_image_classification_with_pytorch.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyM0PtxT6+mJdF8Mtw0uJyz3",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/mohamed-stifi/-Image-Classification-with-PyTorch-and-CIFAR-10-dataset/blob/main/_image_classification_with_pytorch.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x6OgZ7rej_pr",
        "outputId": "2fa65b09-d41b-4a95-afa8-b6a0d3052c89"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<torch._C.Generator at 0x7805c7f6bdb0>"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ],
      "source": [
        "import torch\n",
        "import torchvision\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import torch.nn as nn\n",
        "import torch.optim as optim\n",
        "from torchvision.transforms import transforms\n",
        "from torchvision.utils import make_grid\n",
        "%matplotlib inline\n",
        "torch.manual_seed(43)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Download and preprocess the CIFAR-10 dataset\n",
        "\n"
      ],
      "metadata": {
        "id": "kioDz6AGlJOl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "transform = transforms.Compose(\n",
        "    [transforms.ToTensor(),\n",
        "    transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))\n",
        "])\n",
        "batch_size = 4\n",
        "trainset = torchvision.datasets.CIFAR10(root='./data', train=True,\n",
        "                                        download=True, transform=transform)\n",
        "\n",
        "trainloader = torch.utils.data.DataLoader(trainset, batch_size=batch_size,\n",
        "                                          shuffle=True, num_workers=2)\n",
        "\n",
        "testset = torchvision.datasets.CIFAR10(root='./data', train=False,\n",
        "                                       download=True, transform=transform)\n",
        "testloader = torch.utils.data.DataLoader(testset, batch_size=batch_size,\n",
        "                                         shuffle=False, num_workers=2)\n",
        "\n",
        "classes = trainset.classes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QJYTh2jdkqS3",
        "outputId": "a64ef5e7-bd9e-4b3e-eccf-6fe0b6c6b415"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to ./data/cifar-10-python.tar.gz\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 170498071/170498071 [00:01<00:00, 86405516.50it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracting ./data/cifar-10-python.tar.gz to ./data\n",
            "Files already downloaded and verified\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "With this for loop, we can get the number of images per class in train and test data set."
      ],
      "metadata": {
        "id": "TcJ42EkMpqpe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "train_class_count = {}\n",
        "for _, index in trainset:\n",
        "    label = classes[index]\n",
        "    if label not in train_class_count:\n",
        "        train_class_count[label] = 0\n",
        "    train_class_count[label] += 1\n",
        "test_class_count = {}\n",
        "for _, index in testset:\n",
        "    label = classes[index]\n",
        "    if label not in test_class_count:\n",
        "        test_class_count[label] = 0\n",
        "    test_class_count[label] += 1\n",
        "train_class_count,test_class_count"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aezy9Z-uo3HL",
        "outputId": "cae1885d-ce06-432f-bcd4-663928beff06"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "({'frog': 5000,\n",
              "  'truck': 5000,\n",
              "  'deer': 5000,\n",
              "  'automobile': 5000,\n",
              "  'bird': 5000,\n",
              "  'horse': 5000,\n",
              "  'ship': 5000,\n",
              "  'cat': 5000,\n",
              "  'dog': 5000,\n",
              "  'airplane': 5000},\n",
              " {'cat': 1000,\n",
              "  'ship': 1000,\n",
              "  'airplane': 1000,\n",
              "  'frog': 1000,\n",
              "  'automobile': 1000,\n",
              "  'truck': 1000,\n",
              "  'dog': 1000,\n",
              "  'horse': 1000,\n",
              "  'deer': 1000,\n",
              "  'bird': 1000})"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Here, we can visualize a batch of data using the make_grid helper function from Torchvision."
      ],
      "metadata": {
        "id": "cML54gLtsn6E"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for images, labels in trainloader:\n",
        "    print('images.shape:', images.shape)\n",
        "    print(' '.join(f'{classes[labels[j]]:5s}' for j in range(batch_size)))\n",
        "    images = images/2 + 0.5   # unnormalize\n",
        "    plt.figure(figsize=(16,8))\n",
        "    plt.axis('off')\n",
        "    plt.imshow(make_grid(images, nrow=16).permute((1, 2, 0)))\n",
        "    plt.xlabel(labels)\n",
        "    break"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 387
        },
        "id": "HRzXEn6Sphzb",
        "outputId": "2414b5b5-5ff1-4709-c9a7-685eb8261f87"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "images.shape: torch.Size([4, 3, 32, 32])\n",
            "cat   horse ship  dog  \n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for images, labels in testloader:\n",
        "    print('images.shape:', images.shape)\n",
        "    print(' '.join(f'{classes[labels[j]]:5s}' for j in range(batch_size)))\n",
        "    images = images/2 + 0.5   # unnormalize\n",
        "    plt.figure(figsize=(16,8))\n",
        "    plt.axis('off')\n",
        "    plt.imshow(make_grid(images, nrow=16).permute((1, 2, 0)))\n",
        "    plt.xlabel(labels)\n",
        "    break"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 415
        },
        "id": "fMAkb3H6sU8z",
        "outputId": "b53b65d8-42b5-477d-938e-3a9494a4ef7d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "images.shape: torch.Size([4, 3, 32, 32])\n",
            "cat   ship  ship  airplane\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Build a CNN model for image classification"
      ],
      "metadata": {
        "id": "plln0cR7s1GQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def accuracy(outputs, labels):\n",
        "    _, preds = torch.max(outputs, dim=1)\n",
        "    return torch.tensor(torch.sum(preds == labels).item() / len(preds))"
      ],
      "metadata": {
        "id": "qQCZUvELsafn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "\n",
        "\n",
        "class CNN(nn.Module):\n",
        "    def __init__(self):\n",
        "        super().__init__()\n",
        "        self.conv1 = nn.Conv2d(3, 6, 5)\n",
        "        self.pool = nn.MaxPool2d(2, 2)\n",
        "        self.conv2 = nn.Conv2d(6, 16, 5)\n",
        "        self.fc1 = nn.Linear(16 * 5 * 5, 120)\n",
        "        self.fc2 = nn.Linear(120, 84)\n",
        "        self.fc3 = nn.Linear(84, 10)\n",
        "\n",
        "    def forward(self, x):\n",
        "        x = self.pool(F.relu(self.conv1(x)))\n",
        "        x = self.pool(F.relu(self.conv2(x)))\n",
        "        x = torch.flatten(x, 1) # flatten all dimensions except batch\n",
        "        x = F.relu(self.fc1(x))\n",
        "        x = F.relu(self.fc2(x))\n",
        "        x = self.fc3(x)\n",
        "        return x\n"
      ],
      "metadata": {
        "id": "4IZ6FSvptEBX"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Train model on the training dataset"
      ],
      "metadata": {
        "id": "g2AVerwAu4qH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cnn = CNN()\n",
        "num_epook = 5\n",
        "Loss = nn.CrossEntropyLoss()\n",
        "optimizer = optim.SGD(cnn.parameters(), lr=0.01)"
      ],
      "metadata": {
        "id": "UPHQ3y6ctwYY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "history = []\n",
        "for epook  in  range(num_epook):\n",
        "    for i, (imgs, labels) in enumerate(trainloader):\n",
        "      if i%10 == 0 :\n",
        "        optimizer.zero_grad()\n",
        "        outs = cnn(imgs)\n",
        "        loss = Loss(outs, labels)\n",
        "        loss.backward()\n",
        "        optimizer.step()\n",
        "        if i % 1000 == 0:\n",
        "          print(f\"epook [{epook}/{num_epook}] | i = {i} | loss = {loss.item()}\")\n",
        "        history.append([loss.item(), accuracy(outs, labels)])\n"
      ],
      "metadata": {
        "id": "TfNJw_xju9Df",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d4a2c3d6-1fec-4ae8-ff09-56868edf3bfb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "epook [0/5] | i = 0 | loss = 2.2939932346343994\n",
            "epook [0/5] | i = 1000 | loss = 2.3093085289001465\n",
            "epook [0/5] | i = 2000 | loss = 2.3217790126800537\n",
            "epook [0/5] | i = 3000 | loss = 2.3068528175354004\n",
            "epook [0/5] | i = 4000 | loss = 2.287153959274292\n",
            "epook [0/5] | i = 5000 | loss = 2.3204920291900635\n",
            "epook [0/5] | i = 6000 | loss = 2.3145806789398193\n",
            "epook [0/5] | i = 7000 | loss = 2.2807698249816895\n",
            "epook [0/5] | i = 8000 | loss = 2.2841086387634277\n",
            "epook [0/5] | i = 9000 | loss = 2.2649238109588623\n",
            "epook [0/5] | i = 10000 | loss = 2.30293607711792\n",
            "epook [0/5] | i = 11000 | loss = 2.2417118549346924\n",
            "epook [0/5] | i = 12000 | loss = 2.1992642879486084\n",
            "epook [1/5] | i = 0 | loss = 2.3083248138427734\n",
            "epook [1/5] | i = 1000 | loss = 2.0971133708953857\n",
            "epook [1/5] | i = 2000 | loss = 2.342707633972168\n",
            "epook [1/5] | i = 3000 | loss = 2.1954197883605957\n",
            "epook [1/5] | i = 4000 | loss = 2.018808603286743\n",
            "epook [1/5] | i = 5000 | loss = 1.960712194442749\n",
            "epook [1/5] | i = 6000 | loss = 2.6857337951660156\n",
            "epook [1/5] | i = 7000 | loss = 2.0647969245910645\n",
            "epook [1/5] | i = 8000 | loss = 1.8094797134399414\n",
            "epook [1/5] | i = 9000 | loss = 2.488135576248169\n",
            "epook [1/5] | i = 10000 | loss = 2.360186815261841\n",
            "epook [1/5] | i = 11000 | loss = 1.3170703649520874\n",
            "epook [1/5] | i = 12000 | loss = 1.7085285186767578\n",
            "epook [2/5] | i = 0 | loss = 2.3547120094299316\n",
            "epook [2/5] | i = 1000 | loss = 2.5050315856933594\n",
            "epook [2/5] | i = 2000 | loss = 1.5652220249176025\n",
            "epook [2/5] | i = 3000 | loss = 1.4929122924804688\n",
            "epook [2/5] | i = 4000 | loss = 2.1184258460998535\n",
            "epook [2/5] | i = 5000 | loss = 1.6593060493469238\n",
            "epook [2/5] | i = 6000 | loss = 1.7037878036499023\n",
            "epook [2/5] | i = 7000 | loss = 1.6771773099899292\n",
            "epook [2/5] | i = 8000 | loss = 2.2999138832092285\n",
            "epook [2/5] | i = 9000 | loss = 1.454134464263916\n",
            "epook [2/5] | i = 10000 | loss = 2.4108452796936035\n",
            "epook [2/5] | i = 11000 | loss = 1.6471459865570068\n",
            "epook [2/5] | i = 12000 | loss = 1.853062629699707\n",
            "epook [3/5] | i = 0 | loss = 1.8309880495071411\n",
            "epook [3/5] | i = 1000 | loss = 1.4924733638763428\n",
            "epook [3/5] | i = 2000 | loss = 1.8160874843597412\n",
            "epook [3/5] | i = 3000 | loss = 1.9040799140930176\n",
            "epook [3/5] | i = 4000 | loss = 2.0824084281921387\n",
            "epook [3/5] | i = 5000 | loss = 1.3091933727264404\n",
            "epook [3/5] | i = 6000 | loss = 1.736208438873291\n",
            "epook [3/5] | i = 7000 | loss = 1.5053837299346924\n",
            "epook [3/5] | i = 8000 | loss = 1.6010410785675049\n",
            "epook [3/5] | i = 9000 | loss = 1.7707786560058594\n",
            "epook [3/5] | i = 10000 | loss = 1.8152402639389038\n",
            "epook [3/5] | i = 11000 | loss = 1.6721398830413818\n",
            "epook [3/5] | i = 12000 | loss = 0.9133337736129761\n",
            "epook [4/5] | i = 0 | loss = 1.5569453239440918\n",
            "epook [4/5] | i = 1000 | loss = 3.050900936126709\n",
            "epook [4/5] | i = 2000 | loss = 1.574882984161377\n",
            "epook [4/5] | i = 3000 | loss = 2.2309231758117676\n",
            "epook [4/5] | i = 4000 | loss = 1.3980636596679688\n",
            "epook [4/5] | i = 5000 | loss = 1.4346274137496948\n",
            "epook [4/5] | i = 6000 | loss = 1.2478291988372803\n",
            "epook [4/5] | i = 7000 | loss = 2.1842358112335205\n",
            "epook [4/5] | i = 8000 | loss = 3.2130815982818604\n",
            "epook [4/5] | i = 9000 | loss = 1.6533210277557373\n",
            "epook [4/5] | i = 10000 | loss = 2.031165599822998\n",
            "epook [4/5] | i = 11000 | loss = 2.0320491790771484\n",
            "epook [4/5] | i = 12000 | loss = 1.7054674625396729\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "PATH = './cnn_model.pth'\n",
        "torch.save(cnn.state_dict(), PATH)"
      ],
      "metadata": {
        "id": "xvngMCq6u9Ir"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Evaluate model's performance on the test dataset"
      ],
      "metadata": {
        "id": "Vq3M8w8l1fA9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "cnn_load = CNN()\n",
        "cnn_load.load_state_dict(torch.load(PATH))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IS2xeOo81emp",
        "outputId": "c44fabac-bd66-40fe-fd9e-6cbfad9f3b2a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<All keys matched successfully>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataiter = iter(testloader)\n",
        "images, labels = next(dataiter)"
      ],
      "metadata": {
        "id": "8oAdnCIU2Xx1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "outputs = cnn_load(images)"
      ],
      "metadata": {
        "id": "dFG4Fp5x1_1W"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "_, predicted = torch.max(outputs, 1)\n",
        "\n",
        "print('Predicted: ', ' '.join(f'{classes[predicted[j]]:5s}'\n",
        "                              for j in range(4)))\n",
        "print('True: ', ' '.join(f'{classes[labels[j]]:5s}'\n",
        "                              for j in range(4)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UetytBae1_v5",
        "outputId": "1470f060-773f-4769-dd41-ab24ef807be6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Predicted:  ship  ship  ship  ship \n",
            "True:  cat   ship  ship  airplane\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "correct = 0\n",
        "total = 0\n",
        "\n",
        "with torch.no_grad():\n",
        "    for images, labels in testloader:\n",
        "\n",
        "        outputs = cnn_load(images)\n",
        "\n",
        "        _, predicted = torch.max(outputs.data, 1)\n",
        "        total += labels.size(0)\n",
        "        correct += (predicted == labels).sum().item()\n",
        "\n",
        "print(f'Accuracy of the network on the 10000 test images: {100 * correct // total} %')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yu1VVBUW1_Yy",
        "outputId": "76b322d5-b9c3-4320-9081-fd6209851fcd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy of the network on the 10000 test images: 40 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# prepare to count predictions for each class\n",
        "correct_pred = {classname: 0 for classname in classes}\n",
        "total_pred = {classname: 0 for classname in classes}\n",
        "\n",
        "\n",
        "with torch.no_grad():\n",
        "    for data in testloader:\n",
        "        images, labels = data\n",
        "        outputs = cnn_load(images)\n",
        "        _, predictions = torch.max(outputs, 1)\n",
        "\n",
        "        for label, prediction in zip(labels, predictions):\n",
        "            if label == prediction:\n",
        "                correct_pred[classes[label]] += 1\n",
        "            total_pred[classes[label]] += 1\n",
        "\n",
        "\n",
        "# print accuracy for each class\n",
        "for classname, correct_count in correct_pred.items():\n",
        "    accuracy = 100 * float(correct_count) / total_pred[classname]\n",
        "    print(f'Accuracy for class: {classname:5s} is {accuracy:.1f} %')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PorHVQwf3eDn",
        "outputId": "71b39981-ded5-4d85-9020-36bb246ae9d1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Accuracy for class: airplane is 42.0 %\n",
            "Accuracy for class: automobile is 49.3 %\n",
            "Accuracy for class: bird  is 11.0 %\n",
            "Accuracy for class: cat   is 5.6 %\n",
            "Accuracy for class: deer  is 33.1 %\n",
            "Accuracy for class: dog   is 27.7 %\n",
            "Accuracy for class: frog  is 58.2 %\n",
            "Accuracy for class: horse is 71.7 %\n",
            "Accuracy for class: ship  is 59.6 %\n",
            "Accuracy for class: truck is 46.0 %\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Visualize the train of model"
      ],
      "metadata": {
        "id": "Wv2hyHt045v1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_losses(history):\n",
        "\n",
        "    plt.plot(history, '-x')\n",
        "    #plt.xlabel('epoch')\n",
        "    plt.ylabel('loss')\n",
        "    #plt.title('Loss vs. No. of epochs');"
      ],
      "metadata": {
        "id": "_5q-m9I84OLB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def plot_accuracies(history):\n",
        "\n",
        "    plt.plot(history, '-x')\n",
        "\n",
        "    plt.ylabel('accuracy')\n"
      ],
      "metadata": {
        "id": "UgycXr8I5BA1"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "history = np.array(history)"
      ],
      "metadata": {
        "id": "WVeB9a9o52Lf"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "plot_losses(history[::10,0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "KrLduh_V5A9A",
        "outputId": "a137505c-b809-4862-cd7e-9ef49543ad86"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plot_accuracies(history[::20,1])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "tmpRfX7A5A4w",
        "outputId": "55796e5e-1ceb-45ce-90cc-6d0701c1f5b0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "5tAw5Nc27FlT"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}