MultitaskerDataPrep.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"MultitaskerDataPrep.ipynb","provenance":[],"machine_shape":"hm","mount_file_id":"1I3E718F7rKy8coTq1a2p6JloER3sVzJy","authorship_tag":"ABX9TyMIjNjhFHkkIH6xjD5EUX4F"},"kernelspec":{"name":"python3","display_name":"Python 3"},"accelerator":"GPU"},"cells":[{"cell_type":"code","metadata":{"id":"egw6fIdxNi0U","executionInfo":{"status":"ok","timestamp":1614565711873,"user_tz":360,"elapsed":1467,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}}},"source":["import tensorflow as tf\r\n","import numpy as np\r\n","import matplotlib.pyplot as plt"],"execution_count":2,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"bsGVFPIgN5Un","executionInfo":{"status":"ok","timestamp":1614565713356,"user_tz":360,"elapsed":451,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"db806fa4-babb-4fb6-800c-75f761d1998f"},"source":["#Run to check what gpu is being used\r\n","!nvidia-smi"],"execution_count":3,"outputs":[{"output_type":"stream","text":["Mon Mar  1 02:28:34 2021       \n","+-----------------------------------------------------------------------------+\n","| NVIDIA-SMI 460.39       Driver Version: 460.32.03    CUDA Version: 11.2     |\n","|-------------------------------+----------------------+----------------------+\n","| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n","| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n","|                               |                      |               MIG M. |\n","|===============================+======================+======================|\n","|   0  Tesla P100-PCIE...  Off  | 00000000:00:04.0 Off |                    0 |\n","| N/A   38C    P0    27W / 250W |      0MiB / 16280MiB |      0%      Default |\n","|                               |                      |                  N/A |\n","+-------------------------------+----------------------+----------------------+\n","                                                                               \n","+-----------------------------------------------------------------------------+\n","| Processes:                                                                  |\n","|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n","|        ID   ID                                                   Usage      |\n","|=============================================================================|\n","|  No running processes found                                                 |\n","+-----------------------------------------------------------------------------+\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"s6Eg5WjxN7Jh","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1614565715685,"user_tz":360,"elapsed":1418,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"1b85d23d-1365-42ba-abb4-024705990e1f"},"source":["mnist = tf.keras.datasets.mnist\r\n","(x_train, y_train), (x_test, y_test) = mnist.load_data()"],"execution_count":4,"outputs":[{"output_type":"stream","text":["Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz\n","11493376/11490434 [==============================] - 0s 0us/step\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"WpHEWHZtN-Rx","executionInfo":{"status":"ok","timestamp":1614565717175,"user_tz":360,"elapsed":688,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}}},"source":["x_train = tf.keras.utils.normalize(x_train, axis = 1)\r\n","x_test = tf.keras.utils.normalize(x_test, axis = 1)"],"execution_count":5,"outputs":[]},{"cell_type":"code","metadata":{"id":"C4VCRajJN-mi","executionInfo":{"status":"ok","timestamp":1614565719489,"user_tz":360,"elapsed":354,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}}},"source":["#Using grayscale images\r\n","in_channel = 1\r\n","\r\n","img_rows, img_cols = 100, 100\r\n","steps = 550\r\n","num_images = 70000\r\n","num_targets = 4 "],"execution_count":6,"outputs":[]},{"cell_type":"code","metadata":{"id":"ZBCZDSIFOEa1","executionInfo":{"status":"ok","timestamp":1614565733801,"user_tz":360,"elapsed":13262,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}}},"source":["import h5py\r\n","import numpy as np #Numpy again because the dependency from other file\r\n","import pandas as pd\r\n","from sklearn.model_selection import train_test_split\r\n","\r\n","filename = '/content/drive/MyDrive/loadwalks.py'\r\n","exec(open(filename).read())\r\n","\r\n","walk_imgs,count_imgs = read_many_hdf5()\r\n","\r\n","x_train_Walks, x_test_Walks, x_train_Counts, x_test_Counts, y_train_Walks, y_test_Walks = process_loaded_data(img_rows, img_cols,in_channel)"],"execution_count":7,"outputs":[]},{"cell_type":"code","metadata":{"id":"39_KRFCiOMfb","executionInfo":{"status":"ok","timestamp":1614565758146,"user_tz":360,"elapsed":3491,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}}},"source":["x_train_Counts = tf.keras.utils.normalize(x_train_Counts, axis = 1)\r\n","x_test_Counts = tf.keras.utils.normalize(x_test_Counts, axis = 1)"],"execution_count":8,"outputs":[]},{"cell_type":"code","metadata":{"id":"J2dltvYYOPi1","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1614565760268,"user_tz":360,"elapsed":286,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"bb8f6937-611d-4b82-80eb-eed7bcf2648b"},"source":["#Remove in_channel variable since not needed for feedforward network\r\n","x_train_Counts = x_train_Counts.reshape(x_train_Counts.shape[0], img_rows, img_cols)\r\n","x_test_Counts = x_test_Counts.reshape(x_test_Counts.shape[0], img_rows, img_cols)\r\n","\r\n","print(x_train_Counts.shape)\r\n","print(x_test_Counts.shape)"],"execution_count":9,"outputs":[{"output_type":"stream","text":["(60000, 100, 100)\n","(10000, 100, 100)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":283},"id":"Cl-I7s-kf2nj","executionInfo":{"status":"ok","timestamp":1614566216554,"user_tz":360,"elapsed":402,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"da2a1f5e-6f8d-4f3f-c88f-6b1d01479fb3"},"source":["n = 55555\r\n","plt.imshow(x_train[n])\r\n","print(y_train[n])"],"execution_count":23,"outputs":[{"output_type":"stream","text":["[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0.]\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"}}]},{"cell_type":"code","metadata":{"id":"p9FN5NMdOQSs","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1614565768946,"user_tz":360,"elapsed":2853,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"eabe0074-6896-4baa-beb6-2ec0ca74d930"},"source":["h = 36 #precise padding amount\r\n","\r\n","#Loop to fit output shape for multitask net\r\n","for i in range(10):\r\n","  y_train_Walks[5+i] = np.zeros(60000)\r\n","  y_test_Walks[5+i] = np.zeros(10000)\r\n","\r\n","#Pad images to make MNIST data larger\r\n","padded_x_train = np.pad(x_train, h) #New image is 100x100\r\n","padded_x_test = np.pad(x_test, h)\r\n","\r\n","print(padded_x_train.shape)\r\n","print(padded_x_test.shape)"],"execution_count":11,"outputs":[{"output_type":"stream","text":["(60072, 100, 100)\n","(10072, 100, 100)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":286},"id":"z2axg5aif1hv","executionInfo":{"status":"ok","timestamp":1614565778900,"user_tz":360,"elapsed":397,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"c80a269d-0e12-444b-8755-c418e5b2d02a"},"source":["n = 59964\r\n","#padded_x_train = padded_x_train[:-35]\r\n","plt.imshow(padded_x_train[n])\r\n","print(y_train[n])"],"execution_count":12,"outputs":[{"output_type":"stream","text":["3\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"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"oyzKVd8Zf0QO","executionInfo":{"status":"ok","timestamp":1614565794281,"user_tz":360,"elapsed":3008,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"55533956-5bcf-418c-f36c-990c4df8cc7d"},"source":["#Remove additional empty data from beginning and end respectively \r\n","padded_x_train = np.delete(padded_x_train,range(36), axis = 0)\r\n","padded_x_test = np.delete(padded_x_test,range(36), axis = 0)\r\n","padded_x_train = padded_x_train[:-36]\r\n","padded_x_test = padded_x_test[:-36]\r\n","#Verify training dimensions\r\n","print(padded_x_train.shape)\r\n","print(padded_x_test.shape)"],"execution_count":13,"outputs":[{"output_type":"stream","text":["(60000, 100, 100)\n","(10000, 100, 100)\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":304},"id":"znx7tjaWbrZA","executionInfo":{"status":"ok","timestamp":1614565812493,"user_tz":360,"elapsed":328,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"57422181-174e-458c-f97a-bf88d46b92bf"},"source":["plt.imshow(padded_x_train[n])\r\n","print(padded_x_train.shape)\r\n","print(padded_x_test.shape)"],"execution_count":14,"outputs":[{"output_type":"stream","text":["(60000, 100, 100)\n","(10000, 100, 100)\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"}}]},{"cell_type":"code","metadata":{"id":"Hbmj-CmnQvgw","executionInfo":{"status":"ok","timestamp":1614565819559,"user_tz":360,"elapsed":1227,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}}},"source":["from sklearn.preprocessing import OneHotEncoder\r\n","ytrain = y_train.reshape(-1,1)\r\n","ytest = y_test.reshape(-1,1)\r\n","\r\n","y1 = OneHotEncoder().fit_transform(ytrain).toarray()\r\n","y2 = OneHotEncoder().fit_transform(ytest).toarray()\r\n","\r\n","y1.reshape(60000,10)\r\n","y2.reshape(10000,10)\r\n","\r\n","#Extend the MNIST targets by four\r\n","large_ytrain = []\r\n","large_ytest = []\r\n","for i in range(len(y1)):\r\n","  large_ytrain.append(np.insert(y1[i],0,np.zeros(4)))\r\n","for i in range(len(y2)):\r\n","  large_ytest.append(np.insert(y2[i],0,np.zeros(4)))\r\n","\r\n","y_train = np.array(large_ytrain)\r\n","y_test = np.array(large_ytest)"],"execution_count":15,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":304},"id":"MZ5AAQfiaQIF","executionInfo":{"status":"ok","timestamp":1614565828965,"user_tz":360,"elapsed":378,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"ccc95727-f191-4a34-c5ec-813917ead78d"},"source":["print(y_train[n])\r\n","plt.imshow(padded_x_train[n])"],"execution_count":16,"outputs":[{"output_type":"stream","text":["[0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0.]\n"],"name":"stdout"},{"output_type":"execute_result","data":{"text/plain":["<matplotlib.image.AxesImage at 0x7f32681ae710>"]},"metadata":{"tags":[]},"execution_count":16},{"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":"SG8OcMMtT1fg","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1614565836964,"user_tz":360,"elapsed":213,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"9ed5719c-36d9-4671-b406-6e5c1d71a5fb"},"source":["y_train_Walks.shape"],"execution_count":17,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(60000, 14)"]},"metadata":{"tags":[]},"execution_count":17}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"E9SthIXhMhKu","executionInfo":{"status":"ok","timestamp":1614565845062,"user_tz":360,"elapsed":967,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"813360b4-8650-4b34-84d5-6a7abadeee46"},"source":["path = '/content/drive/My Drive/CapstoneWalks/Y_Testing_Data.h5'\r\n","\r\n","filename = '/content/drive/MyDrive/loadwalks.py'\r\n","exec(open(filename).read())\r\n","\r\n","CombineProcessedData(y_test,y_test_Walks,path,1)"],"execution_count":18,"outputs":[{"output_type":"stream","text":["completed\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"af7-D0uOTW-t","executionInfo":{"status":"ok","timestamp":1614565855203,"user_tz":360,"elapsed":8335,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"697e4df7-360e-4a2b-c1f7-3c0091dababe"},"source":["path = '/content/drive/My Drive/CapstoneWalks/X_Testing_Data.h5'\r\n","\r\n","filename = '/content/drive/MyDrive/loadwalks.py'\r\n","exec(open(filename).read())\r\n","\r\n","CombineProcessedData(padded_x_test,x_test_Counts,path,0)"],"execution_count":19,"outputs":[{"output_type":"stream","text":["completed\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"I0NFEj9PTxpH","executionInfo":{"status":"ok","timestamp":1614565860346,"user_tz":360,"elapsed":1655,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"86d19ccc-783c-472a-97d3-bd8ad09d832d"},"source":["path = '/content/drive/My Drive/CapstoneWalks/Y_Train_Data.h5'\r\n","\r\n","filename = '/content/drive/MyDrive/loadwalks.py'\r\n","exec(open(filename).read())\r\n","\r\n","CombineProcessedData(y_train,y_train_Walks,path,1)"],"execution_count":20,"outputs":[{"output_type":"stream","text":["completed\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"dp1yGajIT-mG","executionInfo":{"status":"ok","timestamp":1614565972391,"user_tz":360,"elapsed":108386,"user":{"displayName":"Jack Bressett","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gj8LAu0rdLeGhHZPxw7waI-wjt06PdOC9E6bl_O=s64","userId":"08923683069860490448"}},"outputId":"d90f8138-324e-4643-e7f3-10481ef6b36a"},"source":["path = '/content/drive/My Drive/CapstoneWalks/X_Train_Data.h5'\r\n","\r\n","filename = '/content/drive/MyDrive/loadwalks.py'\r\n","exec(open(filename).read())\r\n","\r\n","CombineProcessedData(padded_x_train,x_train_Counts,path,0)"],"execution_count":21,"outputs":[{"output_type":"stream","text":["completed\n"],"name":"stdout"}]}]}