412597656 s\n",
            "3.012163367344112e-10\n",
            "1.734036922454834 s\n",
            "6.024326715259321e-10\n",
            "1.732842206954956 s\n",
            "1.3822572952904012e-09\n",
            "0.01684260368347168 s\n",
            "5.369739981830878e-10\n",
            "1.7294235229492188 s\n",
            "2.426760579293807e-10\n",
            "1.7298707962036133 s\n",
            "7.28543721670305e-10\n",
            "1.7384600639343262 s\n",
            "5.460211336544285e-10\n",
            "1.7321877479553223 s\n",
            "5.736947147200188e-10\n",
            "1.7334518432617188 s\n",
            "3.0653817921499905e-10\n",
            "1.7332992553710938 s\n",
            "6.42346499879487e-10\n",
            "1.7322428226470947 s\n",
            "1.3915789054408379e-09\n",
            "0.017234325408935547 s\n",
            "5.191458168907204e-10\n",
            "1.7305524349212646 s\n",
            "2.5438411328793097e-10\n",
            "1.7397971153259277 s\n",
            "7.434448862086995e-10\n",
            "1.7394609451293945 s\n",
            "5.385705451749212e-10\n",
            "1.7350199222564697 s\n",
            "5.763556275295567e-10\n",
            "1.7360920906066895 s\n",
            "3.065381808109446e-10\n",
            "1.7398474216461182 s\n",
            "6.213252045500494e-10\n",
            "1.7374191284179688 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e00791630>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.395620188304747e-09\n",
            "0.024575471878051758 s\n",
            "5.345791709299164e-10\n",
            "1.826470136642456 s\n",
            "2.437404268001986e-10\n",
            "1.7362143993377686 s\n",
            "7.469207157634328e-10\n",
            "1.7351982593536377 s\n",
            "5.353774400890243e-10\n",
            "1.7310247421264648 s\n",
            "5.843383991260831e-10\n",
            "1.7300467491149902 s\n",
            "3.060059965143136e-10\n",
            "1.7348253726959229 s\n",
            "6.420804063433927e-10\n",
            "1.732435703277588 s\n",
            "1.415078116906443e-09\n",
            "0.017353296279907227 s\n",
            "5.122274226304624e-10\n",
            "1.7274458408355713 s\n",
            "2.719461968114789e-10\n",
            "1.7321326732635498 s\n",
            "7.732638208912679e-10\n",
            "1.7365834712982178 s\n",
            "5.478837742517451e-10\n",
            "1.731787919998169 s\n",
            "5.859183271200718e-10\n",
            "1.7374036312103271 s\n",
            "3.0973128589684154e-10\n",
            "1.7284584045410156 s\n",
            "6.07488416723423e-10\n",
            "1.7297825813293457 s\n",
            "1.4291809691258095e-09\n",
            "0.017657041549682617 s\n",
            "5.409653782914581e-10\n",
            "1.727196455001831 s\n",
            "2.655599847661838e-10\n",
            "1.740285873413086 s\n",
            "7.724655552709958e-10\n",
            "1.7337052822113037 s\n",
            "5.579952744305672e-10\n",
            "1.7264316082000732 s\n",
            "5.83257396130632e-10\n",
            "1.7362391948699951 s\n",
            "3.256968171549968e-10\n",
            "1.7292869091033936 s\n",
            "6.346298286885599e-10\n",
            "1.7296056747436523 s\n",
            "1.4230609224341605e-09\n",
            "0.01737523078918457 s\n",
            "5.289912307152034e-10\n",
            "1.728437900543213 s\n",
            "2.671565373785212e-10\n",
            "1.7268357276916504 s\n",
            "7.522425523112664e-10\n",
            "1.7310521602630615 s\n",
            "5.505446973655404e-10\n",
            "1.7283987998962402 s\n",
            "6.01634394456485e-10\n",
            "1.7290289402008057 s\n",
            "3.1345657562631414e-10\n",
            "1.724973201751709 s\n",
            "6.271626123641183e-10\n",
            "1.7249560356140137 s\n",
            "1.4294471384346251e-09\n",
            "0.0177459716796875 s\n",
            "5.595918334960759e-10\n",
            "1.7199690341949463 s\n",
            "2.7034964385219686e-10\n",
            "1.7257261276245117 s\n",
            "7.445258693936085e-10\n",
            "1.7373549938201904 s\n",
            "5.590596483667776e-10\n",
            "1.7052106857299805 s\n",
            "5.949820897771518e-10\n",
            "1.6959145069122314 s\n",
            "3.177140513177523e-10\n",
            "1.6944682598114014 s\n",
            "6.524579844804923e-10\n",
            "1.6877858638763428 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e004f3198>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.4217305022157234e-09\n",
            "0.025099754333496094 s\n",
            "5.524073416404707e-10\n",
            "1.863837480545044 s\n",
            "2.650278016491647e-10\n",
            "1.7145462036132812 s\n",
            "7.809805197683816e-10\n",
            "1.7239973545074463 s\n",
            "5.540038970977546e-10\n",
            "1.7225217819213867 s\n",
            "5.949820804096451e-10\n",
            "1.722949504852295 s\n",
            "3.4379108525273147e-10\n",
            "1.7221312522888184 s\n",
            "6.524579963806953e-10\n",
            "1.7214438915252686 s\n",
            "1.4004430681779922e-09\n",
            "0.01710224151611328 s\n",
            "5.364418106945656e-10\n",
            "1.713426113128662 s\n",
            "2.9536231020005353e-10\n",
            "1.7296383380889893 s\n",
            "7.756586816246025e-10\n",
            "1.7277402877807617 s\n",
            "5.391027293674688e-10\n",
            "1.7223138809204102 s\n",
            "5.835401312506705e-10\n",
            "1.7243165969848633 s\n",
            "3.3953360907557073e-10\n",
            "1.724886417388916 s\n",
            "6.423464875629503e-10\n",
            "1.7255825996398926 s\n",
            "1.298529781479374e-09\n",
            "0.017490625381469727 s\n",
            "5.188797305363812e-10\n",
            "1.720090627670288 s\n",
            "2.8471862267148704e-10\n",
            "1.7249438762664795 s\n",
            "7.269638181012228e-10\n",
            "1.7297847270965576 s\n",
            "5.369739944013907e-10\n",
            "1.7148678302764893 s\n",
            "5.50544703402378e-10\n",
            "1.7252039909362793 s\n",
            "3.262290007924329e-10\n",
            "1.7256786823272705 s\n",
            "5.712998921159063e-10\n",
            "1.7283329963684082 s\n",
            "1.217637759509671e-09\n",
            "0.017467021942138672 s\n",
            "5.0078546417337e-10\n",
            "1.720029354095459 s\n",
            "2.7780022698875584e-10\n",
            "1.7208008766174316 s\n",
            "7.141913832206526e-10\n",
            "1.7187330722808838 s\n",
            "4.962618891865556e-10\n",
            "1.7229526042938232 s\n",
            "5.297894998743114e-10\n",
            "1.7217111587524414 s\n",
            "3.0707036410143606e-10\n",
            "1.7197253704071045 s\n",
            "5.494803270722493e-10\n",
            "1.721984624862671 s\n",
            "1.1351491480127152e-09\n",
            "0.017688989639282227 s\n",
            "4.818929180000487e-10\n",
            "1.717024803161621 s\n",
            "2.559806678778531e-10\n",
            "1.726714849472046 s\n",
            "6.545867307916619e-10\n",
            "1.7250797748565674 s\n",
            "4.813607320727775e-10\n",
            "1.7197446823120117 s\n",
            "4.917383221447747e-10\n",
            "1.723292350769043 s\n",
            "2.852508061701453e-10\n",
            "1.7241442203521729 s\n",
            "5.127596061638151e-10\n",
            "1.7243192195892334 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niOf+P7eKxLQInX6NAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e007a4860>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "1.0816646778266658e-09\n",
            "0.0203094482421875 s\n",
            "4.590089911632456e-10\n",
            "1.762723445892334 s\n",
            "2.5172319399052734e-10\n",
            "1.7367222309112549 s\n",
            "6.050935826007464e-10\n",
            "1.7407867908477783 s\n",
            "4.443739183915274e-10\n",
            "1.733351230621338 s\n",
            "4.773693471071816e-10\n",
            "1.7381596565246582 s\n",
            "2.7088182991824585e-10\n",
            "1.740579605102539 s\n",
            "5.100986944991948e-10\n",
            "1.7357873916625977 s\n",
            "1.0180686160765618e-09\n",
            "0.017783403396606445 s\n",
            "4.494296771892503e-10\n",
            "1.7327723503112793 s\n",
            "2.4161169089736977e-10\n",
            "1.7360336780548096 s\n",
            "5.907246176245496e-10\n",
            "1.742981195449829 s\n",
            "4.3239977352144134e-10\n",
            "1.734607458114624 s\n",
            "4.651291144949776e-10\n",
            "1.7384982109069824 s\n",
            "2.692852759875186e-10\n",
            "1.7375597953796387 s\n",
            "4.709831307250778e-10\n",
            "1.732299566268921 s\n",
            "9.91193331856266e-10\n",
            "0.017538070678710938 s\n",
            "4.44373924497754e-10\n",
            "1.732506513595581 s\n",
            "2.3628984806983724e-10\n",
            "1.7374475002288818 s\n",
            "5.659780331901399e-10\n",
            "1.7373900413513184 s\n",
            "4.143055065686241e-10\n",
            "1.7358109951019287 s\n",
            "4.5874289825165173e-10\n",
            "1.7386131286621094 s\n",
            "2.5172319343541584e-10\n",
            "1.7279131412506104 s\n",
            "4.744423351410454e-10\n",
            "1.732133150100708 s\n",
            "9.558030455991684e-10\n",
            "0.01738262176513672 s\n",
            "4.2015953487239966e-10\n",
            "1.7278594970703125 s\n",
            "2.2990363543473613e-10\n",
            "1.7284905910491943 s\n",
            "5.577291886660341e-10\n",
            "1.7396986484527588 s\n",
            "4.0446009940547924e-10\n",
            "1.7371079921722412 s\n",
            "4.507601279388207e-10\n",
            "1.7338643074035645 s\n",
            "2.448047966424616e-10\n",
            "1.729936122894287 s\n",
            "4.651291172358407e-10\n",
            "1.733137845993042 s\n",
            "9.45425426834845e-10\n",
            "0.01744365692138672 s\n",
            "4.222882756671487e-10\n",
            "1.7268986701965332 s\n",
            "2.1979213254974539e-10\n",
            "1.7396578788757324 s\n",
            "5.476176873769889e-10\n",
            "1.732656478881836 s\n",
            "3.90623300962345e-10\n",
            "1.733851432800293 s\n",
            "4.363911531787834e-10\n",
            "1.7326831817626953 s\n",
            "2.4693353462695853e-10\n",
            "1.7363579273223877 s\n",
            "4.558158856263206e-10\n",
            "1.7354729175567627 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e00285550>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "9.260007516331825e-10\n",
            "0.019579648971557617 s\n",
            "4.1058021517381693e-10\n",
            "1.7029838562011719 s\n",
            "2.1979213268852326e-10\n",
            "1.6735608577728271 s\n",
            "5.343130715651512e-10\n",
            "1.7077181339263916 s\n",
            "3.781169704078491e-10\n",
            "1.7133674621582031 s\n",
            "4.350606912922883e-10\n",
            "1.7105731964111328 s\n",
            "2.394829533639009e-10\n",
            "1.706418514251709 s\n",
            "4.4836530207342796e-10\n",
            "1.7142107486724854 s\n",
            "9.283955648697883e-10\n",
            "0.017431020736694336 s\n",
            "4.0179917629168393e-10\n",
            "1.7161049842834473 s\n",
            "2.0701970873671095e-10\n",
            "1.7137954235076904 s\n",
            "5.353774373481613e-10\n",
            "1.717881679534912 s\n",
            "3.8104398240867974e-10\n",
            "1.7149386405944824 s\n",
            "4.2814229564425155e-10\n",
            "1.7110586166381836 s\n",
            "2.4161169138309234e-10\n",
            "1.7069144248962402 s\n",
            "4.488974891109221e-10\n",
            "1.7088115215301514 s\n",
            "9.228076436329502e-10\n",
            "0.017007827758789062 s\n",
            "3.853014637553165e-10\n",
            "1.705920934677124 s\n",
            "2.083501693048162e-10\n",
            "1.7105536460876465 s\n",
            "5.356435398007342e-10\n",
            "1.7122712135314941 s\n",
            "3.6960201753311053e-10\n",
            "1.7117719650268555 s\n",
            "4.265457410196349e-10\n",
            "1.7110066413879395 s\n",
            "2.4853008678826784e-10\n",
            "1.7040274143218994 s\n",
            "4.4171299094092343e-10\n",
            "1.7143313884735107 s\n",
            "9.233398401420345e-10\n",
            "0.0176393985748291 s\n",
            "3.9248595144758536e-10\n",
            "1.7096641063690186 s\n",
            "2.0835016944359408e-10\n",
            "1.7098469734191895 s\n",
            "5.356435382047886e-10\n",
            "1.7152163982391357 s\n",
            "3.7039925716852995e-10\n",
            "1.7070930004119873 s\n",
            "4.2548136944264846e-10\n",
            "1.707547903060913 s\n",
            "2.464013498792994e-10\n",
            "1.711855173110962 s\n",
            "4.5980726198768806e-10\n",
            "1.712592601776123 s\n",
            "9.217432506147816e-10\n",
            "0.017396211624145508 s\n",
            "3.8663191988252966e-10\n",
            "1.710637092590332 s\n",
            "2.0994672250695955e-10\n",
            "1.712155818939209 s\n",
            "5.273946784498107e-10\n",
            "1.708932638168335 s\n",
            "3.741255883218941e-10\n",
            "1.7101027965545654 s\n",
            "4.3373023290993465e-10\n",
            "1.707533836364746 s\n",
            "2.442726131784978e-10\n",
            "1.713843584060669 s\n",
            "4.3506068646975705e-10\n",
            "1.7145931720733643 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIiKeU5CLiHju/wNNv0lwfVwGegAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e000a24e0>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "9.238719655968452e-10\n",
            "0.02638697624206543 s\n",
            "3.8849456832079633e-10\n",
            "1.9213173389434814 s\n",
            "2.136720120976543e-10\n",
            "1.7292253971099854 s\n",
            "5.295234134158888e-10\n",
            "1.732947587966919 s\n",
            "3.6800546807796984e-10\n",
            "1.739241361618042 s\n",
            "4.3053712123208856e-10\n",
            "1.727957010269165 s\n",
            "2.4374042867369993e-10\n",
            "1.7277045249938965 s\n",
            "4.5049404810704185e-10\n",
            "1.7257835865020752 s\n",
            "9.164214276324856e-10\n",
            "0.017182588577270508 s\n",
            "3.8743020017856233e-10\n",
            "1.73154616355896 s\n",
            "2.104789063525625e-10\n",
            "1.7394821643829346 s\n",
            "5.433602031854057e-10\n",
            "1.7337918281555176 s\n",
            "3.6348190329132943e-10\n",
            "1.7271578311920166 s\n",
            "4.2548138078774003e-10\n",
            "1.7296512126922607 s\n",
            "2.4427261255399735e-10\n",
            "1.736194372177124 s\n",
            "4.44373912007745e-10\n",
            "1.7317087650299072 s\n",
            "9.270650735970776e-10\n",
            "0.017207860946655273 s\n",
            "3.9700951647708703e-10\n",
            "1.7333228588104248 s\n",
            "2.0462487825695376e-10\n",
            "1.7341766357421875 s\n",
            "5.537378049841335e-10\n",
            "1.7265748977661133 s\n",
            "3.6694109951940224e-10\n",
            "1.730208396911621 s\n",
            "4.2574747328300024e-10\n",
            "1.7302353382110596 s\n",
            "2.4294215181241973e-10\n",
            "1.7364883422851562 s\n",
            "4.5395324738822795e-10\n",
            "1.7427175045013428 s\n",
            "9.164214276324856e-10\n",
            "0.01732802391052246 s\n",
            "3.860997374940944e-10\n",
            "1.7344119548797607 s\n",
            "2.1420419684531343e-10\n",
            "1.7311742305755615 s\n",
            "5.481498746920388e-10\n",
            "1.7302217483520508 s\n",
            "3.6082097674278166e-10\n",
            "1.731557846069336 s\n",
            "4.2920667228663054e-10\n",
            "1.7312586307525635 s\n",
            "2.44272611790719e-10\n",
            "1.7337117195129395 s\n",
            "4.443739119903978e-10\n",
            "1.7299518585205078 s\n",
            "9.217432506147816e-10\n",
            "0.01709437370300293 s\n",
            "3.9328422730272593e-10\n",
            "1.730391263961792 s\n",
            "2.128737358261801e-10\n",
            "1.7328510284423828 s\n",
            "5.40167102991429e-10\n",
            "1.732374906539917 s\n",
            "3.661428266826805e-10\n",
            "1.7346882820129395 s\n",
            "4.326658651319926e-10\n",
            "1.7405040264129639 s\n",
            "2.432082432321514e-10\n",
            "1.7444019317626953 s\n",
            "4.6406473632604197e-10\n",
            "1.733485221862793 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e0001eb00>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "9.025846026133877e-10\n",
            "0.0207517147064209 s\n",
            "3.940825021517269e-10\n",
            "1.770484209060669 s\n",
            "2.2138868701823687e-10\n",
            "1.7228584289550781 s\n",
            "5.383044548654125e-10\n",
            "1.7212109565734863 s\n",
            "3.6374799542229775e-10\n",
            "1.7251157760620117 s\n",
            "4.204256231522818e-10\n",
            "1.7234468460083008 s\n",
            "2.4187778335793554e-10\n",
            "1.7189114093780518 s\n",
            "4.387859855146947e-10\n",
            "1.7132799625396729 s\n",
            "8.95134064649028e-10\n",
            "0.016753673553466797 s\n",
            "3.8689801345331843e-10\n",
            "1.7231378555297852 s\n",
            "2.2032431754026583e-10\n",
            "1.7299680709838867 s\n",
            "5.369739911054161e-10\n",
            "1.7242145538330078 s\n",
            "3.616192582878153e-10\n",
            "1.7238359451293945 s\n",
            "4.116445924927381e-10\n",
            "1.7291102409362793 s\n",
            "2.4853008798522704e-10\n",
            "1.725984811782837 s\n",
            "4.5501759991795067e-10\n",
            "1.7216525077819824 s\n",
            "8.818294361390145e-10\n",
            "0.01705455780029297 s\n",
            "3.7997961763180934e-10\n",
            "1.7291276454925537 s\n",
            "2.131398289285935e-10\n",
            "1.7253801822662354 s\n",
            "5.359096326776336e-10\n",
            "1.7277090549468994 s\n",
            "3.578939683328286e-10\n",
            "1.7277445793151855 s\n",
            "4.073871169400778e-10\n",
            "1.7281692028045654 s\n",
            "2.392168612155854e-10\n",
            "1.724860668182373 s\n",
            "4.2920665929355174e-10\n",
            "1.7280209064483643 s\n",
            "8.722501121383174e-10\n",
            "0.017027854919433594 s\n",
            "3.805118031427468e-10\n",
            "1.6850783824920654 s\n",
            "2.2112259464440732e-10\n",
            "1.692467451095581 s\n",
            "5.218067502046896e-10\n",
            "1.681816816329956 s\n",
            "3.592244302540182e-10\n",
            "1.6822190284729004 s\n",
            "4.028635404093595e-10\n",
            "1.6812078952789307 s\n",
            "2.402812306241675e-10\n",
            "1.685319185256958 s\n",
            "4.414468997467058e-10\n",
            "1.7259762287139893 s\n",
            "8.448426314089374e-10\n",
            "0.017583131790161133 s\n",
            "3.5895833805366094e-10\n",
            "1.725478172302246 s\n",
            "2.1606684321925917e-10\n",
            "1.7232933044433594 s\n",
            "5.194119149544429e-10\n",
            "1.7335703372955322 s\n",
            "3.570956877245457e-10\n",
            "1.7265384197235107 s\n",
            "3.954129557115493e-10\n",
            "1.7260046005249023 s\n",
            "2.3495938630477276e-10\n",
            "1.7306385040283203 s\n",
            "4.169664203496071e-10\n",
            "1.7300405502319336 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAEDCAYAAAAoWo9tAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nnlOQi4h47v8DKrhMqILSgzoAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0dedfd2e80>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "8.240874649345642e-10\n",
            "0.02010655403137207 s\n",
            "3.6188535234432663e-10\n",
            "1.7706389427185059 s\n",
            "2.1287373665884734e-10\n",
            "1.74049973487854 s\n",
            "5.116952414389863e-10\n",
            "1.7365565299987793 s\n",
            "3.4804856011150245e-10\n",
            "1.7311015129089355 s\n",
            "3.807779010156498e-10\n",
            "1.7377893924713135 s\n",
            "2.293714505482991e-10\n",
            "1.733048677444458 s\n",
            "4.153698777639714e-10\n",
            "1.7361042499542236 s\n",
            "7.855040706772342e-10\n",
            "0.01736164093017578 s\n",
            "3.315508417464641e-10\n",
            "1.728475570678711 s\n",
            "2.18993855896632e-10\n",
            "1.7294723987579346 s\n",
            "4.848199349448412e-10\n",
            "1.7303693294525146 s\n",
            "3.480485539011924e-10\n",
            "1.7353429794311523 s\n",
            "3.7359340284565113e-10\n",
            "1.7358975410461426 s\n",
            "2.2378351612756254e-10\n",
            "1.7321815490722656 s\n",
            "3.922198587268111e-10\n",
            "1.7339794635772705 s\n",
            "7.596931084208336e-10\n",
            "0.017304420471191406 s\n",
            "3.310186574151386e-10\n",
            "1.731438398361206 s\n",
            "2.0941453838380087e-10\n",
            "1.7344253063201904 s\n",
            "4.664595691823703e-10\n",
            "1.7346482276916504 s\n",
            "3.3713877720803473e-10\n",
            "1.7363488674163818 s\n",
            "3.637480006785099e-10\n",
            "1.7365491390228271 s\n",
            "2.1872776341871902e-10\n",
            "1.7340741157531738 s\n",
            "3.9009111846982637e-10\n",
            "1.7314114570617676 s\n",
            "7.200453921996086e-10\n",
            "0.017543554306030273 s\n",
            "3.142548538753731e-10\n",
            "1.7360005378723145 s\n",
            "1.9717429826024424e-10\n",
            "1.7405321598052979 s\n",
            "4.5102622449333386e-10\n",
            "1.7297658920288086 s\n",
            "3.225037121211416e-10\n",
            "1.7304372787475586 s\n",
            "3.531043035742698e-10\n",
            "1.7356619834899902 s\n",
            "2.1074499881312825e-10\n",
            "1.7319355010986328 s\n",
            "3.632158116287365e-10\n",
            "1.7361669540405273 s\n",
            "6.870499902333904e-10\n",
            "0.017011165618896484 s\n",
            "3.070703637891858e-10\n",
            "1.7320096492767334 s\n",
            "1.929168237831125e-10\n",
            "1.7304801940917969 s\n",
            "4.4038253156977734e-10\n",
            "1.7374231815338135 s\n",
            "3.1159392822888155e-10\n",
            "1.745760440826416 s\n",
            "3.366065961553366e-10\n",
            "1.731522798538208 s\n",
            "2.038266035293834e-10\n",
            "1.736114740371704 s\n",
            "3.54700864079599e-10\n",
            "1.734865427017212 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAEDCAYAAAD3FPVyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nirSIiMNUpEVEHPb/ATq643JJN84pAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e00053390>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "6.535223207038143e-10\n",
            "0.02587270736694336 s\n",
            "2.958944939068786e-10\n",
            "1.910649061203003 s\n",
            "1.81474860295322e-10\n",
            "1.7362301349639893 s\n",
            "4.246830989824979e-10\n",
            "1.732560157775879 s\n",
            "2.9908759963462316e-10\n",
            "1.7381136417388916 s\n",
            "3.2383416817896583e-10\n",
            "1.741304874420166 s\n",
            "1.9424728516653778e-10\n",
            "1.7318196296691895 s\n",
            "3.374048656787365e-10\n",
            "1.727339506149292 s\n",
            "6.234539284832863e-10\n",
            "0.0181581974029541 s\n",
            "2.759375806495046e-10\n",
            "1.72808837890625 s\n",
            "1.7774956994134894e-10\n",
            "1.7343366146087646 s\n",
            "4.1111239218460937e-10\n",
            "1.7317781448364258 s\n",
            "2.879117231430195e-10\n",
            "1.739189624786377 s\n",
            "3.0387725181643676e-10\n",
            "1.7426080703735352 s\n",
            "1.846679674455398e-10\n",
            "1.7274549007415771 s\n",
            "3.291560149096262e-10\n",
            "1.7350208759307861 s\n",
            "5.965786442629905e-10\n",
            "0.01728057861328125 s\n",
            "2.6449561508004593e-10\n",
            "1.722931146621704 s\n",
            "1.7029898933748623e-10\n",
            "1.7341272830963135 s\n",
            "3.9088938683096153e-10\n",
            "1.7327613830566406 s\n",
            "2.79662866892183e-10\n",
            "1.7346742153167725 s\n",
            "2.972249505545088e-10\n",
            "1.7337126731872559 s\n",
            "1.7721738543655108e-10\n",
            "1.728100299835205 s\n",
            "3.1159392576557423e-10\n",
            "1.7285504341125488 s\n",
            "5.763556387705648e-10\n",
            "0.017511367797851562 s\n",
            "2.647617087375709e-10\n",
            "1.7296342849731445 s\n",
            "1.66573699712097e-10\n",
            "1.7374114990234375 s\n",
            "3.831727234809845e-10\n",
            "1.6889712810516357 s\n",
            "2.7088182667431294e-10\n",
            "1.6990265846252441 s\n",
            "2.8631517021843187e-10\n",
            "1.692521333694458 s\n",
            "1.76419108436493e-10\n",
            "1.7262728214263916 s\n",
            "3.0520771734585116e-10\n",
            "1.727829933166504 s\n",
            "5.622527510240615e-10\n",
            "0.018228769302368164 s\n",
            "2.5544848380673614e-10\n",
            "1.7345421314239502 s\n",
            "1.5938921042388255e-10\n",
            "1.7356913089752197 s\n",
            "3.765204188883875e-10\n",
            "1.7302019596099854 s\n",
            "2.5970595347868385e-10\n",
            "1.7333285808563232 s\n",
            "2.831220711693727e-10\n",
            "1.738757848739624 s\n",
            "1.695007129272341e-10\n",
            "1.7300517559051514 s\n",
            "2.988215087006141e-10\n",
            "1.7376255989074707 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAEDCAYAAAD3FPVyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4yLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvNQv5yAAAHsdJREFUeJzt3Xt0nHd95/G3pNHoLlmyx3fHNjb+\n5eIkJG7SJC25lJwAgZIupLCnnAK79NDTJZzdQ6HtWdoe2HYpDYdCN6FpoTQ9m4aWZNklCaGQkABJ\nsENsB9uxY/98ieOLbMuj+2U099k/5iZpZGskz6P5PdLn9Y8145lHX83lM9/5PreaTCaDiIi4qbba\nBYiIyIUppEVEHKaQFhFxmEJaRMRhCmkREYcppEVEHBbwasHGmK3AE8BXrbUPzvK+dcA/AFuAIPB1\na+0jla9SRMRtnnTSxpgW4AHguTku4t1Ai7X2VuAO4K+NMer6RWTR8aqTjgF3A3+cv8IYcyXwIJAB\nRoCPWWsHL3D/XmBJLphbgRFrbdqjWkVEnOVJd2qtTVprx6dc/QDw+9badwDPAJ+8yP1fBk4Cx4HD\nwJ94UaeIiOs8m0lP40bgm8YYgAZgpzHmeuDvptzuCeAlYB2wCVgBPG+MedpaG5/HekVEqm4+QzoC\n3GGtnXqwkJum3tAY88fAc9baJNBtjOkH1gJveF+miIg75nNl3F7gXQDGmP9ojHnHRW57lGznjTGm\nHVgDnPW8QhERx9R4cRQ8Y8w24CvABiABdAOfA74EpIFx4Hestf0XuH8t8BBwFVAH/K219t8qXqiI\niOM8CWkREakMbXssIuKwiq84DIdH5tyad3Y2MzAQqWQ5nvBLneCfWlVn5fmlVtWZFQq11Ux3vVOd\ndCBQV+0SyuKXOsE/tarOyvNLrarz4pwKaRERmUwhLSLiMIW0iIjDFNIiIg5TSIuIOEwhLSLiMIW0\niIjD5vMoeBe124YJnhjg6vWd1S5FRMQZznTST7z0Bg9///VqlyEi4hRnQjqdgXRaB3sSEZnImZAG\n0AH5REQmcyaks0cWUUqLiEzkTEgz7fGfREQWN3dCGo07RESmciak1UiLiJRyJqRBE2kRkakcCmn1\n0iIiUzkU0mgoLSIyhTMhXaNGWkSkhDMhDZpJi4hM5UxI16Bph4jIVM6EtNYbioiUciekAQ08REQm\ncyaka9RKi4iUcCakQTNpEZGp3AlpNdIiIiXcCWk0kRYRmWrGcxwaY24HHgcO5K56zVr7qUoXokZa\nRKRUuSei/Zm19l5PK0EzaRGRqZwZd2i3cBGRUuV20lcaY54EuoAvWGufvdANOzubCQTqZl9IoA4y\nGUKhtlnftxr8Uif4p1bVWXl+qVV1Xlg5IX0E+ALwGPAW4CfGmM3W2vh0Nx4YiMypkGQyTQYIh0fm\ndP/5FAq1+aJO8E+tqrPy/FKr6iwufzozhrS1thv4Tu7iMWPMOWANcLxi1aFxh4jIdGacSRtjPmyM\n+Uzu55XACqDbi2K04lBEZLJyxh1PAt82xtwDBIE/uNCo41KokRYRKVXOuGME+M15qAXtziIiMpkz\nm+CplRYRKeVOSKOZtIjIVM6EtA5VKiJSypmQBk2kRUSmciekdZJDEZESzoS0hh0iIqWcCWnQuENE\nZCpnQlqdtIhIKWdCGjSSFhGZyp2Q1hGWRERKuBPSIiJSwpmQVh8tIlLKmZDOy2gwLSJS4ExI50fS\nimgRkSJnQlpEREq5F9JqpUVECpwJ6RptgiciUsKZkM7LqJUWESlwLqRFRKTIuZDWFngiIkXOhLRG\n0iIipZwJaRERKeVMSKuRFhEp5UxI52kmLSJS5E5IF4bSSmkRkTxnQlrjDhGRUmWFtDGmyRhzzBjz\nMY/r0bhDRGSCcjvpPwX6vSxErbSISKkZQ9oYczlwJfC09+VoIi0iMlGgjNt8BbgP+Gg5C+zsbCYQ\nqJt1IQ3BbCnLlrXSGCynrOoKhdqqXULZ/FKr6qw8v9SqOi/somlojPkIsMNae9wYU9YCBwYicyok\nHk8B0BsepSE4+5CfT6FQG+HwSLXLKItfalWdleeXWlVncfnTmallfQ/wFmPMe4G1QMwYc9pa++MK\n16fdwkVEpnHRkLbWfij/szHm88CbXgT0RDpUqYhIkTPbSedpEzwRkaKy19BZaz/vYR3aAk9EZBrO\nddIiIlLkTEjrHIciIqWcCek8zaRFRIqcC2kRESlyMKTVSouI5DkT0hpJi4iUciak89RHi4gUORfS\nIiJS5FxIa+sOEZEiZ0Ja20mLiJRyJ6SrXYCIiIOcCem8jOYdIiIF7oS0WmkRkRLuhHSO+mgRkSJn\nQlqNtIhIKWdCukCttIhIgTshrU3wRERKuBPSOWqkRUSKnAnpQh+tTfBERArcCWlNO0RESjgT0nnq\no0VEipwLaRERKXIupDWSFhEpciakdRQ8EZFSzoS0iIiUciak1UeLiJQKzHQDY0wz8M/ACqAR+Atr\n7fe9KkiHKhURKSqnk/5NYJe19jbgg8DfeFKJWmkRkRIzdtLW2u9MuLgOOO1FIcpoEZFSM4Z0njFm\nO7AWeO/FbtfZ2UwgUDfrQhoa67P372oh1Nk86/vPt1CordollM0vtarOyvNLrarzwsoOaWvtLcaY\ntwH/Yoy51lo77fB4YCAyp0Ji0SQA/X1j1CRTc1rGfAmF2giHR6pdRln8UqvqrDy/1Ko6i8ufzowz\naWPMNmPMOgBr7R6ywR6qaHUTZLRjuIhIQTkrDm8F/hDAGLMCaAV6K12I9mURESlVTkj/PbDcGPMi\n8DTwSWtt2rOK1EiLiBSUs3XHOPA7XheiRlpEpJQzexzmqZEWESlyJ6TVSouIlHAnpHPUSYuIFDkT\n0jX5VlrH7hARKXAmpDXuEBEp5U5I56iPFhEpciak1UiLiJRyJqQL1EqLiBQ4E9LaLVxEpJQzIZ2n\nRlpEpMihkFYrLSIylUMhnaVzHIqIFDkT0ppJi4iUciekq12AiIiDnAnpPE07RESK3AlpzTtEREq4\nE9I5aqRFRIqcCWn10SIipZwJ6QINpUVECtwJabXSIiIl3AnpHPXRIiJFzoS0GmkR8atEMs3R7iFP\n9ph2JqQL1EqLiM+8tO8MX3xkN2+cGa74sp0J6fw5DpXRIuI3Y9EkAOPxZMWX7UxIa94hIn6VH3PU\neLBTnjshnaOj4ImI3+Rjy4teM1DOjYwx9wNvz93+r6y1/7fShaiRFhG/yreWVemkjTF3AFuttTcD\n7wK+VvEqRER8LD8BqPWg2yxn3PEC8Nu5nweBFmNMXcUrUSstIj6Vzo87POikZxx3WGtTwFju4seB\nH+Su84RG0iLiN16uSytrJg1gjLmHbEjfdbHbdXY2EwjMvtFubg4W7h8Ktc36/vPNDzXm+aVW1Vl5\nfqnV73Xm86urs6Xif0u5Kw7fCXwOeJe1duhitx0YiMypkPFIonD/cEPlpymVFAq1EQ6PVLuMsvil\nVtVZeX6pdSHUOToWA2BoKEI4XD/n5U9nxpA2xnQAXwbutNb2z+m3lyE/yslodxYR8ZnCtMODdWvl\ndNIfApYBjxlj8td9xFp7svLliIj4T3HrjuqsOPwG8I2K/+YL0IpDEfGbws4sVdoEb17oFIci4lfF\nPQ4XwW7hIiJ+Uzx2R+WX7UxIe/EJJCIyH6q6W/h800xaRPxmUXTSaqRFxK8yHu4W7k5I52g7aRHx\nm0In7cGynQnpwh+njBYRnynOpCu/bGdCWuMOEfErL3dmcSekc9RIi4jfpD3cLdyZkNYmeCLiW4tp\nxaFaaRHxm8K4w4NlOxPS2i28utJpfTqKzJWXZ2ZxJqTztAne/Hv8p0f5vft/wuBorNqliPhSPrcW\n9tYdUjX//nL2qLNHT1/0fA4iciGLqpNWIy0iPpNeDLuFayYtIn61qHYLFxHxm0WxW3j+z/Py1Ogi\nIpU2Hkuyy4aBhT7uqHYBIiJz8OTPjxd+1rhDRMQxw2Pxws8Lu5NWKy0iPrcoznGokbSI+EsxmBd0\nJy0ii1skmiQSTVa7jEuiQ5WKyIJ139de4L6vvVDtMmZtUi4v5E7ai7WiIn4RT6R4+AcHOdkzUu1S\n5BLULuSQLtBQWhahn+8/x4v7zvLFR3ZXuxSZpUmN9EIed+T/NEW0LEaxeAqAeDJd5UrENWWFtDFm\nqzHmmDHmPs8q0bRDRHyuKisOjTEtwAPAcxX/7dNQJ109Wi0gMgcT3jfV2gQvBtwNnKn8ry9SPlSf\nVgeIXBovZtKBmW5grU0CSWNMWQvs7GwmEKibdSEtLQ0AdLQ3EQq1zfr+880PNeaVW2t7R3Ufe788\npl7UmX/9V3r5fnxMXa55utqaGoMX/f9LNWNIz9bAQGRO9xuLZPd/HxoaJxx2ezOkUKjN+RrzZlPr\ncBUfe788pl7VOTZWPHVZpZbv18fU1Zov9HhGo4nCz5dS+4UC3pmtO/J0jkMRkSJnQloz6erTx6PI\nHHgcXjOOO4wx24CvABuAhDHmXuD91tp+TypSUlSNTrgg4p5yVhzuBm73uhBt/lV9aYW0VImfX3te\nR5cz4448/z5V/ufj94n43MRvcfpGN5l7Ia3np2r05pBqSU/YG97PXbUXnAlpHQWv+vTekGqZGMxp\nnx2+xOvociaki5QU1aIORqolnda440KcCWn10dWn94ZUy8TXnv+aBW/Ty5mQzvPd87OA+O/NIQuF\nn8cdXnMnpNVKV50yWqplYkj7b69jb+t1J6Rz/Pb0LCSaBUq1TBp3pP31OvS683cmpGvUSledMlqq\nZWIw+yyjPR8TOhPSBT57ghYSzaSlWvy8M8uiC2n/zaMWDp+9NxaUxf66n7zi0F+Phdf1OhPS2pel\n+vzWwSwkfgumSkv7eBM8r586Z0K6wF/Pz4Lis/fGgrLIM5rMpJ1ZqljIHCyeTrraBYjznXQ6k2HH\ngXOMjidmvrHPuP7Ye23SuMNnj8WiCem8mf7cnYfO882nDvjuifSDmR7TWDzFzkPnSaaqs7fBjv3n\n+OZTr/PQ9/ZX5fd7SeOOCT/77LHIv2+C9d7EqTshXeZQ+qHv7WfHgR56+ud2LkW5sJneG48+e5iH\nvrefZ3edmp+CpujJnT/z0MmBi95uaCzOC3vP+OqD3Ge5VHG+HnfkCv7qfb/uyfIrfiLaS+W3J2gh\nmekr9+FTgwCc7Bmdj3Lm7GuP7eVEzwiNwTpuvGJFtcspi8Yd/h135D9gAnULvJOe7UzaZ8+jL7j+\nmObrm2nHpxM92TM29w1HvS6pYvwWTJXm6z0Oc+XWepSmzoR0UXlPUCKpo7BUWrndnFbyVl5mkb+c\nJx27w18ZTTKVpgao9Wg7YndCOvf3lfsEJaq08mohK7eBqfZ7aCFuU7/YO+nJu4X767GIJ9IE6+s8\nO3GJMyE92z9PnXTlLfa5aDX57St+pfn5eNLxZMqzLTvAoZCerUQyVe0SFpxy3xu+aWQv8b3eHR5l\n/xt9lallBj7LpYqbNO7wWf8VT6QIBuo8W74zIT3brwrqpCtvxk7aN+mcdam592ffeoW/eWzvvGwX\n7rfusdL8PO6IJdKLq5Mu9+mZGNKDozHGY0lvCgLO9Ud898KZixn/xCo/BKlZjgRSFQrXsah3r628\nxfD6uhg/HwUvkczOpL3iXEiXK54L6WQqzacf/DlfeHinJ7/nlYM9/PdvvMyzO6uzA8d8cj0okrP8\n9hSv0Let+dgNfbHMpA+fGmRgJFZyvV/3OMxkMsQTKRoCi6mTvkhQpCacAiHfSQ+OZp/w84PjntTz\nsz1nANi+/5wny3fJjCFdU+btPDLbLXoqNRIbm4eQnviQ7rZhej16PV9MMpX2NCAHRmJ86dFX+fzD\nr5T836SdWTyroPKSqTQZoL7anbQx5qvGmB3GmO3GmBu8KCQ/ku4ZyL4405kMY9EE6XSGR35keeC7\n+xiPFVcWPvrsYTKZzLSfyrNxtm+s8GZOZzIlL9L8h8DASIwnXjpe8sbPTHOf6aTSaTKZzKQPmrxY\nPMW5/gjDY/E5/Q3TLXOiZCpN79A45/ojPP7To8QSKcZjSeKJyStfU+kM/cNR4okU6XSG4UicobF4\n8Q2U+yeeSPPkz4/z7M5TZDIZDr7Zz8ETA4XZbc9AhFhu2YdPDTIWzYbcdI/vdE6fH2U4MvmxSCTT\nhbAsd/VFNJ4imUpztm+sUM90z0EimaZ/yo4vE+fQ+foBxmNJhiNxMpkMI5Hpn6/870il05PuC7Dv\nWC9/+/heIlOunxhSX/9/r/Hlf/tleX/kBD39EfYd6+OHvzjJoRMX33V+qlg8xWf+bjuffvAlInMY\n71zoNTg4GmMo9x460zcGwEik9ENvYnMWjaU41j3Ez/Z08/3tb5LOZEim0oU8mCgSTZDJZEgkU3z3\nZ8c40zvG6fOj7KhAUzUcifPy6+d4ducpwoPj0zaQsUT27w562EnXzDT/McbcBnzWWvteY8wVwD9Z\na2++0O3D4ZE5fRTvO9bL1x7fB8DmNR30Do0zODr5TfC2zcvYc7S3cDkYqJ30lXZNqIVQRxMtjQFq\namsYGI5yomeUrW/pIhJN0h0eJVhfx9m+CBtXtXF+YLwwb1y9rIUzvdkX0ZZ1S2gK1tHWHOSl185O\nW++d29ayZd0SfrTzJMe6h7nxiuUsbW/kTO8Y4aEozQ0B1i1vpau9gWQqw3O7Txe+Nl+xvpO3X7uK\nXYfCvHo4PGm577/1LTQ1BHj02cN0tjVw/ZYQXW0NnDo/ij01yLrlrZzsGSk8NrdsXcnuw2Fi8RSr\nl7WwbUuIfcf6aGqo49DJwWlrb24IEIkl2bS6nQ/cton7/7U0EDpagwyNzvyh0VBfVwjAt67t4Kar\nVvLIj2zJ71vR1cz5gQhj0SQ3X7WS7t5Rtqxdwlg0SSqdpqa2lsHhKMOROGf7ssfo2LSmnZGxBMs7\nm9h/vH/SMpe2NxCJJbn7pvWc6R1jx4EeAK7fEip5TPPuumEde4/2cn5wnDu3reNs/xihJU28sOdM\nYd597aalbLlsCUdODU16rWV/ZyN9w1HqA7UEA7VEokk+fNcW1ixr4WTPKHuP9bJl7RIOvNnPkdND\nBOpqSabStDbV09ZcTyKZpneo+GFw7aalpDMQqKvhl0cm/y6ATavbeeu6JWxY2cax7mGef/U061e2\nsaqrmV8cPE9HS5C7b7qMk+dHOdcXwZ6a/Hx/4I7N1AF7j/YSjacI1NXQOxwlk4HhsTjv/tXLaG4M\n8NqxPg6fHircb0lrkNamepoaAgyMxOgbirJl3RKC9XWMx5J0tjVw4Hg/5rIlJFMZBkaiDEcSfPCO\nTRw4PsDASJRVS1tYu7yVR585TDqTYcvajkm/4z03r+fpHScKlye+/8qxZlkL0XiqsFdpbU1NyTe8\n9uZ62pqDNDbUsbKrmdPnxxiPJ0mnMyzraKS9JUgylaG7d4yBkSg3XL6c1qZ6eoeiHD87TP9waQN4\n1w3r6GproCFYRzqT/WB8ZucpbrpyBZ9431Vl1z+dUKht2vajnJD+H8BJa+0/5i4fAm601g5Pd/u5\nhjTA3z/5Oq+8vvDHCiKysPzK5cv5L7+19ZKWcaGQLucASyuB3RMuh3PXTRvSnZ3NBOa4zeCnPvg2\n/ump/Rw/M8x/uH0T1741lNubp5bDJwfZdbCH1ctaeN+tm/jp7lN0tjdy2Yo2TvaM0BCs47WjvRw5\nNciNV62kvq6W60yIlsZ6HnvuMLFEiuvNcjatWcLhkwOsXdFKUzDAniNh+oaimMs6GRqLcb4/glnf\nxbHTg6wOtZJIplm/so2+4SjJZJrvvXCMy1a00VBfx3AkTltzkO7wKKuWtrBpbQd7j/SSyWQKvy+e\nSNHeEmTz2k6WtAUZjSQ42TPCkVODtDTVc7pnhEQyzR3b1vHdnxyho7WB+kAtK7qaSaczpDMZ1oRa\nCQRqWbW0hfFYku/+5Agrulq4YkMXI5E4S9oa6D4/yuBIjHQmw5nwGJdv6KRvKMrVm5fx1rVL6BmI\nkEikaW8JsmP/WYbH4iSSKVLpDNdtCXH1phB7Dp8nWF/HdWY5bc319A9HaW0O0n1+lN7BcdataOP0\n+REagwE2rumguSHAiXPDtLcEOXRigOHRGK+/2U9zQ4D+4ShbLuvkOrOcQ2/2c7ZvjPe9Pfu8NQQD\nBOtrORMeI0OGm7euojs8xngsQWtTkFuuWcXzu05x4I0+gvV1fOCOzYyOJ9h7pJeNq9s5cXaYjWs6\nON0zQlNjPcOjMa7ZHGJJWwPReJJEMs3BN/s5fmaIutpa1q9qY+OqDiLRBBtXdzA6nsj+bU31DIxE\nSSYznDg3zL6jvbS3BGlqCLC0o5GRSIINq9o5Ex6luameKzd2EU+kSWcy/GL/WW6+ehVPvXic1471\ncs3mZVyzeRnJVIbLN3Tyti3Lqaut4fiZIYZGYzy/6xQjkQS3XreGjpYGfrL7FO2tQW66ahXjsSQ/\nfPlNutobqQ/U8u6bNxBPprEnBkil0nSHR1m/qp3+4Shnw2Pcdv1axmNJXj/eR0tTPc2N9fQOjnPZ\nyjYagwGaGgKMjSeIJVLE4klqa2upD9Ry09aV/PiVk4xEEty0dSXP7zpFPJFm09oOAnW1bN20lCVt\nDTzz8gkSyTS3b1vLroM9ZDIwEomzddMy7IkBXtzTzaa1HbQ21ZNOZ9i4uoP6QC27D50nlU5z89ZV\nNDUEONM7xvLOZuoDtYyOx1m/sp11K9rYfeg89kQ/I5EEV2zoJJnK8PrxPlZ0tXDrdWsID47TOzhO\nKp3hLavbsScHON0zSiBQyxXru2hqDBAeHCcynmDpkiZOnhvmms3LaG9p4GevniYaT3LgjT6u3ryM\n5sZ67Il+1i1vI55Mc/PVq6ipgT2Hw1yzeRk1NTX0DUVZ2dVMNJ7k4Jv9XL15GfFEdlx145Ur2f7a\nWcYica7YuJRDJ/pJJtM0BOsID4zT1dHInsNh7r5lA6FQ25xybybldNLfAJ621j6Ru/wS8J+ttYen\nu/2ldNKhUBvh8Mhc7z5v/FIn+KdW1Vl5fqlVdRaWP20nXc60+wzZzjlvNTD9oFZERCqqnJB+BrgX\nwBhzPXDGWuv+x56IyAIwY0hba7cDu40x24H/BXzS86pERAQo88ws1to/8boQEREp5dwehyIiUqSQ\nFhFxmEJaRMRhCmkREYfNuDOLiIhUjzppERGHKaRFRBymkBYRcZhCWkTEYQppERGHKaRFRBymkBYR\ncVhZB1iaD8aYrwI3kT3d6X+11u6sckkYY7YCTwBftdY+aIxZBzwC1JE9pvbvWmtjxpgPA/+N7ImO\nv2Gt/dY813k/8Hayz+dfATtdq9MY0wz8M7ACaAT+AtjrWp0T6m0C9ufqfM7FOo0xtwOPAwdyV70G\n3O9orR8G/ghIAn8O7HOtTmPMx4HfnXDVrwC/BjxENpf2WWv/IHfbzwK/nbv+C9baH3hVlxM7s8z2\nZLfzVFML8H3gCNkn50FjzMPAD6y1jxtjvgicAv438CpwIxAnG5C3Wmv7L7DoStd5B9nH7m5jzFLg\nl2RDxbU6PwSst9beb4xZDzwL/Ny1OifU+z+Bu4CvA7e5WGcupO+z1t474ToXX6NLgR3ANqAV+AJQ\n71qdU2q+DfggcCXwR9bancaYb5P9YDkE/B/gZqADeBG4ylqb8qIWV8Yd7wC+B2CtPQh0GmPaq1sS\nMeBusmemybsdeDL381PAncCvAjuttUPW2nGywfNr81jnC2Q/0QEGgRYX67TWfsdae3/u4jrgtIt1\nAhhjLif75nw6d5WTdV7A7bhX653Aj621I9bas9baTzha50R/Dvw1sHHCt/p8nXcA/26tjVtrw8AJ\nsq8XT7gy7pjVyW7ng7U2CSSNMROvbrHW5s/zfh5YRbbO8ITb5K+fF7lP77HcxY8DPwDe6VqdebmT\nR6wF3kv2jetinV8B7gM+mrvs3PM+wZXGmCeBLrIdqou1bgCac3V2Ap/HzToBMMbcQLazTwID09TT\nx/R1vuZFPa500lNNe0JGx1yoxqrUboy5h2xI3zflv5yq01p7C/A+4F+m1OBEncaYjwA7rLXHZ1lP\nNR7PI2SD+R6yHyjfYnLj5UqtNcBS4P3Ax4CHcfC5n+D3yK4/maoqdboS0n452e1oboUSwBqydU+t\nPX/9vDHGvBP4HPBua+2Qi3UaY7blVrxird1DNkxGXKsTeA9wjzHmZbJv1j/DwccTwFrbnRsjZay1\nx4BzZEeFrtXaA2y31iZzdY7g5nOfdzuwnWy3vHSaeua1TldC2i8nu/0x8IHczx8Afgj8ArjBGLPE\nGNNKdob24nwVZIzpAL4MvHfCChbn6gRuBf4wV/MKsiuQnKvTWvsha+0N1tqbgH8ku3WHc3VCdosJ\nY8xncj+vJLvlzMMO1voM8BvGmNrcSkQnn3sAY8xqYDQ3b04Ah4wxv5777/fn6nweeI8xJpi7/Rrg\nda9qcmLrDgBjzJfIvpHTwCettXurXM82srPJDUAC6AY+TPZrUCPZlQX/yVqbMMbcC3yW7OY4D1hr\nH53HOj9BdsZ3eMLVHyUbMC7V2UT26/g6oIns1/RdZNfoO1PnlJo/D7wJ/MjFOo0xbcC3gSVAkOxj\n+ktHa/19suM4gL8ku+WGi3VuA/7SWvvu3OUrgX8g29D+wlr76dz1nyKbBxngT621z3lVkzMhLSIi\npVwZd4iIyDQU0iIiDlNIi4g4TCEtIuIwhbSIiMMU0iIiDlNIi4g47P8DxECwTQgzjkAAAAAASUVO\nRK5CYII=\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0dede8fb38>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "5.478837650230162e-10\n",
            "0.025670528411865234 s\n",
            "2.586415916855378e-10\n",
            "1.862067699432373 s\n",
            "1.575265658887437e-10\n",
            "1.727149486541748 s\n",
            "3.6454626532733683e-10\n",
            "1.7253623008728027 s\n",
            "2.575772216871497e-10\n",
            "1.7245426177978516 s\n",
            "2.682209083657017e-10\n",
            "1.7220520973205566 s\n",
            "1.639127769278992e-10\n",
            "1.7247085571289062 s\n",
            "2.993536928758145e-10\n",
            "1.7230513095855713 s\n",
            "5.345791720401394e-10\n",
            "0.017235517501831055 s\n",
            "2.352254776724627e-10\n",
            "1.7313902378082275 s\n",
            "1.5938921049327148e-10\n",
            "1.719313621520996 s\n",
            "3.5576522837074686e-10\n",
            "1.7230546474456787 s\n",
            "2.5012663986898055e-10\n",
            "1.7246084213256836 s\n",
            "2.6609217305267883e-10\n",
            "1.722280740737915 s\n",
            "1.6205013235806586e-10\n",
            "1.7215845584869385 s\n",
            "2.9030655140233066e-10\n",
            "1.720984697341919 s\n",
            "5.292573135307066e-10\n",
            "0.01708364486694336 s\n",
            "2.341611084720474e-10\n",
            "1.7326853275299072 s\n",
            "1.540673668677661e-10\n",
            "1.726257562637329 s\n",
            "3.469841878059321e-10\n",
            "1.7268266677856445 s\n",
            "2.4693353067178905e-10\n",
            "1.7282986640930176 s\n",
            "2.607703252464899e-10\n",
            "1.7238545417785645 s\n",
            "1.6231622417678393e-10\n",
            "1.7302875518798828 s\n",
            "2.812594184636863e-10\n",
            "1.7313039302825928 s\n",
            "5.178153372753513e-10\n",
            "0.01697683334350586 s\n",
            "2.2937145092993826e-10\n",
            "1.722010850906372 s\n",
            "1.577926575860311e-10\n",
            "1.7261698246002197 s\n",
            "3.3634049819569745e-10\n",
            "1.7227153778076172 s\n",
            "2.386846759475092e-10\n",
            "1.7235183715820312 s\n",
            "2.6316515225680016e-10\n",
            "1.7306337356567383 s\n",
            "1.5805874959556876e-10\n",
            "1.7241497039794922 s\n",
            "2.743410242034283e-10\n",
            "1.7272136211395264 s\n",
            "5.082360488017912e-10\n",
            "0.016884803771972656 s\n",
            "2.301697281034687e-10\n",
            "1.7239820957183838 s\n",
            "1.5220472207241876e-10\n",
            "1.7226202487945557 s\n",
            "3.3527613197900654e-10\n",
            "1.7170538902282715 s\n",
            "2.3096800300451136e-10\n",
            "1.724440097808838 s\n",
            "2.541180166119872e-10\n",
            "1.7281389236450195 s\n",
            "1.6098576322703951e-10\n",
            "1.727144479751587 s\n",
            "2.6795481755312324e-10\n",
            "1.719984531402588 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAEDCAYAAAD3FPVyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0dedf53400>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "5.034463868014427e-10\n",
            "0.02515244483947754 s\n",
            "2.3123409435485408e-10\n",
            "1.855921745300293 s\n",
            "1.511403533403788e-10\n",
            "1.7357852458953857 s\n",
            "3.254307241393195e-10\n",
            "1.733269453048706 s\n",
            "2.2697661968690274e-10\n",
            "1.7311296463012695 s\n",
            "2.485300889913666e-10\n",
            "1.7358276844024658 s\n",
            "1.556639195841869e-10\n",
            "1.7363195419311523 s\n",
            "2.668904436169128e-10\n",
            "1.738774299621582 s\n",
            "4.997210822921261e-10\n",
            "0.01772451400756836 s\n",
            "2.240496064023767e-10\n",
            "1.7328736782073975 s\n",
            "1.4688287886324701e-10\n",
            "1.7404742240905762 s\n",
            "3.2516462621437483e-10\n",
            "1.742696762084961 s\n",
            "2.293714486401033e-10\n",
            "1.7321522235870361 s\n",
            "2.4560307508234015e-10\n",
            "1.7321834564208984 s\n",
            "1.5300299822246232e-10\n",
            "1.7304511070251465 s\n",
            "2.6555998164368157e-10\n",
            "1.728562831878662 s\n",
            "4.936009645462036e-10\n",
            "0.017951011657714844 s\n",
            "2.1606684216107785e-10\n",
            "1.735039472579956 s\n",
            "1.4555241774003026e-10\n",
            "1.7339472770690918 s\n",
            "3.214393355481515e-10\n",
            "1.732175350189209 s\n",
            "2.2697662064100065e-10\n",
            "1.7334818840026855 s\n",
            "2.4453870314106174e-10\n",
            "1.7383713722229004 s\n",
            "1.5193862940368619e-10\n",
            "1.7386462688446045 s\n",
            "2.586415846425605e-10\n",
            "1.737058162689209 s\n",
            "4.978584300374678e-10\n",
            "0.01744556427001953 s\n",
            "2.1979213154360577e-10\n",
            "1.745481252670288 s\n",
            "1.444880490079903e-10\n",
            "1.7347896099090576 s\n",
            "3.2037497110087856e-10\n",
            "1.7417514324188232 s\n",
            "2.2165477639099486e-10\n",
            "1.7397642135620117 s\n",
            "2.429421514481278e-10\n",
            "1.7334177494049072 s\n",
            "1.5060816869680305e-10\n",
            "1.7344083786010742 s\n",
            "2.57045031579195e-10\n",
            "1.7337634563446045 s\n",
            "4.893434990549395e-10\n",
            "0.017745256423950195 s\n",
            "2.1500247299535702e-10\n",
            "1.7375788688659668 s\n",
            "1.3916620538248493e-10\n",
            "1.7324190139770508 s\n",
            "3.19310601883116e-10\n",
            "1.7370858192443848 s\n",
            "2.1659902357806793e-10\n",
            "1.738126277923584 s\n",
            "2.4240996853927557e-10\n",
            "1.7378902435302734 s\n",
            "1.4901161573752097e-10\n",
            "1.7373144626617432 s\n",
            "2.578433139222014e-10\n",
            "1.732529640197754 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAEDCAYAAAD3FPVyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e007ef978>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "4.87214748545739e-10\n",
            "0.022455930709838867 s\n",
            "2.195260402106103e-10\n",
            "1.796400547027588 s\n",
            "1.391662052784015e-10\n",
            "1.7198035717010498 s\n",
            "3.2117324267125214e-10\n",
            "1.7136046886444092 s\n",
            "2.1420419495446486e-10\n",
            "1.7154176235198975 s\n",
            "2.3974904346524274e-10\n",
            "1.717566728591919 s\n",
            "1.479472469534393e-10\n",
            "1.7206392288208008 s\n",
            "2.562467604078078e-10\n",
            "1.7104859352111816 s\n",
            "4.861503910547072e-10\n",
            "0.017574787139892578 s\n",
            "2.1659902637097272e-10\n",
            "1.713791847229004 s\n",
            "1.37835744692949e-10\n",
            "1.7206590175628662 s\n",
            "3.1452093868580834e-10\n",
            "1.709501028060913 s\n",
            "2.1287373310266422e-10\n",
            "1.6729762554168701 s\n",
            "2.394829501546625e-10\n",
            "1.675260305404663 s\n",
            "1.4768115459695697e-10\n",
            "1.6805901527404785 s\n",
            "2.517231931405128e-10\n",
            "1.6762237548828125 s\n",
            "4.861503910547072e-10\n",
            "0.017105579376220703 s\n",
            "2.1899385516804815e-10\n",
            "1.6734585762023926 s\n",
            "1.3277999370148175e-10\n",
            "1.6902389526367188 s\n",
            "3.1079565426458953e-10\n",
            "1.7217891216278076 s\n",
            "2.1393810350003873e-10\n",
            "1.7165136337280273 s\n",
            "2.394829475005356e-10\n",
            "1.719611644744873 s\n",
            "1.4502023297502386e-10\n",
            "1.7212765216827393 s\n",
            "2.4932836354546463e-10\n",
            "1.7170782089233398 s\n",
            "4.824250865453905e-10\n",
            "0.017908096313476562 s\n",
            "2.139381049398592e-10\n",
            "1.714376449584961 s\n",
            "1.3144953275173733e-10\n",
            "1.7182910442352295 s\n",
            "3.091990959797064e-10\n",
            "1.7171993255615234 s\n",
            "2.1526856415488016e-10\n",
            "1.7138564586639404 s\n",
            "2.394829524791919e-10\n",
            "1.7180812358856201 s\n",
            "1.4315758776334285e-10\n",
            "1.7148098945617676 s\n",
            "2.469335287115515e-10\n",
            "1.719771146774292 s\n",
            "4.802963715633268e-10\n",
            "0.01809096336364746 s\n",
            "2.1553465670218207e-10\n",
            "1.7162199020385742 s\n",
            "1.3118344056872733e-10\n",
            "1.7238190174102783 s\n",
            "3.0707036335550495e-10\n",
            "1.720823049545288 s\n",
            "2.155346562164595e-10\n",
            "1.7214405536651611 s\n",
            "2.3762030827365053e-10\n",
            "1.7182097434997559 s\n",
            "1.4209321904865014e-10\n",
            "1.7226691246032715 s\n",
            "2.466674380724454e-10\n",
            "1.7205350399017334 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAWkAAAEDCAYAAAD3FPVyAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\npEVEHKaQFhFxmEJaRMRh/x+pqWsEh9t+qAAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f0e045069e8>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "[[1]]\n",
            "[[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]\n",
            "TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT\n",
            "[[31]]\n",
            "[[31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n",
            "mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm\n",
            "[[56]]\n",
            "[[56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56], [56]]\n",
            "OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO\n",
            "4.802963715633268e-10\n",
            "0.026140928268432617 s\n",
            "2.1260764487482375e-10\n",
            "1.9037199020385742 s\n",
            "1.303851640370446e-10\n",
            "1.7388362884521484 s\n",
            "3.068042696806328e-10\n",
            "1.7392020225524902 s\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-40-ccc2f2fd6d1d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mepoch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m5000\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m   \u001b[0mhistory\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m   \u001b[0;32mif\u001b[0m \u001b[0mepoch\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;36m5\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhistory\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-39-be31f5c3ea6c>\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(debug)\u001b[0m\n\u001b[1;32m     15\u001b[0m     \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcriterion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontiguous\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mview\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mntoken\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontiguous\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mview\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m     \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m     \u001b[0mtotal_loss\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     18\u001b[0m     \u001b[0mhistory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3Fc9e1HJZ5lV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def show_hist():\n",
        "  all_good = []\n",
        "  all_bad = []\n",
        "  for i in range(720):\n",
        "    good = data[i].transpose(0, 1)[0].view(chunk_size, 1)\n",
        "    bad = torch.LongTensor(chunk_size, 1).random_(0, ntoken).to(device)\n",
        "    all_good.append(evaluate(good))\n",
        "    all_bad.append(evaluate(bad))\n",
        "\n",
        "  all_good = np.array(all_good)\n",
        "  all_bad = np.array(all_bad)\n",
        "  \n",
        "  good_norm = all_good.mean()\n",
        "  bad_norm = all_bad.mean()\n",
        "\n",
        "  good = all_good / good_norm\n",
        "  bad = all_bad / bad_norm\n",
        "\n",
        "  print(\"good: \", good_norm)\n",
        "  print(\"bad: \", bad_norm)\n",
        "  \n",
        "  g = sns.FacetGrid(attend, col=\"subject\", col_wrap=1, height=2)\n",
        "  \n",
        "  sns.distplot(bad, label=\"bad\")\n",
        "  sns.distplot(good, label=\"good\")\n",
        "  plt.legend()\n",
        "  plt.show()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KdkXupWwaEH5",
        "colab_type": "code",
        "outputId": "b5d01783-00a0-40a6-e2f8-dd65055c803d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 399
        }
      },
      "source": [
        "for i in range(2):\n",
        "  show_hist()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:12: UserWarning: RNN module weights are not part of single contiguous chunk of memory. This means they need to be compacted at every call, possibly greatly increasing memory usage. To compact weights again call flatten_parameters().\n",
            "  if sys.path[0] == '':\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "good:  -1568140547.25\n",
            "bad:  -912133705.0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "error",
          "ename": "NameError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-23-51fafbd8189f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m   \u001b[0mshow_hist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m<ipython-input-20-e46686c5ef2e>\u001b[0m in \u001b[0;36mshow_hist\u001b[0;34m()\u001b[0m\n\u001b[1;32m     20\u001b[0m   \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"bad: \"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbad_norm\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m   \u001b[0mg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mFacetGrid\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mattend\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcol\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"subject\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcol_wrap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     23\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m   \u001b[0msns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdistplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbad\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"bad\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mNameError\u001b[0m: name 'attend' is not defined"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UxqzWi4tNICE",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def evaluate(q):\n",
        "  model.eval()\n",
        "  hidden = model.init_hidden(1)\n",
        "  total_loss = .0\n",
        "  \n",
        "  with torch.no_grad():\n",
        "    output, hidden = model(q, hidden)\n",
        "    output_flat = output.contiguous().view(-1, ntoken)\n",
        "    target = q.contiguous().view(-1)\n",
        "    total_loss += len(data) * criterion(output_flat, target).item()\n",
        "  \n",
        "  return total_loss"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "imXWRlKz922W",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "all_good = []\n",
        "all_bad = []\n",
        "for i in range(720):\n",
        "  good = data[i].transpose(0, 1)[0].view(chunk_size, 1)\n",
        "  bad = torch.LongTensor(chunk_size, 1).random_(0, ntoken).to(device)\n",
        "  all_good.append(evaluate(good))\n",
        "  all_bad.append(evaluate(bad))\n",
        "  \n",
        "all_good = np.array(all_good)\n",
        "all_bad = np.array(all_bad)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R-iyq9EldZq3",
        "colab_type": "code",
        "outputId": "18999a42-dd62-46e2-ae31-ddc221875217",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "print(evaluate(torch.tensor([7] * 70).to(device).view(70, 1)))\n",
        "print(to_alpha[2])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "-193929817.5\n",
            "h\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y091cvwd-P8q",
        "colab_type": "code",
        "outputId": "24c53537-1cc1-4c03-9ae3-a20327af20a3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "good_norm = all_good.mean()\n",
        "bad_norm = all_bad.mean()\n",
        "\n",
        "good = all_good / good_norm\n",
        "bad = all_bad / bad_norm\n",
        "\n",
        "print(\"good: \", good_norm)\n",
        "print(\"bad: \", bad_norm)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "good:  -1568140547.25\n",
            "bad:  -908830605.8125\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9YeO5mrrTfjz",
        "colab_type": "code",
        "outputId": "142780a3-36fd-4f59-84da-2e640f1db10d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        }
      },
      "source": [
        "sns.distplot(bad, label=\"bad\")\n",
        "sns.distplot(good, label=\"good\")\n",
        "plt.legend()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7f40ebd8e3c8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW8AAAD4CAYAAAAjKGdbAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nogH9f/rYyjczw/2AAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<matplotlib.figure.Figure at 0x7f40ebda5048>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1LrA_yNJNAVm",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def pretty(ugly):\n",
        "  res = ''\n",
        "  for c in ugly:\n",
        "    res += to_alpha(c)\n",
        "  \n",
        "  return res"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XTCbkFAJU85p",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def sample(now, debug=False):\n",
        "  now = [[from_alpha[q]] for q in now]\n",
        "  print(now)\n",
        "  model.eval()\n",
        "  hidden = model.init_hidden(1)\n",
        "  \n",
        "  with torch.no_grad():\n",
        "    for i in range(70 - len(now)):\n",
        "      output, hidden = model(torch.tensor(now).type(torch.LongTensor).to(device), hidden)\n",
        "      output = output[-1].squeeze()\n",
        "      now.append([torch.argmax(output).data.cpu().numpy().item()])\n",
        "      \n",
        "  res = ''\n",
        "  print(now)\n",
        "    \n",
        "  for c in now:\n",
        "    res += to_alpha[c[0]]\n",
        "  \n",
        "  return res"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8m2nEoAbWOeF",
        "colab_type": "code",
        "outputId": "dffe5064-774c-42f5-a3b2-b7c984cf30aa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 125
        }
      },
      "source": [
        "sample('From')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[[57], [6], [7], [31]]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:12: UserWarning: RNN module weights are not part of single contiguous chunk of memory. This means they need to be compacted at every call, possibly greatly increasing memory usage. To compact weights again call flatten_parameters().\n",
            "  if sys.path[0] == '':\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "[[57], [6], [7], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31], [31]]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Frommmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8WnMFfa-M3E6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "x = data[0]\n",
        "x.transpose_(0, 1)\n",
        "print(x)\n",
        "\n",
        "pretty(x[0])"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}