3. Machine Learning & Deep Learning/191002_(2) _ cifar-10.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"191002_(2) ; cifar-10.ipynb","provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"QQOs_tw043W_","colab_type":"code","colab":{}},"source":["import tensorflow as tf\n","import os, warnings\n","warnings.filterwarnings(action='ignore')\n","from tensorflow.keras.datasets.cifar10 import load_data"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"WUX-Wexw58Hu","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":55},"outputId":"1fbaafee-97cd-4920-a275-9b80bddb407f","executionInfo":{"status":"ok","timestamp":1569993632939,"user_tz":-540,"elapsed":5041,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["cifar10 = tf.keras.datasets.cifar10\n","(X_train, y_train), (X_test, y_test) = cifar10.load_data()"],"execution_count":2,"outputs":[{"output_type":"stream","text":["Downloading data from https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz\n","170500096/170498071 [==============================] - 2s 0us/step\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"fnNYtoZ_6Zh_","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":36},"outputId":"61282519-ef1c-4cca-a119-1ef594773cdb","executionInfo":{"status":"ok","timestamp":1569993710212,"user_tz":-540,"elapsed":437,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["X_train.shape"],"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(50000, 32, 32, 3)"]},"metadata":{"tags":[]},"execution_count":3}]},{"cell_type":"code","metadata":{"id":"itL_wTpQ6thg","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":36},"outputId":"78f7ae61-fd2e-4a60-9a0d-02ca314c0570","executionInfo":{"status":"ok","timestamp":1569993719259,"user_tz":-540,"elapsed":536,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["y_train.shape"],"execution_count":4,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(50000, 1)"]},"metadata":{"tags":[]},"execution_count":4}]},{"cell_type":"code","metadata":{"id":"DmkNioYg6vtf","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":36},"outputId":"c889a345-c158-42bc-9d0e-db5657bf5f09","executionInfo":{"status":"ok","timestamp":1569993725216,"user_tz":-540,"elapsed":491,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["X_test.shape"],"execution_count":5,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(10000, 32, 32, 3)"]},"metadata":{"tags":[]},"execution_count":5}]},{"cell_type":"code","metadata":{"id":"Suts34Qh6xLP","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":56},"outputId":"bc57a789-81ef-4605-975b-cb917aa24860","executionInfo":{"status":"ok","timestamp":1569993744802,"user_tz":-540,"elapsed":488,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["cifar10"],"execution_count":6,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<module 'tensorflow.keras.datasets.cifar10' from '/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/api/_v1/keras/datasets/cifar10/__init__.py'>"]},"metadata":{"tags":[]},"execution_count":6}]},{"cell_type":"code","metadata":{"id":"xDFmlOaj73Sl","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":36},"outputId":"94af19b8-b2ca-4395-caf9-da7e211661f8","executionInfo":{"status":"ok","timestamp":1569994490680,"user_tz":-540,"elapsed":603,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["import numpy as np\n","np.unique(y_test)"],"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"]},"metadata":{"tags":[]},"execution_count":16}]},{"cell_type":"code","metadata":{"id":"NukdZzeC619P","colab_type":"code","colab":{}},"source":["X = tf.placeholder(tf.float32, [None, 32, 32, 3])\n","Y = tf.placeholder(tf.float32, [None,10])"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"LvmtHg009-nS","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":36},"outputId":"e281b681-cf38-4faf-d8d9-fb7f925e895e","executionInfo":{"status":"ok","timestamp":1569994597656,"user_tz":-540,"elapsed":593,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["W1 = tf.Variable(tf.random_normal([3,3,3,32], stddev=0.01))\n","L1 = tf.nn.conv2d(X, W1, strides=[1,1,1,1], padding='SAME')\n","L1 = tf.nn.relu(L1) ## 활성화 함수\n","L1 = tf.nn.max_pool(L1, ksize=[1,2,2,1], strides=[1,2,2,1], padding='SAME')\n","print(L1)"],"execution_count":18,"outputs":[{"output_type":"stream","text":["Tensor(\"MaxPool:0\", shape=(?, 16, 16, 32), dtype=float32)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"0pBLBWO7-GJQ","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":36},"outputId":"4501b256-6431-4025-ac3d-8343679f1599","executionInfo":{"status":"ok","timestamp":1569994625518,"user_tz":-540,"elapsed":485,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["W2 = tf.Variable(tf.random_normal([3,3,32,64], stddev=0.01))\n","L2 = tf.nn.conv2d(L1, W2, strides=[1,1,1,1], padding='SAME')\n","L2 = tf.nn.relu(L2) ## 활성화 함수\n","L2 = tf.nn.max_pool(L2, ksize=[1,2,2,1], strides=[1,2,2,1], padding='SAME')\n","print(L2)"],"execution_count":19,"outputs":[{"output_type":"stream","text":["Tensor(\"MaxPool_1:0\", shape=(?, 8, 8, 64), dtype=float32)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"FuY4TCrd-M-Q","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":36},"outputId":"cd36b318-5575-4bb5-b961-c84baeb1e875","executionInfo":{"status":"ok","timestamp":1569994643829,"user_tz":-540,"elapsed":533,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["W3 = tf.Variable(tf.random_normal([3,3,64,128], stddev=0.01))\n","L3 = tf.nn.conv2d(L2, W3, strides=[1,1,1,1], padding='SAME')\n","L3 = tf.nn.relu(L3) ## 활성화 함수\n","L3 = tf.nn.max_pool(L3, ksize=[1,2,2,1], strides=[1,2,2,1], padding='SAME')\n","print(L3)"],"execution_count":20,"outputs":[{"output_type":"stream","text":["Tensor(\"MaxPool_2:0\", shape=(?, 4, 4, 128), dtype=float32)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"5cEwsq48-Rbv","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":75},"outputId":"b7ab2597-9306-4fd6-df06-fcdee6e1eeb7","executionInfo":{"status":"ok","timestamp":1569994697572,"user_tz":-540,"elapsed":494,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["W4 = tf.Variable(tf.random_normal([4*4*128, 256], stddev=0.01))\n","L4 = tf.reshape(L3, [-1,4*4*128])\n","print(W4, L4)\n","\n","L4 = tf.matmul(L4, W4)\n","L4 = tf.nn.relu(L4)\n","print(L4)"],"execution_count":21,"outputs":[{"output_type":"stream","text":["<tf.Variable 'Variable_3:0' shape=(2048, 256) dtype=float32_ref> Tensor(\"Reshape:0\", shape=(?, 2048), dtype=float32)\n","Tensor(\"Relu_3:0\", shape=(?, 256), dtype=float32)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"96Zc4L5l-ekB","colab_type":"code","colab":{}},"source":["W5 = tf.Variable(tf.random_normal([256,10], stddev=0.01))\n","model = tf.matmul(L4, W5)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"632lwEQS-miB","colab_type":"code","colab":{}},"source":["cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits_v2(logits=model,\n","                                                                 labels=Y))\n","optimizer = tf.train.AdamOptimizer(0.001).minimize(cost)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"utbrlI9o-qIw","colab_type":"code","colab":{}},"source":["init = tf.global_variables_initializer()\n","sess = tf.Session()\n","sess.run(init)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"TMPgUGsW-sHg","colab_type":"code","colab":{}},"source":["batch_size = 100\n","total_batch = int(len(X_train)/ batch_size)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"UA5z-RsF-wyd","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":251},"outputId":"6103cce5-1677-46ab-dd8e-46964a21f2ef","executionInfo":{"status":"error","timestamp":1569996688242,"user_tz":-540,"elapsed":602,"user":{"displayName":"백서연","photoUrl":"","userId":"13608049772715071568"}}},"source":["for e in range(5):\n","  total_cost = 0\n","\n","  for i in range(total_batch):\n","    batch_xs, batch_ys = X_test.next_batch\n","    batch_xs = batch_xs.reshape(-1, 32, 32, 3)\n","    _, cost_val = sess.run([optimizer, cost],\n","                          feed_dict = {X:batch_xs, Y:batch_ys})\n","    total_cost += cost_val\n","\n","  print('Epoch = {}, AVG.cost = {}'. format(e, total_cost / total_batch)),\n"],"execution_count":31,"outputs":[{"output_type":"error","ename":"ValueError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)","\u001b[0;32m<ipython-input-31-724b773750af>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m   \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtotal_batch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m     \u001b[0mbatch_xs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch_ys\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray_split\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbatch_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      6\u001b[0m     \u001b[0mbatch_xs\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbatch_xs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m32\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m32\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m     _, cost_val = sess.run([optimizer, cost],\n","\u001b[0;31mValueError\u001b[0m: too many values to unpack (expected 2)"]}]},{"cell_type":"code","metadata":{"id":"Mj_EUgpU-2fA","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]}]}