CIFAR_10.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.3"
    },
    "colab": {
      "name": "CIFAR_10.ipynb",
      "provenance": [],
      "collapsed_sections": []
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "ejPc2dMqNeq6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0kFIsY9CNerJ",
        "colab_type": "code",
        "outputId": "a15769fa-e03c-49da-b16a-ec6c2f183e9c",
        "colab": {}
      },
      "source": [
        "from keras.datasets import cifar10"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Using TensorFlow backend.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vqk9j74ENer7",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "(x_train, y_train), (x_test, y_test) = cifar10.load_data()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NhNcziz_NesJ",
        "colab_type": "code",
        "outputId": "12003829-f3fa-4beb-a567-b1ffa760ab50",
        "colab": {}
      },
      "source": [
        "print(x_train.shape,y_train.shape)\n",
        "print(x_test.shape,y_test.shape)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(50000, 32, 32, 3) (50000, 1)\n",
            "(10000, 32, 32, 3) (10000, 1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "PpxcWVGKNesP",
        "colab_type": "code",
        "outputId": "2865451a-784d-447a-93a5-e8fa8b13ee20",
        "colab": {}
      },
      "source": [
        "i=1\n",
        "for i in range(10):\n",
        "    plt.imshow(x_train[i])\n",
        "    plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hJcQuvNWNeul",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from keras.layers import Dense, Conv2D, MaxPooling2D, Flatten, Dropout, Activation\n",
        "from keras.models import Sequential\n",
        "from keras.utils import np_utils"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VgxyYmqiNevK",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "y_train=np_utils.to_categorical(y_train)\n",
        "y_test=np_utils.to_categorical(y_test)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wenGR4bZNevS",
        "colab_type": "code",
        "outputId": "184d0222-de91-4a0d-caf6-086f2b1eb94a",
        "colab": {}
      },
      "source": [
        "y_train.shape"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(50000, 10)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VidgphXYNeva",
        "colab_type": "code",
        "outputId": "4442e55d-e5b1-4020-cd4c-ef38df630427",
        "colab": {}
      },
      "source": [
        "model = Sequential()\n",
        "model.add(Conv2D(32, (3, 3), padding='same',\n",
        "                 input_shape=x_train.shape[1:]))\n",
        "model.add(Activation('relu'))\n",
        "model.add(Conv2D(32, (3, 3)))\n",
        "model.add(Activation('relu'))\n",
        "model.add(MaxPooling2D(pool_size=(2, 2)))\n",
        "model.add(Dropout(0.25))\n",
        "\n",
        "model.add(Conv2D(64, (3, 3), padding='same'))\n",
        "model.add(Activation('relu'))\n",
        "model.add(Conv2D(64, (3, 3)))\n",
        "model.add(Activation('relu'))\n",
        "model.add(MaxPooling2D(pool_size=(2, 2)))\n",
        "model.add(Dropout(0.25))\n",
        "\n",
        "model.add(Flatten())\n",
        "model.add(Dense(512))\n",
        "model.add(Activation('relu'))\n",
        "model.add(Dropout(0.5))\n",
        "model.add(Dense(10))\n",
        "model.add(Activation('softmax'))\n",
        "model.summary()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING: Logging before flag parsing goes to stderr.\n",
            "W0713 21:11:16.222381   884 deprecation_wrapper.py:119] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:63: The name tf.get_default_graph is deprecated. Please use tf.compat.v1.get_default_graph instead.\n",
            "\n",
            "W0713 21:11:17.124542   884 deprecation_wrapper.py:119] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:492: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.\n",
            "\n",
            "W0713 21:11:17.502353   884 deprecation_wrapper.py:119] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:3630: The name tf.random_uniform is deprecated. Please use tf.random.uniform instead.\n",
            "\n",
            "W0713 21:11:17.826379   884 deprecation_wrapper.py:119] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:3458: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.\n",
            "\n",
            "W0713 21:11:17.858380   884 deprecation.py:506] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:3013: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
            "W0713 21:11:18.024473   884 deprecation.py:506] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:1259: calling reduce_prod_v1 (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "keep_dims is deprecated, use keepdims instead\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "conv2d_1 (Conv2D)            (None, 32, 32, 32)        896       \n",
            "_________________________________________________________________\n",
            "activation_1 (Activation)    (None, 32, 32, 32)        0         \n",
            "_________________________________________________________________\n",
            "conv2d_2 (Conv2D)            (None, 30, 30, 32)        9248      \n",
            "_________________________________________________________________\n",
            "activation_2 (Activation)    (None, 30, 30, 32)        0         \n",
            "_________________________________________________________________\n",
            "max_pooling2d_1 (MaxPooling2 (None, 15, 15, 32)        0         \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 15, 15, 32)        0         \n",
            "_________________________________________________________________\n",
            "conv2d_3 (Conv2D)            (None, 15, 15, 64)        18496     \n",
            "_________________________________________________________________\n",
            "activation_3 (Activation)    (None, 15, 15, 64)        0         \n",
            "_________________________________________________________________\n",
            "conv2d_4 (Conv2D)            (None, 13, 13, 64)        36928     \n",
            "_________________________________________________________________\n",
            "activation_4 (Activation)    (None, 13, 13, 64)        0         \n",
            "_________________________________________________________________\n",
            "max_pooling2d_2 (MaxPooling2 (None, 6, 6, 64)          0         \n",
            "_________________________________________________________________\n",
            "dropout_2 (Dropout)          (None, 6, 6, 64)          0         \n",
            "_________________________________________________________________\n",
            "flatten_1 (Flatten)          (None, 2304)              0         \n",
            "_________________________________________________________________\n",
            "dense_1 (Dense)              (None, 512)               1180160   \n",
            "_________________________________________________________________\n",
            "activation_5 (Activation)    (None, 512)               0         \n",
            "_________________________________________________________________\n",
            "dropout_3 (Dropout)          (None, 512)               0         \n",
            "_________________________________________________________________\n",
            "dense_2 (Dense)              (None, 10)                5130      \n",
            "_________________________________________________________________\n",
            "activation_6 (Activation)    (None, 10)                0         \n",
            "=================================================================\n",
            "Total params: 1,250,858\n",
            "Trainable params: 1,250,858\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m0vFioWyNewO",
        "colab_type": "code",
        "outputId": "e1f679c0-497f-483f-a424-27a8b2b2fa41",
        "colab": {}
      },
      "source": [
        "model.compile(loss='categorical_crossentropy',\n",
        "              optimizer='adam',\n",
        "              metrics=['accuracy'])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "W0713 21:11:26.358563   884 deprecation_wrapper.py:119] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\optimizers.py:711: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.\n",
            "\n",
            "W0713 21:11:26.406565   884 deprecation.py:506] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:2880: calling reduce_sum_v1 (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "keep_dims is deprecated, use keepdims instead\n",
            "W0713 21:11:26.422567   884 deprecation_wrapper.py:119] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:2884: The name tf.log is deprecated. Please use tf.math.log instead.\n",
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yGBTJcVKNewW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qTEhoNaHNewb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "x_train = x_train.astype('float32')\n",
        "x_test = x_test.astype('float32')\n",
        "x_train /= 255\n",
        "x_test /= 255"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AMLBQXIKNews",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "scrolled": true,
        "id": "A3ir-qucNew0",
        "colab_type": "code",
        "outputId": "ff4def8f-5af9-4ae6-c181-5b4a388433e8",
        "colab": {}
      },
      "source": [
        "model.fit(x_train, y_train,\n",
        "          batch_size=100,\n",
        "          epochs=10,\n",
        "          verbose=2,\n",
        "          validation_data=(x_test, y_test))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "W0713 21:11:44.024093   884 deprecation.py:323] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\tensorflow\\python\\ops\\math_grad.py:1250: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
            "W0713 21:11:44.360929   884 deprecation_wrapper.py:119] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:953: The name tf.assign_add is deprecated. Please use tf.compat.v1.assign_add instead.\n",
            "\n",
            "W0713 21:11:44.385367   884 deprecation.py:506] From C:\\Users\\RAHUL\\AppData\\Local\\Programs\\Python\\Python37\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:675: calling Constant.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Call initializer instance with the dtype argument instead of passing it to the constructor\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Train on 50000 samples, validate on 10000 samples\n",
            "Epoch 1/10\n",
            " - 363s - loss: 1.5982 - acc: 0.4164 - val_loss: 1.2495 - val_acc: 0.5541\n",
            "Epoch 2/10\n",
            " - 328s - loss: 1.2079 - acc: 0.5694 - val_loss: 1.0439 - val_acc: 0.6247\n",
            "Epoch 3/10\n",
            " - 637s - loss: 1.0335 - acc: 0.6371 - val_loss: 0.8983 - val_acc: 0.6887\n",
            "Epoch 4/10\n",
            " - 512s - loss: 0.9135 - acc: 0.6770 - val_loss: 0.8409 - val_acc: 0.7065\n",
            "Epoch 5/10\n",
            " - 304s - loss: 0.8339 - acc: 0.7057 - val_loss: 0.7627 - val_acc: 0.7339\n",
            "Epoch 6/10\n",
            " - 302s - loss: 0.7752 - acc: 0.7270 - val_loss: 0.7279 - val_acc: 0.7496\n",
            "Epoch 7/10\n",
            " - 299s - loss: 0.7219 - acc: 0.7489 - val_loss: 0.6719 - val_acc: 0.7662\n",
            "Epoch 8/10\n",
            " - 301s - loss: 0.6840 - acc: 0.7608 - val_loss: 0.6711 - val_acc: 0.7718\n",
            "Epoch 9/10\n",
            " - 311s - loss: 0.6445 - acc: 0.7732 - val_loss: 0.6372 - val_acc: 0.7813\n",
            "Epoch 10/10\n",
            " - 318s - loss: 0.6104 - acc: 0.7836 - val_loss: 0.6413 - val_acc: 0.7816\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0xe1e70c0eb8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F6E-8g5-Nexl",
        "colab_type": "code",
        "outputId": "f86aa09f-d20c-4242-dc4f-81a6231cf2c3",
        "colab": {}
      },
      "source": [
        "ans=model.predict(x_test,batch_size=16,verbose=1)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "10000/10000 [==============================] - 24s 2ms/step\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "45lES0JqNexs",
        "colab_type": "code",
        "outputId": "681af4d3-33d2-49af-9489-4970d898dff9",
        "colab": {}
      },
      "source": [
        "np.argmax(ans[0])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6veW0MvKNex1",
        "colab_type": "code",
        "outputId": "dd1dd1c9-1d4f-475e-e7cc-306054fb7ec6",
        "colab": {}
      },
      "source": [
        "y_test[0]"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0., 0., 0., 1., 0., 0., 0., 0., 0., 0.])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I6yGZUkoNeyA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "78qZv8PbNezV",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dict={\n",
        "    0:'airplane',\n",
        "    1:'automobile',\n",
        "    2:'bird',\n",
        "    3:'cat',\n",
        "    4:'deer',\n",
        "    5:'dog',\n",
        "    6:'frog',\n",
        "    7:'horse',\n",
        "    8:'ship',\n",
        "    9:'truck'\n",
        "}"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dziW8zYbNezc",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WFW2Dm5JNezt",
        "colab_type": "code",
        "outputId": "ef86d58f-f145-419e-ee13-7c008ac8307d",
        "colab": {}
      },
      "source": [
        "for i in range(len(ans)):\n",
        "    print(np.argmax(ans[i]), np.argmax(y_test[i]))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "370YO5kuNe0h",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q4VON7tmNe1s",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jooWQSIbNe10",
        "colab_type": "code",
        "outputId": "80d6bd12-b15e-4d8f-bcb9-b43993472482",
        "colab": {}
      },
      "source": [
        "scores = model.evaluate(x_test, y_test, verbose=1)\n",
        "print('Test loss:', scores[0])\n",
        "print('Test accuracy:', scores[1])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "10000/10000 [==============================] - 15s 1ms/step\n",
            "Test loss: 0.6413080701828003\n",
            "Test accuracy: 0.7816\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MAMbaWsINe16",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j-UJGgLiNe2B",
        "colab_type": "code",
        "outputId": "f72b809d-e136-443f-f75f-6e2789c302b3",
        "colab": {}
      },
      "source": [
        "for i in range(20):\n",
        "    plt.imshow(x_test[i])\n",
        "    plt.show()\n",
        "    print(dict[np.argmax(ans[i])])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "cat\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "ship\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "ship\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "airplane\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "frog\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "frog\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "automobile\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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OvOkXktvbTS7JnL3KC1/WrPcWgLUgFa1BilhyLwAUXF5rtXn2XRlIXnVN5KsiyLCr+Hm1ujwjDiX3v0vaYQHAiLRyWjjPi5VeWbya3tcwkA2pRQjxhkLBLkQmKNiFyAQFuxCZoGAXIhMU7EJkwnSlNxToNNKF93odnsm1azYth92ylxdePHDwMLXt3TdPbTN9LtnN35Ye9/SzT3I/Du2ntlv276G2bpAldfIUL2JZEaWsF9QSaKzw22AYZFEF+WsYlzr4eSzowdcMMh/roFAlSu7JcJQumGJBf7tRUPiyHRXMvMaLWF5Y4LbhQroI62pQ/NSiZoYEPdmFyAQFuxCZoGAXIhMU7EJkgoJdiEyY6mp8p9PFL93xK0nbbfN81frW+fQq+K5dPKGl2eTtdgZrfLU1ak90111Hk9ufffEndMxTz/KklV3B7Pf38ESYVtAW6MzLLyW3HzzEE0maHe7IWh30XQrW4+s6nZ1SBKkwUTuvRpD01GhyPyqyst5o8vpuoyHPrBmspFfOAWAlWHEvLvJ9tkbp87aCX2dj5xzIHXqyC5EJCnYhMkHBLkQmKNiFyAQFuxCZoGAXIhM20v7pdgB/BeAAxiXEjrv7Z81sH4CvADiCcQuoP3D3y9G++v0+7v4n/yxp65AWTwBgnpYZzPhr1fJKul4cAPzto9+lNm+OqG33fDqZ5OraBTrm8lVeR+y2GZ4Ic+XaNWpr7ObS4cpK+hIsl3xMM6j91g5uEQ/q09VGpDfn0lDL+fWMnkqjYJ9MHvQ68L0Mkn9WuW22yeXNQYMntTSQnv8Gue8BwGt+nzI28mQvAfypu78FwDsA/ImZvRXA/QAecfc7ATwy+V0I8Tpl3WB397Pu/tjk50UApwAcAnAvgAcnf/YggPdtl5NCiM1zQ5/ZzewIgLcBeBTAbe5+Fhi/IADgX4ETQuw4Gw52M5sF8DUAH3V3/oHy58cdM7MTZnbi4kXeDlkIsb1sKNjNrIVxoH/R3R+abD5nZgcn9oMAkitR7n7c3Y+6+9H5+Vu2wmchxE2wbrCbmWHcj/2Uu3/6OtPDAO6b/HwfgG9svXtCiK1iI1lv7wTwIQBPmtnjk20fA/BJAF81sw8DeBHA76+3I7MCbSqxcfnESSZPEWRJrQyWqO3/PPotart09Ry1dXalXxtXK/6pZqbPJcW1K1ypXBleobblOlA4SZunly/wbC0f8IysdlCTz4IMq4pIb1ExuWZgq4fc/9U1fq2HVVqiKoNzxho/r/aIPx+jLMzFET+31WtpWa4VuFhUaT8iEXLdYHf37wb7ePd644UQrw/0DTohMkHBLkQmKNiFyAQFuxCZoGAXIhOmWnASBlRBphSjrtIaxPISl7yef+HFYH9cBul00q2mAKBpaVlr6cpFOmbh0gK1lcPAZum2RQBgQVXMtqfln+WXeeHIwSLPEDz05l3U1gouZd1IF3R0XucRNgzkV3IPAIC1uLzZ76Slw1bJ56Nc4U5aINl1ejyc2vN7qe3satqXquZ+NJpEelPBSSGEgl2ITFCwC5EJCnYhMkHBLkQmKNiFyISpSm9VXWFxkO6HdeE8L9r4/Onnk9tfCOS1pSs8a2y2l+4dBwC9Hpfe3NJFGxdqLl2dfp77WLZ5McpGm8sunUaf2vbPHkhuv3Uf7x33zDnej+7kyZ9R277D3I+il5Ype23ev2xXl2eNdXpcAmzwXaIapiXMcsALcGIpkLxIXzYAqFt8nzM9Pldzu9K2y5f4Pczheqie7EJkgoJdiExQsAuRCQp2ITJBwS5EJkx1Nf7ylSt46L8/lLSde/llOm5tkK4/Vte8FU9Yz2zAW+csL/PkmjVS165d8LY/t99yB7U9f5Gv+q4F7at6s/x4c/NpW9P4sQ4e3kdtl4Ki4QVJxgAAVmqw1Q6SRYIV66I1S201+Cp4t5v2sdXnq9aXXuY17bzkiTArS3xcs+DnvXdfug3YcMTv06XFtKoVoSe7EJmgYBciExTsQmSCgl2ITFCwC5EJCnYhMmFd6c3MbgfwVwAOAKgBHHf3z5rZJwD8IYBXMlg+5u7fjPa1trKCk4//IGkrGvx1p1GkbaNAmlhbTrfUAYCS1PwCgFYzqE/XSvvRbQXJHbcepra52bTkAgALl7gU2Q0SLnyYnpNlcA2t3edzP1Pzc7OgP1GrTWq/RYkwe7gE2AqSZK4t8e7Ag7W0bNvrcz/mD/GkocUXrlKbh1IZn/89+9INT3cTSQ4AFpfTCT4e9H/aiM5eAvhTd3/MzOYAfN/Mvj2xfcbd/+MG9iGE2GE20uvtLICzk58XzewUgEPb7ZgQYmu5oc/sZnYEwNsAPDrZ9BEze8LMHjAzXitXCLHjbDjYzWwWwNcAfNTdrwH4HIA7ANyF8ZP/U2TcMTM7YWYnVlf552ghxPayoWA3sxbGgf5Fd38IANz9nLtX7l4D+DyAu1Nj3f24ux9196O9Hv9OtxBie1k32G3cYuILAE65+6ev237wuj97P4CTW++eEGKr2Mhq/DsBfAjAk2b2+GTbxwB80Mzuwrjo1WkAf7TejryuUa6mJYPBkMtJI2KLst66pO0PAPRm+GtciytvKKq0tDIi5wQAiyvcNgyy72a4CVcv8Npkl9vpgd1b+buqbp/PVYera1gFlzArT8+xB9pQo8H9aAbZcmjwDLY14uNwxD9Sdjrcx95sl9rqq/x+HI3SEiAALC2lMxzbMzN0TH8unSHYKPgNvJHV+O8CSJ19qKkLIV5f6Bt0QmSCgl2ITFCwC5EJCnYhMkHBLkQmTLXgZFmWWLh4MW10Llt0SKbUTJBB1Wlz+aQwrmuVq7xo4OBa2rZ6jReHXFnk+2sFOt++ffzbx3WXSzIXl9Oy3NpVrqF1jds6I35dSm4CkN7nSs2lyJfWXqK23r7gujiX0QZr6WttI37OQU1JtCpu9EBKhfFrvUoKVVZcUUR/Ni29RdmjerILkQkKdiEyQcEuRCYo2IXIBAW7EJmgYBciE6YqvZkBjVZaEmsXQeYVeUkqSp5JNLjC5ZjhgPfJWr3KZbQh6a9lQ95HrRlkec3s5QUFC1JkEwBaPT5Xs55ustbv8Ky36jyXtbDC57FJ5DUAqFtp3agyPh8XjctyrVsWqK0b9L7rkAKiVvHstWFQrHT1WpAtt8a1sm7Bz7smffiWR4Fs209Lb15zH/RkFyITFOxCZIKCXYhMULALkQkKdiEyQcEuRCZMVXorzDDTSB/SR7zg5Bop2rga9M8aBtlrXvJjoQpSuUg6VBFkJwVKCIpIJglSngzcxz7JBLQ1fs7l1UBeK7kfZZABVhdpG+sBNybY35BLonWXZ5vVpIilBcVKfRD00lviMmsZJL2NCj7OLR0Ta0MuLa+RlMMquCZ6sguRCQp2ITJBwS5EJijYhcgEBbsQmbDuaryZdQF8B0Bn8vd/7e4fN7M3AfgygH0AHgPwIXcPlrmBajTC4rnzSdvqIl9tHS2nV9brIW8/FJSgwwxJjgCAosmnZEhWwWvjK9bR6qgHLa/qoOOtFUG9PnJu165y5aIRrLg3A1WgERShY+2aLEgMslEwj8vBKnOT3wfDMj2PQZcvtIIWSlZx/6uSr7gPgvuRPXLLQK0ZDtNJWVFLtI082QcAftvdfx3j9sz3mNk7APwFgM+4+50ALgP48Ab2JYTYIdYNdh/zyqO1NfnnAH4bwF9Ptj8I4H3b4qEQYkvYaH/2xqSD63kA3wbwUwBX3P2V9y1nABzaHheFEFvBhoLd3St3vwvAYQB3A3hL6s9SY83smJmdMLMTg2HwFSMhxLZyQ6vx7n4FwP8G8A4Ae8z+//f8DgNIVvh39+PuftTdj3bCr0oKIbaTdYPdzG41sz2Tn3sA3gPgFIC/AfCvJ392H4BvbJeTQojNs5FEmIMAHjSzBsYvDl919/9hZk8B+LKZ/XsAPwDwhfV2NBoOcfb0C0mbBbJFh9TvatRB26IWfxfhA36sYdDCp26m/aiC+mJl0NaqChJyLDi3USDZNXvpemxFxV/Xy2A+PJAOzYMsHyf7DGS+RrC/uub+W81vY6/TftSBrOXB9QxydRBMFQbEDwCwRvp4HjyLaa254JKsG+zu/gSAtyW2P4fx53chxD8A9A06ITJBwS5EJijYhcgEBbsQmaBgFyITzCP5ZKsPZnYBwCva2zyAi1M7OEd+vBr58Wr+ofnxi+5+a8ow1WB/1YHNTrj70R05uPyQHxn6obfxQmSCgl2ITNjJYD++g8e+HvnxauTHq3nD+LFjn9mFENNFb+OFyIQdCXYzu8fMfmxmz5rZ/Tvhw8SP02b2pJk9bmYnpnjcB8zsvJmdvG7bPjP7tpn9ZPL/3h3y4xNm9veTOXnczN47BT9uN7O/MbNTZvYjM/s3k+1TnZPAj6nOiZl1zezvzOyHEz/+3WT7m8zs0cl8fMXM0r2+GO4+1X8YF/b8KYA3A2gD+CGAt07bj4kvpwHM78BxfxPA2wGcvG7bfwBw/+Tn+wH8xQ758QkAfzbl+TgI4O2Tn+cAPAPgrdOek8CPqc4JAAMwO/m5BeBRjAvGfBXABybb/xOAP76R/e7Ek/1uAM+6+3M+Lj39ZQD37oAfO4a7fwfAwms234tx4U5gSgU8iR9Tx93Puvtjk58XMS6OcghTnpPAj6niY7a8yOtOBPshAD+77vedLFbpAL5lZt83s2M75MMr3ObuZ4HxTQdg/w768hEze2LyNn/bP05cj5kdwbh+wqPYwTl5jR/AlOdkO4q87kSwp8py7JQk8E53fzuAfwXgT8zsN3fIj9cTnwNwB8Y9As4C+NS0DmxmswC+BuCj7s67Wkzfj6nPiW+iyCtjJ4L9DIDbr/udFqvcbtz9pcn/5wF8HTtbeeecmR0EgMn/6dY524y7n5vcaDWAz2NKc2JmLYwD7Ivu/tBk89TnJOXHTs3J5Ng3XOSVsRPB/j0Ad05WFtsAPgDg4Wk7YWZ9M5t75WcAvwPgZDxqW3kY48KdwA4W8HwluCa8H1OYEzMzjGsYnnL3T19nmuqcMD+mPSfbVuR1WiuMr1ltfC/GK50/BfDnO+TDmzFWAn4I4EfT9APAlzB+OzjC+J3OhwHcAuARAD+Z/L9vh/z4LwCeBPAExsF2cAp+/HOM35I+AeDxyb/3TntOAj+mOicA/jHGRVyfwPiF5d9ed8/+HYBnAfw3AJ0b2a++QSdEJugbdEJkgoJdiExQsAuRCQp2ITJBwS5EJijYhcgEBbsQmaBgFyIT/h83oXt/SlpF6QAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "frog\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "cat\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "automobile\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "deer\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "truck\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "dog\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "horse\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "truck\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "ship\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "dog\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "horse\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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bMr34wiFqKza5HxevpNsuXZriraYmr/Jd8OPH+Q4tarwu3JaxQGmopVsXvXHqdTpnZHQHtTnfYEa1yo0Dg+mkoaUmrzM3V+Uyw7XJi/xcTf466G8QH5u8NmCzxNd+scpbQ1UXuf9DgzxBpX9D+vW9czff+W820+qV84elK7sQuaBgFyITFOxCZIKCXYhMULALkQkKdiEyYSXtn/YA+BsA2wE0ARx096+a2RiAbwPYi1YLqD9y96vRsfoqZezdtT1pO/rcz+m8mYnp5HixwJNnZmbScwCgvshbCf3073mNtPmFtLQyMDhE5xTB5amzZ09S2/ZbdlHb3DyXeM5PTKTnTKdlQwDoL3P/G1XeaurCWZ4kMziYTq5pBserLXKZ8uIVnpyydTevXbdhNJ1kMjSSbgsFACMV3vKqFrSvWlzgr7mBCr+uDo+OJMdvf/e76BwPEl4YK7my1wH8ubvfBeBDAP7UzO4G8DCAJ919H4An238LIW5Slg12d59w98Pt2zMAjgHYBeBBAI+17/YYgI+tl5NCiNVzQ9/ZzWwvgA8AeBrANnefAFpvCAC2rrVzQoi1Y8XBbmZDAL4L4LPuzr+c/Ot5B8zskJkdqi7x72tCiPVlRcFuZmW0Av0b7v699vAFM9vRtu8AkPzxsrsfdPdxdx+v9PGNDyHE+rJssFurzs0jAI65+5evMz0O4KH27YcA/GDt3RNCrBUryXq7H8CnALxoZs+3xz4H4IsAvmNmnwZwCsAfLneg/sEN+I39H0za9uy9jc479mI6U27i5K/onIU5/k1jbGNa6gCAoaF0qykAOH8uLcstzvGst5FRfrzZa1xqutTkmVf1Gv+EVCIy2tw1roq+8cob1DYwwNthNZb6qG1DXzqTbniAzyn285StKeetpqaX+LwjR9Py4OWrPLtxyyhf+/kCf11duZKWPQGgWuGvg/G7fiM5vnFTOnMQAFgyX8Sywe7uTwFgot7v3vgphRC9QL+gEyITFOxCZIKCXYhMULALkQkKdiEyoasFJ90d9Xo6e2n7ntvpvOHN6ayml5/j0sSRZ/6B2i6e58UoZ8vctjCTln8WFngmVFT4shTIMTPT/NeG57nCg7Nn07KRk3UHgOocl6GKzuctzHI5z+vpwozVoGDjtUV+rlpQXLQILpUtkEzF4HCYu3qJ2iYvcJm1VuSS6Lbb7qS2aj3tzNQ0b5VVqqQFsmZQIVRXdiEyQcEuRCYo2IXIBAW7EJmgYBciExTsQmRCV6W36sIcTr34T0nb5U28AOCefe9Jjn/wwzwP57Zde6nthX98gtpOHE1n2AFAYyEtUTUbXMepBc23qjVeMLM5z2WoqNTg1cm0ZFcEP1dfgfchW1rg2WZW4J5Mkx53FhRKLJcq1NYI1rFpXG5ypOcNlfm5Bka5hDa2fYzaCpt4kdDZQJY79soryfENI/x4O3buS443mpLehMgeBbsQmaBgFyITFOxCZIKCXYhM6Opu/ML8LI4+/3TS1j/Kdzk379yZHB8a2Uzn3HH3vdR2606+y3loB28l9Nw/P5kc3zHAd3bnq7xV0/QcT6Dx4KnhVdwANMmudZPvxheD7f1SsHteqXAfG2QXnO+pAwXj6+gFnuzSMH7UciW9WiNDvAVYuczPtVjgu93XJnmSzOQiTzbaMJJO6LpwIVmwGQCwcWx3cty1Gy+EULALkQkKdiEyQcEuRCYo2IXIBAW7EJmwrPRmZnsA/A2A7QCaAA66+1fN7AsA/hjAmwW7PufuP4qO1Wg6pkm9tgXwelsz8+m6ZZuC5IglJkEB6N/Iu0sXNnHbNSJr7NjKk3juu/sears0OUVts7NcqhkIElCK5O3bg0QYCxJJikGSTySkLZKad7VAArw2zR/z9CyXKVmdOQCYraXnXZ7ktfCCcn2YrwZJT4FM2TfIW45VG+kwvHKV1/irNdJOehATK9HZ6wD+3N0Pm9kwgF+Y2ZtpY19x9/+6gmMIIXrMSnq9TQCYaN+eMbNjAPivUoQQNyU39J3dzPYC+ACAN38G9xkzO2Jmj5oZr+sshOg5Kw52MxsC8F0An3X3aQBfA3AHgP1oXfm/ROYdMLNDZnao2Yy+/wkh1pMVBbuZldEK9G+4+/cAwN0vuHvD3ZsAvg7gvtRcdz/o7uPuPl4odPWn+EKI61g22K1VR+gRAMfc/cvXje+47m4fB3B07d0TQqwVK7nU3g/gUwBeNLPn22OfA/BJM9uPlv5yAsCfLHegZrOBhfl0TbNag0sGdZI55sHXgsUFLq28/OqvqO3JH/8dtU1enU6OH5rlddquLvLHtWfvHdR2LmhBNBfUhSv3pTO2ijyRC/CgFl7QrqlW4xrV3GJa8lqsc5msOc+fT18KatBFGXFOrmcFfp0rlvjxSoO8ZVfB+Dwr8jp/TI5cDDIml4g+2Azk0JXsxj+FdI3DUFMXQtxc6Bd0QmSCgl2ITFCwC5EJCnYhMkHBLkQmdPVXLgbAmMzjkYyWlprmZ3mm3PmzJ6nt+Wd/Tm1Li+n2SQBQKKaLF3KBBHjt9AVqm7jGZa35RW6zIKOvlZiYmBMUSmw0gkfQ4POiRlR1T89rBHPK4C2SPJAOPfqxFpG8LKiyWSDyJQD09Q9SW63O18qCFlteSRfanJpLS70AcGU6nRFXb3AZVVd2ITJBwS5EJijYhcgEBbsQmaBgFyITFOxCZEJXpTd3h5NCebVA8lqYTffQOnXiOJ1z+NmnqO3yxClqq9e45AVLL1e5n/coKwVSzdxikAHWCIoX1vl7dJPIch5kQxXJ4wIAC6SyYok/7uHB/uR4NajmGDxklPvSxwMAC/xg0lsjKMBZLAf97Uq8097SFM9GLARr7KX08+llPmeJFD+NCk7qyi5EJijYhcgEBbsQmaBgFyITFOxCZIKCXYhM6G5tZ3c0qmnppRFkZV29cjk5fv7SeTrn8uWz1La4wHtoNZaCrCGSXeVBPzRWYBMAmoEcUwokngaRagCgQLKr6kFGVlTPvxQUShwYGaK2DSPDyfFCjcuNpb7gXBt4ocdSH8+WGx3bkhyvNrkEOB/IwH0FLvM1nb8eG1FG3GD6cVejgqqkcGdUcFJXdiEyQcEuRCYo2IXIBAW7EJmgYBciE5bdjTezfgA/A9DXvv/fuvvnzex2AN8CMAbgMIBPuXtUjg0A4JbeLSwYTz5YWJxPjs/MzdE5FePvY/WoZlkhyMYgLYMsmFMMzsV2zgHASlHiBLc1SA26YrBjXSnzmmuFIMmkSWqnAYCRnfrRPq4yDPRz29TUFD9X8NphiTfTc1wlieq4WYWvfbHCk3VQ5LvxlYH0PHf+uGbJa78Z1AxcyZV9CcDvuPv70WrP/ICZfQjAXwH4irvvA3AVwKdXcCwhRI9YNti9xZtvg+X2PwfwOwD+tj3+GICPrYuHQog1YaX92YvtDq4XATwB4DUAU+7/Uv/5DIBd6+OiEGItWFGwu3vD3fcD2A3gPgB3pe6WmmtmB8zskJkdcvJ9Ugix/tzQbry7TwH4KYAPAdho9i+/99wN4ByZc9Ddx9193LT5L0TPWDb6zGyLmW1s3x4A8HsAjgH4CYB/377bQwB+sF5OCiFWz0oSYXYAeMzMimi9OXzH3X9oZr8E8C0z+88AngPwyLJHMlD5yov8fWd6Pi0zlIM5VudyUrPGJaNCmR+zYenEhAaREwGgVOE16PoHRqktSlxBoHCWyuyxcR/7+7ks17eRJ7v0BckpW7fsSI5HcmMlqLk2umkbtVkgs1ar6bWqLvEkk3pQn24pmOdl/tiaQXuzeo3I0SX+nNVIezAnbbeAFQS7ux8B8IHE+OtofX8XQvwaoC/RQmSCgl2ITFCwC5EJCnYhMkHBLkQmWNQuZs1PZnYJwMn2n5sBpIvLdRf58Vbkx1v5dfPjNndPFt7rarC/5cRmh9x9vCcnlx/yI0M/9DFeiExQsAuRCb0M9oM9PPf1yI+3Ij/eyjvGj559ZxdCdBd9jBciE3oS7Gb2gJm9bGbHzezhXvjQ9uOEmb1oZs+b2aEunvdRM7toZkevGxszsyfM7NX2/5t65McXzOxse02eN7OPdsGPPWb2EzM7ZmYvmdmftce7uiaBH11dEzPrN7NnzOyFth//qT1+u5k93V6Pb5sZT99M4e5d/QegiFZZq3cBqAB4AcDd3faj7csJAJt7cN7fBnAvgKPXjf0XAA+3bz8M4K965McXAPxFl9djB4B727eHAbwC4O5ur0ngR1fXBK1k8KH27TKAp9EqGPMdAJ9oj/93AP/hRo7biyv7fQCOu/vr3io9/S0AD/bAj57h7j8DMPm24QfRKtwJdKmAJ/Gj67j7hLsfbt+eQas4yi50eU0CP7qKt1jzIq+9CPZdAE5f93cvi1U6gB+b2S/M7ECPfHiTbe4+AbRedAC29tCXz5jZkfbH/HX/OnE9ZrYXrfoJT6OHa/I2P4Aur8l6FHntRbCnKt/3ShK4393vBfDvAPypmf12j/y4mfgagDvQ6hEwAeBL3TqxmQ0B+C6Az7r7dLfOuwI/ur4mvooir4xeBPsZAHuu+5sWq1xv3P1c+/+LAL6P3lbeuWBmOwCg/f/FXjjh7hfaL7QmgK+jS2tiZmW0Auwb7v699nDX1yTlR6/WpH3uGy7yyuhFsD8LYF97Z7EC4BMAHu+2E2a2wcyG37wN4PcBHI1nrSuPo1W4E+hhAc83g6vNx9GFNbFW/6ZHABxz9y9fZ+rqmjA/ur0m61bktVs7jG/bbfwoWjudrwH4yx758C60lIAXALzUTT8AfBOtj4M1tD7pfBrALQCeBPBq+/+xHvnxPwG8COAIWsG2owt+fBitj6RHADzf/vfRbq9J4EdX1wTA+9Aq4noErTeW/3jda/YZAMcB/G8AfTdyXP2CTohM0C/ohMgEBbsQmaBgFyITFOxCZIKCXYhMULALkQkKdiEyQcEuRCb8P4wrVUTsfp/kAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "ship\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "frog\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TRbwsINMNe2I",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-ISI3kIrNe2N",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WGVElgttNe2S",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}