Upload ipynd

Nikonov(47)_Autoncoder_(3) (2).ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "source": [
+        "Вариант 6"
+      ],
+      "metadata": {
+        "id": "yyxquN89TFjg"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 131,
+      "metadata": {
+        "id": "CVydt4VKGgsO"
+      },
+      "outputs": [],
+      "source": [
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import tensorflow.keras as keras\n",
+        "import tensorflow.keras.datasets\n",
+        "from  tensorflow.keras.datasets import mnist\n",
+        "from  tensorflow.keras.layers import Input, Dense"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "(train_x, train_y), (test_x, test_y) = mnist.load_data()\n",
+        "\n",
+        "train_x = train_x/255\n",
+        "test_x = test_x/255\n",
+        "\n",
+        "train_x= np.reshape(train_x, (len(train_x), 28*28))\n",
+        "test_x= np.reshape(test_x, (len(test_x), 28*28))"
+      ],
+      "metadata": {
+        "id": "WOd48RHAHfnP"
+      },
+      "execution_count": 132,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "inputs = Input(shape = (28* 28))\n",
+        "x = Dense(150, activation= 'relu')(inputs)\n",
+        "x = Dense(32, activation= 'relu')(x)\n",
+        "x = Dense(10, activation= 'relu')(x)\n",
+        "encoder = Dense(3, activation = 'linear')(x)\n",
+        "\n",
+        "inputs_dec = Input(shape = (3, ))\n",
+        "x = Dense(10, activation= 'relu')(inputs_dec)\n",
+        "x = Dense(32, activation= 'relu')(x)\n",
+        "x = Dense(128, activation= 'relu')(x)\n",
+        "decoder = Dense(28*28, activation='relu')(x)"
+      ],
+      "metadata": {
+        "id": "6WIJF2neKqDP"
+      },
+      "execution_count": 133,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "encoder_model= keras.Model(inputs, encoder)\n",
+        "decoder_model= keras.Model(inputs_dec, decoder)\n",
+        "autoenc = keras.Model(inputs, decoder_model(encoder_model(inputs)))"
+      ],
+      "metadata": {
+        "id": "pC2Jc99fNEMj"
+      },
+      "execution_count": 134,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from tensorflow.keras.utils import plot_model\n",
+        "autoenc.summary()"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-A65igBDgDz9",
+        "outputId": "e36d7a37-72f9-44d5-b47a-923aa33e8a4e"
+      },
+      "execution_count": 161,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Model: \"model_29\"\n",
+            "_________________________________________________________________\n",
+            " Layer (type)                Output Shape              Param #   \n",
+            "=================================================================\n",
+            " input_19 (InputLayer)       [(None, 784)]             0         \n",
+            "                                                                 \n",
+            " model_27 (Functional)       (None, 3)                 122945    \n",
+            "                                                                 \n",
+            " model_28 (Functional)       (None, 784)               105752    \n",
+            "                                                                 \n",
+            "=================================================================\n",
+            "Total params: 228,697\n",
+            "Trainable params: 228,697\n",
+            "Non-trainable params: 0\n",
+            "_________________________________________________________________\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "plot_model(autoenc, expand_nested= True, show_shapes= True, show_layer_names= False, dpi = 70)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 861
+        },
+        "id": "x49KZ4ZMgLjN",
+        "outputId": "5aecb453-765b-45c1-b393-1fb049504143"
+      },
+      "execution_count": 162,
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "image/png": 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\n",
+            "text/plain": [
+              "<IPython.core.display.Image object>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 162
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "autoenc.compile(optimizer= 'adam', loss= 'mean_squared_error', metrics = ['accuracy'])"
+      ],
+      "metadata": {
+        "id": "_FSaNE2vPBC4"
+      },
+      "execution_count": 137,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "autoenc.fit(train_x, train_x, epochs = 7, batch_size = 150)"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "-rlMO3dAP8i1",
+        "outputId": "8f06ed79-d014-48eb-b726-ab2285c0d535"
+      },
+      "execution_count": 138,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Epoch 1/7\n",
+            "400/400 [==============================] - 7s 10ms/step - loss: 0.0611 - accuracy: 0.0109\n",
+            "Epoch 2/7\n",
+            "400/400 [==============================] - 6s 16ms/step - loss: 0.0487 - accuracy: 0.0088\n",
+            "Epoch 3/7\n",
+            "400/400 [==============================] - 6s 15ms/step - loss: 0.0443 - accuracy: 0.0084\n",
+            "Epoch 4/7\n",
+            "400/400 [==============================] - 4s 10ms/step - loss: 0.0417 - accuracy: 0.0085\n",
+            "Epoch 5/7\n",
+            "400/400 [==============================] - 4s 10ms/step - loss: 0.0396 - accuracy: 0.0100\n",
+            "Epoch 6/7\n",
+            "400/400 [==============================] - 5s 13ms/step - loss: 0.0383 - accuracy: 0.0104\n",
+            "Epoch 7/7\n",
+            "400/400 [==============================] - 4s 10ms/step - loss: 0.0377 - accuracy: 0.0105\n"
+          ]
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "<keras.callbacks.History at 0x7f270428b4f0>"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 138
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "autoenc.save('drive2/MyDrive/autoncoder_model')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "7JpFogTU4Wbj",
+        "outputId": "3b38bbba-297a-4364-834e-966b87c20871"
+      },
+      "execution_count": 169,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "WARNING:absl:Found untraced functions such as _update_step_xla while saving (showing 1 of 1). These functions will not be directly callable after loading.\n"
+          ]
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "imageindex = 12\n",
+        "\n",
+        "y = autoenc.predict(test_x)\n",
+        "plt.imshow(test_x[int(imageindex)].reshape(28, 28), cmap = 'gray')\n",
+        "print(\"Исходное изображение:\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 465
+        },
+        "id": "fPE2IJ5mQdjw",
+        "outputId": "876381d7-4bb9-45a9-be0d-b41b8b06b539"
+      },
+      "execution_count": 156,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "313/313 [==============================] - 1s 2ms/step\n",
+            "Исходное изображение:\n"
+          ]
+        },
+        {
+          "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": [
+        "plt.imshow(y[int(imageindex)].reshape(28, 28), cmap = 'gray')\n",
+        "print(\"Полученное изображение:\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 447
+        },
+        "id": "2CFJ9YgcfA_B",
+        "outputId": "0fbbb788-130e-403d-e621-209e03fc512f"
+      },
+      "execution_count": 157,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Полученное изображение:\n"
+          ]
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ],
+            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaAAAAGdCAYAAABU0qcqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAcqUlEQVR4nO3df2xV9f3H8VcL9ILQ3lL647ZQSgsKRH5sY9I1Kl8cDdAlTpQ//PUHLEYmFjfsnKaLirol3VjijEuH/ywwE1FnIhDNwgLVlrgVDBVGGLPSrgiOtiix90JpC7af7x/Eu10p4udy23dbno/kJO2959X75nDoi9N7+7lJzjknAAAGWbL1AACAaxMFBAAwQQEBAExQQAAAExQQAMAEBQQAMEEBAQBMUEAAABOjrQf4qr6+Pp08eVKpqalKSkqyHgcA4Mk5pzNnzigvL0/JyZe/zhlyBXTy5Enl5+dbjwEAuEonTpzQlClTLnv/kPsRXGpqqvUIAIAEuNL38wEroOrqak2bNk1jx45VcXGx3n///W+U48duADAyXOn7+YAU0Ouvv66Kigpt2LBBH3zwgebPn69ly5bp1KlTA/FwAIDhyA2AhQsXuvLy8ujnvb29Li8vz1VVVV0xGw6HnSQ2NjY2tmG+hcPhr/1+n/AroPPnz6uhoUGlpaXR25KTk1VaWqr6+vpL9u/p6VEkEonZAAAjX8IL6LPPPlNvb69ycnJibs/JyVFbW9sl+1dVVSkYDEY3XgEHANcG81fBVVZWKhwOR7cTJ05YjwQAGAQJ/z2gzMxMjRo1Su3t7TG3t7e3KxQKXbJ/IBBQIBBI9BgAgCEu4VdAKSkpWrBggWpqaqK39fX1qaamRiUlJYl+OADAMDUgKyFUVFRo1apV+u53v6uFCxfqhRdeUGdnp370ox8NxMMBAIahASmgu+++W59++qmefvpptbW16Vvf+pZ27tx5yQsTAADXriTnnLMe4n9FIhEFg0HrMQAAVykcDistLe2y95u/Cg4AcG2igAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmKCAAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmKCAAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmKCAAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmKCAAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYGK09QAAMNDS09PjynV0dCR0DsTiCggAYIICAgCYSHgBPfPMM0pKSorZZs2aleiHAQAMcwPyHNCNN96o3bt3//dBRvNUEwAg1oA0w+jRoxUKhQbiSwMARogBeQ7o6NGjysvLU1FRke6//34dP378svv29PQoEonEbACAkS/hBVRcXKwtW7Zo586d2rRpk1paWnTrrbfqzJkz/e5fVVWlYDAY3fLz8xM9EgBgCEpyzrmBfICOjg4VFBTo+eef1wMPPHDJ/T09Perp6Yl+HolEKCEACcXvAdkIh8NKS0u77P0D/uqA9PR03XDDDWpqaur3/kAgoEAgMNBjAACGmAH/PaCzZ8+qublZubm5A/1QAIBhJOEF9Nhjj6murk7Hjh3T3//+d915550aNWqU7r333kQ/FABgGEv4j+A++eQT3XvvvTp9+rSysrJ0yy23aO/evcrKykr0QwEAhrEBfxGCr0gkomAwaD0GhpDrrrvOOzN+/Pi4Hiuefw6TJ0/2zsTzvGdKSop3Jjk5vh9yxJMbN26cd6arq8s709bW5p358MMPvTO4eld6EQJrwQEATFBAAAATFBAAwAQFBAAwQQEBAExQQAAAExQQAMAEBQQAMEEBAQBMUEAAABMUEADABAUEADAx4G9Ih5FrwoQJ3pl4FpqNJ3PkyBHvjCT9+Mc/9s6EQiHvzOjR/v/0vvjiC+9Mb2+vd0aKb1HWeP5MkUjEO7Nv3z7vTLyLsvb19cWVwzfDFRAAwAQFBAAwQQEBAExQQAAAExQQAMAEBQQAMEEBAQBMUEAAABMUEADABAUEADBBAQEATFBAAAATFBAAwASrYUMpKSlx5eJZMTkrK8s7U1JS4p1Zu3atd0aSsrOzvTPxrOh84sQJ70xXV5d3Jt5VoHNycrwz8fzdNjU1eWfS0tK8M/Ge493d3XHl8M1wBQQAMEEBAQBMUEAAABMUEADABAUEADBBAQEATFBAAAATFBAAwAQFBAAwQQEBAExQQAAAExQQAMAEi5FCo0aNiiuXm5vrnZk1a5Z35tvf/rZ3ZtKkSd4ZSTp16pR35siRI4OS6e3t9c7Es6ioJGVmZnpnxo8f752ZMmWKd6ahocE7w6KiQxNXQAAAExQQAMAEBQQAMEEBAQBMUEAAABMUEADABAUEADBBAQEATFBAAAATFBAAwAQFBAAwQQEBAEywGCniXoy0sLDQO1NcXOydmTx5sncmnkVFJemf//ynd2b37t3emc8//9w7M2bMGO9Menq6d0aSQqGQd2bChAnemXA47J1JTub/zSMFf5MAABMUEADAhHcB7dmzR7fffrvy8vKUlJSk7du3x9zvnNPTTz+t3NxcjRs3TqWlpTp69Gii5gUAjBDeBdTZ2an58+erurq63/s3btyoF198US+99JL27dun8ePHa9myZbwhFAAghveLEMrKylRWVtbvfc45vfDCC3ryySd1xx13SJJefvll5eTkaPv27brnnnuubloAwIiR0OeAWlpa1NbWptLS0uhtwWBQxcXFqq+v7zfT09OjSCQSswEARr6EFlBbW5ukS9+HPicnJ3rfV1VVVSkYDEa3/Pz8RI4EABiizF8FV1lZqXA4HN1OnDhhPRIAYBAktIC+/OW19vb2mNvb29sv+4ttgUBAaWlpMRsAYORLaAEVFhYqFAqppqYmelskEtG+fftUUlKSyIcCAAxz3q+CO3v2rJqamqKft7S06ODBg8rIyNDUqVO1fv16/epXv9L111+vwsJCPfXUU8rLy9OKFSsSOTcAYJjzLqD9+/frtttui35eUVEhSVq1apW2bNmixx9/XJ2dnVqzZo06Ojp0yy23aOfOnRo7dmzipgYADHveBbR48WI55y57f1JSkp577jk999xzVzUYBs+0adPiyu3atcs785Of/MQ7M3q0/5q5H330kXdGurjSh6+PP/7YO9PX1+edKSgo8M7MnDnTOyPFt7BoPOL5BfV4FjDF0GT+KjgAwLWJAgIAmKCAAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGDCf5lhDGkTJ070zuTm5sb1WA8//LB35nLvjPt1Dh486J2pr6/3zkjSyZMnvTNdXV3emXjeniQzM9M7E+9K55MnT/bORCIR78xnn33mnfniiy+8MxiauAICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmKCAAAAmKCAAgAkKCABggsVIR5i0tDTvTDwLT0rxLWLa19fnnTl79qx3Jl7p6enemXHjxnlnbrjhBu/MLbfc4p2ZPXu2d0aKb+HTeBYW/fTTT70z4XDYO4OhiSsgAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmKCAAAAmKCAAgAkKCABgggICAJiggAAAJliMdITp7e31zsSzqKgk5eTkeGeysrK8MwUFBd6ZJUuWeGckqaOjwzuTkpLinQkGg96ZeBYwLSoq8s5IUlJSkndm9Gj/byfxLEZ6/vx57wyGJq6AAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmGAx0hEmPT3dO5OcHN//Q+JZ+PSLL77wzkyZMsU7M2HCBO+MJPX09Hhn4lnANJ4FNUeNGuWdGT9+vHdGiu/vdunSpd6ZH/7wh96Zjz76yDuDoYkrIACACQoIAGDCu4D27Nmj22+/XXl5eUpKStL27dtj7l+9erWSkpJituXLlydqXgDACOFdQJ2dnZo/f76qq6svu8/y5cvV2toa3V599dWrGhIAMPJ4vwihrKxMZWVlX7tPIBBQKBSKeygAwMg3IM8B1dbWKjs7WzNnztTatWt1+vTpy+7b09OjSCQSswEARr6EF9Dy5cv18ssvq6amRr/5zW9UV1ensrKyy76ss6qqSsFgMLrl5+cneiQAwBCU8N8Duueee6Ifz507V/PmzdP06dNVW1urJUuWXLJ/ZWWlKioqop9HIhFKCACuAQP+MuyioiJlZmaqqamp3/sDgYDS0tJiNgDAyDfgBfTJJ5/o9OnTys3NHeiHAgAMI94/gjt79mzM1UxLS4sOHjyojIwMZWRk6Nlnn9XKlSsVCoXU3Nysxx9/XDNmzNCyZcsSOjgAYHjzLqD9+/frtttui37+5fM3q1at0qZNm3To0CH96U9/UkdHh/Ly8rR06VL98pe/VCAQSNzUAIBhz7uAFi9eLOfcZe//61//elUD4eqcPXvWO3PkyJG4HmvixInemaysLO9MPAtqhsNh70y8uc7OTu/M1/0bupx4fowd72KkLS0t3pnKykrvzF/+8hfvDEYO1oIDAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmKCAAAAmKCAAgAkKCABgggICAJhI+Ftyw9axY8e8M+np6XE9Vnd3t3cmOzvbOxOJRLwzXV1d3hlJ6u3t9c6cP3/eOxPP287395b2VxLv26B8+OGH3plDhw55Z/7xj394ZzBycAUEADBBAQEATFBAAAATFBAAwAQFBAAwQQEBAExQQAAAExQQAMAEBQQAMEEBAQBMUEAAABMUEADABIuRQgcPHhy03Pjx470znZ2d3pnBFAwGvTOzZ8/2zmRlZXlnWltbvTOSdOTIEe/Mzp0743osXLu4AgIAmKCAAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCxUgxqIb6wqLx6Orq8s5MmzbNOxPPoqfHjh3zzkjS/v37vTO9vb1xPRauXVwBAQBMUEAAABMUEADABAUEADBBAQEATFBAAAATFBAAwAQFBAAwQQEBAExQQAAAExQQAMAEBQQAMMFipMBVKioq8s5MnjzZO9PX1+ed+c9//uOdkaQDBw7ElQN8cAUEADBBAQEATHgVUFVVlW666SalpqYqOztbK1asUGNjY8w+3d3dKi8v16RJkzRhwgStXLlS7e3tCR0aADD8eRVQXV2dysvLtXfvXu3atUsXLlzQ0qVLY95k7NFHH9Vbb72lN954Q3V1dTp58qTuuuuuhA8OABjevF6EsHPnzpjPt2zZouzsbDU0NGjRokUKh8P64x//qK1bt+r73/++JGnz5s2aPXu29u7dq+9973uJmxwAMKxd1XNA4XBYkpSRkSFJamho0IULF1RaWhrdZ9asWZo6darq6+v7/Ro9PT2KRCIxGwBg5Iu7gPr6+rR+/XrdfPPNmjNnjiSpra1NKSkpSk9Pj9k3JydHbW1t/X6dqqoqBYPB6Jafnx/vSACAYSTuAiovL9fhw4f12muvXdUAlZWVCofD0e3EiRNX9fUAAMNDXL+Ium7dOr399tvas2ePpkyZEr09FArp/Pnz6ujoiLkKam9vVygU6vdrBQIBBQKBeMYAAAxjXldAzjmtW7dO27Zt0zvvvKPCwsKY+xcsWKAxY8aopqYmeltjY6OOHz+ukpKSxEwMABgRvK6AysvLtXXrVu3YsUOpqanR53WCwaDGjRunYDCoBx54QBUVFcrIyFBaWpoeeeQRlZSU8Ao4AEAMrwLatGmTJGnx4sUxt2/evFmrV6+WJP3ud79TcnKyVq5cqZ6eHi1btkx/+MMfEjIsAGDk8Cog59wV9xk7dqyqq6tVXV0d91DAcDJ79mzvTG5urnemu7vbO3P8+HHvjCQdO3Ysrhzgg7XgAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmKCAAAAm4npHVAD/NWvWLO/MxIkTvTM9PT3emaamJu8MMFi4AgIAmKCAAAAmKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCxUiB/zFjxgzvTDwLiyYlJXlnPv30U+9MR0eHdwYYLFwBAQBMUEAAABMUEADABAUEADBBAQEATFBAAAATFBAAwAQFBAAwQQEBAExQQAAAExQQAMAEBQQAMMFipMD/mDBhwqBkwuGwd+ajjz7yznzwwQfeGWCwcAUEADBBAQEATFBAAAATFBAAwAQFBAAwQQEBAExQQAAAExQQAMAEBQQAMEEBAQBMUEAAABMUEADABIuRAv+jr6/PO/Pvf//bO/P55597Z+rr670zR44c8c4Ag4UrIACACQoIAGDCq4Cqqqp00003KTU1VdnZ2VqxYoUaGxtj9lm8eLGSkpJitoceeiihQwMAhj+vAqqrq1N5ebn27t2rXbt26cKFC1q6dKk6Oztj9nvwwQfV2toa3TZu3JjQoQEAw5/XixB27twZ8/mWLVuUnZ2thoYGLVq0KHr7ddddp1AolJgJAQAj0lU9B/Tl2wpnZGTE3P7KK68oMzNTc+bMUWVlpc6dO3fZr9HT06NIJBKzAQBGvrhfht3X16f169fr5ptv1pw5c6K333fffSooKFBeXp4OHTqkJ554Qo2NjXrzzTf7/TpVVVV69tln4x0DADBMxV1A5eXlOnz4sN57772Y29esWRP9eO7cucrNzdWSJUvU3Nys6dOnX/J1KisrVVFREf08EokoPz8/3rEAAMNEXAW0bt06vf3229qzZ4+mTJnytfsWFxdLkpqamvotoEAgoEAgEM8YAIBhzKuAnHN65JFHtG3bNtXW1qqwsPCKmYMHD0qScnNz4xoQADAyeRVQeXm5tm7dqh07dig1NVVtbW2SpGAwqHHjxqm5uVlbt27VD37wA02aNEmHDh3So48+qkWLFmnevHkD8gcAAAxPXgW0adMmSRd/2fR/bd68WatXr1ZKSop2796tF154QZ2dncrPz9fKlSv15JNPJmxgAMDI4P0juK+Tn5+vurq6qxoIAHBtSHJXapVBFolEFAwGrccABtSMGTO8M01NTQMwCTBwwuGw0tLSLns/i5ECAExQQAAAExQQAMAEBQQAMEEBAQBMUEAAABMUEADABAUEADBBAQEATFBAAAATFBAAwAQFBAAwEfdbcgOIHwuLAlwBAQCMUEAAABMUEADABAUEADBBAQEATFBAAAATFBAAwAQFBAAwQQEBAExQQAAAExQQAMDEkCsg55z1CACABLjS9/MhV0BnzpyxHgEAkABX+n6e5IbYJUdfX59Onjyp1NRUJSUlxdwXiUSUn5+vEydOKC0tzWhCexyHizgOF3EcLuI4XDQUjoNzTmfOnFFeXp6Sky9/nTPk3o4hOTlZU6ZM+dp90tLSrukT7Esch4s4DhdxHC7iOFxkfRyCweAV9xlyP4IDAFwbKCAAgIlhVUCBQEAbNmxQIBCwHsUUx+EijsNFHIeLOA4XDafjMORehAAAuDYMqysgAMDIQQEBAExQQAAAExQQAMDEsCmg6upqTZs2TWPHjlVxcbHef/9965EG3TPPPKOkpKSYbdasWdZjDbg9e/bo9ttvV15enpKSkrR9+/aY+51zevrpp5Wbm6tx48aptLRUR48etRl2AF3pOKxevfqS82P58uU2ww6Qqqoq3XTTTUpNTVV2drZWrFihxsbGmH26u7tVXl6uSZMmacKECVq5cqXa29uNJh4Y3+Q4LF68+JLz4aGHHjKauH/DooBef/11VVRUaMOGDfrggw80f/58LVu2TKdOnbIebdDdeOONam1tjW7vvfee9UgDrrOzU/Pnz1d1dXW/92/cuFEvvviiXnrpJe3bt0/jx4/XsmXL1N3dPciTDqwrHQdJWr58ecz58eqrrw7ihAOvrq5O5eXl2rt3r3bt2qULFy5o6dKl6uzsjO7z6KOP6q233tIbb7yhuro6nTx5UnfddZfh1In3TY6DJD344IMx58PGjRuNJr4MNwwsXLjQlZeXRz/v7e11eXl5rqqqynCqwbdhwwY3f/586zFMSXLbtm2Lft7X1+dCoZD77W9/G72to6PDBQIB9+qrrxpMODi+ehycc27VqlXujjvuMJnHyqlTp5wkV1dX55y7+Hc/ZswY98Ybb0T3+de//uUkufr6eqsxB9xXj4Nzzv3f//2f++lPf2o31Dcw5K+Azp8/r4aGBpWWlkZvS05OVmlpqerr6w0ns3H06FHl5eWpqKhI999/v44fP249kqmWlha1tbXFnB/BYFDFxcXX5PlRW1ur7OxszZw5U2vXrtXp06etRxpQ4XBYkpSRkSFJamho0IULF2LOh1mzZmnq1Kkj+nz46nH40iuvvKLMzEzNmTNHlZWVOnfunMV4lzXkFiP9qs8++0y9vb3KycmJuT0nJ0cffvih0VQ2iouLtWXLFs2cOVOtra169tlndeutt+rw4cNKTU21Hs9EW1ubJPV7fnx537Vi+fLluuuuu1RYWKjm5mb94he/UFlZmerr6zVq1Cjr8RKur69P69ev180336w5c+ZIung+pKSkKD09PWbfkXw+9HccJOm+++5TQUGB8vLydOjQIT3xxBNqbGzUm2++aThtrCFfQPivsrKy6Mfz5s1TcXGxCgoK9Oc//1kPPPCA4WQYCu65557ox3PnztW8efM0ffp01dbWasmSJYaTDYzy8nIdPnz4mnge9Otc7jisWbMm+vHcuXOVm5urJUuWqLm5WdOnTx/sMfs15H8El5mZqVGjRl3yKpb29naFQiGjqYaG9PR03XDDDWpqarIexcyX5wDnx6WKioqUmZk5Is+PdevW6e2339a7774b8/YtoVBI58+fV0dHR8z+I/V8uNxx6E9xcbEkDanzYcgXUEpKihYsWKCamprobX19faqpqVFJSYnhZPbOnj2r5uZm5ebmWo9iprCwUKFQKOb8iEQi2rdv3zV/fnzyySc6ffr0iDo/nHNat26dtm3bpnfeeUeFhYUx9y9YsEBjxoyJOR8aGxt1/PjxEXU+XOk49OfgwYOSNLTOB+tXQXwTr732mgsEAm7Lli3uyJEjbs2aNS49Pd21tbVZjzaofvazn7na2lrX0tLi/va3v7nS0lKXmZnpTp06ZT3agDpz5ow7cOCAO3DggJPknn/+eXfgwAH38ccfO+ec+/Wvf+3S09Pdjh073KFDh9wdd9zhCgsLXVdXl/HkifV1x+HMmTPusccec/X19a6lpcXt3r3bfec733HXX3+96+7uth49YdauXeuCwaCrra11ra2t0e3cuXPRfR566CE3depU984777j9+/e7kpISV1JSYjh14l3pODQ1NbnnnnvO7d+/37W0tLgdO3a4oqIit2jRIuPJYw2LAnLOud///vdu6tSpLiUlxS1cuNDt3bvXeqRBd/fdd7vc3FyXkpLiJk+e7O6++27X1NRkPdaAe/fdd52kS7ZVq1Y55y6+FPupp55yOTk5LhAIuCVLlrjGxkbboQfA1x2Hc+fOuaVLl7qsrCw3ZswYV1BQ4B588MER95+0/v78ktzmzZuj+3R1dbmHH37YTZw40V133XXuzjvvdK2trXZDD4ArHYfjx4+7RYsWuYyMDBcIBNyMGTPcz3/+cxcOh20H/wrejgEAYGLIPwcEABiZKCAAgAkKCABgggICAJiggAAAJiggAIAJCggAYIICAgCYoIAAACYoIACACQoIAGCCAgIAmPh/17UO3x99e54AAAAASUVORK5CYII=\n"
+          },
+          "metadata": {}
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from google.colab import drive\n",
+        "drive.mount('/content/drive2')"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "fM_tP3SFGNfF",
+        "outputId": "e087108e-4f71-4f8b-9049-44aad9fea084"
+      },
+      "execution_count": 168,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Mounted at /content/drive2\n"
+          ]
+        }
+      ]
+    }
+  ]
+}