style_transfer_l13.ipynb

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  "metadata": {
    "colab": {
      "name": "style_transfer_l13.ipynb",
      "version": "0.3.2",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "accelerator": "GPU"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "[View in Colaboratory](https://colab.research.google.com/github/desirajusantosh/DS/blob/master/style_transfer_l13.ipynb)"
      ]
    },
    {
      "metadata": {
        "id": "HhR2tJb1EOnN",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "%matplotlib inline\n",
        "%reload_ext autoreload\n",
        "%autoreload 2"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "W_AP0ADtET8o",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 4452
        },
        "outputId": "c7451aea-d101-42b3-aa51-2b20802abead"
      },
      "cell_type": "code",
      "source": [
        "import sys\n",
        "sys.path.append('../')\n",
        "#!pip install fastai\n",
        "# http://pytorch.org/\n",
        "from os import path\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",
        "\n",
        "accelerator = 'cu80' if path.exists('/opt/bin/nvidia-smi') else 'cpu'\n",
        "\n",
        "!pip install -q http://download.pytorch.org/whl/{accelerator}/torch-0.3.0.post4-{platform}-linux_x86_64.whl torchvision\n",
        "!pip install https://github.com/fastai/fastai/archive/master.zip\n",
        "!pip install opencv-python\n",
        "!apt update && apt install -y libsm6 libxext6\n",
        "!pip3 install http://download.pytorch.org/whl/cu80/torch-0.3.0.post4-cp36-cp36m-linux_x86_64.whl \n",
        "!pip3 install torchvision\n",
        "import torch\n",
        "from fastai.conv_learner import *\n",
        "from fastai.dataset import *\n",
        "\n",
        "from pathlib import Path\n",
        "import json\n",
        "from PIL import ImageDraw, ImageFont\n",
        "from matplotlib import patches, patheffects"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
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            "  Downloading https://files.pythonhosted.org/packages/7b/44/25b7283e50585f0b4156960691d951b05d061abf4a714078393e51929b30/cssselect-1.0.3-py2.py3-none-any.whl\n",
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            "  Downloading https://files.pythonhosted.org/packages/87/31/b984e17bcc7491c1baeda3906fe3abc14cb5cd5dbd046ab46d9fc7a2edfd/progressbar2-3.34.3-py2.py3-none-any.whl\n",
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            "Collecting jmespath<1.0.0,>=0.7.1 (from botocore==1.10.11->awscli->fastai==0.6)\n",
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            "\u001b[?25hCollecting PrettyTable<0.8,>=0.7.1 (from cliff<2.9,>=2.8.0->kaggle-cli->fastai==0.6)\n",
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            "Collecting stevedore>=1.20.0 (from cliff<2.9,>=2.8.0->kaggle-cli->fastai==0.6)\n",
            "  Downloading https://files.pythonhosted.org/packages/17/6b/3b7d6d08b2ab3e5ef09e01c9f7b3b590ee135f289bb94553419e40922c25/stevedore-1.28.0-py2.py3-none-any.whl\n",
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            "Collecting palettable (from mizani>=0.4.1->plotnine->fastai==0.6)\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/ba/cc/54b3ebfc5d3369e242c600ed49dcdcd3f53a9ac46b082da274386859c821/palettable-3.1.0-py2.py3-none-any.whl (78kB)\n",
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            "Collecting pyperclip (from cmd2>=0.6.7->cliff<2.9,>=2.8.0->kaggle-cli->fastai==0.6)\n",
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            "Building wheels for collected packages: fastai, bcolz, feather-format, kaggle-cli, pandas-summary, torchtext, jupyter-latex-envs, cliff, configparser, PrettyTable, pyperclip\n",
            "  Running setup.py bdist_wheel for fastai ... \u001b[?25l-\b \b\\\b \bdone\n",
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            "  Running setup.py bdist_wheel for bcolz ... \u001b[?25l-\b \b\\\b \b|\b \b/\b \b-\b \b\\\b \b|"
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            "  Running setup.py bdist_wheel for configparser ... \u001b[?25l-\b \bdone\n",
            "\u001b[?25h  Stored in directory: /content/.cache/pip/wheels/a3/61/79/424ef897a2f3b14684a7de5d89e8600b460b89663e6ce9d17c\n",
            "  Running setup.py bdist_wheel for PrettyTable ... \u001b[?25l-\b \bdone\n",
            "\u001b[?25h  Stored in directory: /content/.cache/pip/wheels/80/34/1c/3967380d9676d162cb59513bd9dc862d0584e045a162095606\n",
            "  Running setup.py bdist_wheel for pyperclip ... \u001b[?25l-\b \bdone\n",
            "\u001b[?25h  Stored in directory: /content/.cache/pip/wheels/a7/68/ef/ab1ef01625334f10a979e9fe5ef79e1c4fd4cdf4b710a0067b\n",
            "Successfully built fastai bcolz feather-format kaggle-cli pandas-summary torchtext jupyter-latex-envs cliff configparser PrettyTable pyperclip\n",
            "\u001b[31mkaggle-cli 0.12.13 has requirement lxml<4.1,>=4.0.0, but you'll have lxml 4.2.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mplotnine 0.3.0 has requirement scipy>=1.0.0, but you'll have scipy 0.19.1 which is incompatible.\u001b[0m\n",
            "Installing collected packages: jmespath, docutils, botocore, s3transfer, colorama, awscli, bcolz, pyarrow, feather-format, graphviz, widgetsnbextension, ipywidgets, isoweek, parso, jedi, jupyter-console, qtconsole, jupyter, lxml, jupyter-latex-envs, jupyter-highlight-selected-word, jupyter-contrib-core, jupyter-nbextensions-configurator, jupyter-contrib-nbextensions, pbr, pyperclip, cmd2, PrettyTable, stevedore, cliff, MechanicalSoup, cssselect, configparser, python-utils, progressbar2, kaggle-cli, pandas-summary, palettable, mizani, plotnine, sklearn-pandas, tqdm, torchtext, fastai\n",
            "Successfully installed MechanicalSoup-0.8.0 PrettyTable-0.7.2 awscli-1.15.11 bcolz-1.2.1 botocore-1.10.11 cliff-2.8.1 cmd2-0.8.5 colorama-0.3.7 configparser-3.5.0 cssselect-1.0.3 docutils-0.14 fastai-0.6 feather-format-0.4.0 graphviz-0.8.3 ipywidgets-7.2.1 isoweek-1.3.3 jedi-0.12.0 jmespath-0.9.3 jupyter-1.0.0 jupyter-console-5.2.0 jupyter-contrib-core-0.3.3 jupyter-contrib-nbextensions-0.5.0 jupyter-highlight-selected-word-0.2.0 jupyter-latex-envs-1.4.4 jupyter-nbextensions-configurator-0.4.0 kaggle-cli-0.12.13 lxml-4.2.1 mizani-0.4.6 palettable-3.1.0 pandas-summary-0.0.41 parso-0.2.0 pbr-4.0.2 plotnine-0.3.0 progressbar2-3.34.3 pyarrow-0.9.0 pyperclip-1.6.0 python-utils-2.3.0 qtconsole-4.3.1 s3transfer-0.1.13 sklearn-pandas-1.6.0 stevedore-1.28.0 torchtext-0.2.3 tqdm-4.23.1 widgetsnbextension-3.2.1\n",
            "Requirement already satisfied: opencv-python in /usr/local/lib/python3.6/dist-packages (3.4.0.12)\n",
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            "\u001b[31mplotnine 0.3.0 has requirement scipy>=1.0.0, but you'll have scipy 0.19.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mkaggle-cli 0.12.13 has requirement lxml<4.1,>=4.0.0, but you'll have lxml 4.2.1 which is incompatible.\u001b[0m\n",
            "Get:1 http://security.ubuntu.com/ubuntu artful-security InRelease [83.2 kB]\n",
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            "Get:3 http://archive.ubuntu.com/ubuntu artful-updates InRelease [88.7 kB]\n",
            "Get:4 http://archive.ubuntu.com/ubuntu artful-backports InRelease [74.6 kB]\n",
            "Get:5 http://archive.ubuntu.com/ubuntu artful-updates/universe amd64 Packages [136 kB]\n",
            "Get:6 http://security.ubuntu.com/ubuntu artful-security/universe amd64 Packages [74.3 kB]\n",
            "0% [4 InRelease gpgv 74.6 kB] [Waiting for headers] [Waiting for headers]\u001b[0m"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "Get:7 http://security.ubuntu.com/ubuntu artful-security/main amd64 Packages [199 kB]\n",
            "Get:8 http://archive.ubuntu.com/ubuntu artful-updates/main amd64 Packages [325 kB]\n",
            "Fetched 980 kB in 2s (462 kB/s)\n",
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "All packages are up to date.\n",
            "Reading package lists... Done\n",
            "Building dependency tree       \n",
            "Reading state information... Done\n",
            "libsm6 is already the newest version (2:1.2.2-1).\n",
            "libxext6 is already the newest version (2:1.3.3-1).\n",
            "0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded.\n",
            "Requirement already satisfied: torch==0.3.0.post4 from http://download.pytorch.org/whl/cu80/torch-0.3.0.post4-cp36-cp36m-linux_x86_64.whl in /usr/local/lib/python3.6/dist-packages (0.3.0.post4)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.6/dist-packages (from torch==0.3.0.post4) (3.12)\n",
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            "\u001b[31mplotnine 0.3.0 has requirement scipy>=1.0.0, but you'll have scipy 0.19.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mkaggle-cli 0.12.13 has requirement lxml<4.1,>=4.0.0, but you'll have lxml 4.2.1 which is incompatible.\u001b[0m\n",
            "Requirement already satisfied: torchvision in /usr/local/lib/python3.6/dist-packages (0.2.1)\n",
            "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.6/dist-packages (from torchvision) (5.1.0)\n",
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            "\u001b[31mplotnine 0.3.0 has requirement scipy>=1.0.0, but you'll have scipy 0.19.1 which is incompatible.\u001b[0m\n",
            "\u001b[31mkaggle-cli 0.12.13 has requirement lxml<4.1,>=4.0.0, but you'll have lxml 4.2.1 which is incompatible.\u001b[0m\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "ip-rcYAxE8h2",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "from fastai.conv_learner import *\n",
        "from pathlib import Path\n",
        "from scipy import ndimage"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "g7EDzil2GcKw",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "torch.backends.cudnn.benchmark=True"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Rboul0rxGd_Y",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "outputId": "fe81f5cc-a275-4bfb-e301-f10a2291b886"
      },
      "cell_type": "code",
      "source": [
        "ls"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[0m\u001b[01;34mdatalab\u001b[0m/\r\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "olTxCirxGg5K",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "ls datalab/"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "dCAGs02YGiZj",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "mkdir data/imagenet -p"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Vk9FXv3eJQ3Z",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "outputId": "7c1749b3-47d1-43b5-a361-7cba948c44b5"
      },
      "cell_type": "code",
      "source": [
        "cd data/imagenet/\n"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/data/imagenet\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "0jB6k0VJJSw0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 245
        },
        "outputId": "eba8c827-d6dc-4ea6-dcd9-f10025091c3f"
      },
      "cell_type": "code",
      "source": [
        "!wget -c http://files.fast.ai/data/imagenet-sample-train.tar.gz"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2018-05-01 00:46:40--  http://files.fast.ai/data/imagenet-sample-train.tar.gz\n",
            "Resolving files.fast.ai (files.fast.ai)... 67.205.15.147\n",
            "Connecting to files.fast.ai (files.fast.ai)|67.205.15.147|:80... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 2232645974 (2.1G) [application/x-tar]\n",
            "Saving to: ‘imagenet-sample-train.tar.gz’\n",
            "\n",
            "              image  25%[====>               ] 537.79M  12.9MB/s    eta 2m 24s "
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "imagenet-sample-tra 100%[===================>]   2.08G  15.1MB/s    in 2m 42s  \n",
            "\n",
            "2018-05-01 00:49:22 (13.1 MB/s) - ‘imagenet-sample-train.tar.gz’ saved [2232645974/2232645974]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "FfUgVLKMJT19",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}