resnet.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ResNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from encoder_decoder_model import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2018-09-09 18:15:55,048 : WARNING : Using the complete data set.\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/lib/python3.6/logging/__init__.py\", line 992, in emit\n",
      "    msg = self.format(record)\n",
      "  File \"/usr/lib/python3.6/logging/__init__.py\", line 838, in format\n",
      "    return fmt.format(record)\n",
      "  File \"/usr/lib/python3.6/logging/__init__.py\", line 575, in format\n",
      "    record.message = record.getMessage()\n",
      "  File \"/usr/lib/python3.6/logging/__init__.py\", line 338, in getMessage\n",
      "    msg = msg % self.args\n",
      "TypeError: not all arguments converted during string formatting\n",
      "Call stack:\n",
      "  File \"/usr/lib/python3.6/runpy.py\", line 193, in _run_module_as_main\n",
      "    \"__main__\", mod_spec)\n",
      "  File \"/usr/lib/python3.6/runpy.py\", line 85, in _run_code\n",
      "    exec(code, run_globals)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel_launcher.py\", line 16, in <module>\n",
      "    app.launch_new_instance()\n",
      "  File \"/usr/lib/python3.6/site-packages/traitlets/config/application.py\", line 658, in launch_instance\n",
      "    app.start()\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/kernelapp.py\", line 477, in start\n",
      "    ioloop.IOLoop.instance().start()\n",
      "  File \"/usr/lib/python3.6/site-packages/zmq/eventloop/ioloop.py\", line 177, in start\n",
      "    super(ZMQIOLoop, self).start()\n",
      "  File \"/usr/lib/python3.6/site-packages/tornado/ioloop.py\", line 888, in start\n",
      "    handler_func(fd_obj, events)\n",
      "  File \"/usr/lib/python3.6/site-packages/tornado/stack_context.py\", line 277, in null_wrapper\n",
      "    return fn(*args, **kwargs)\n",
      "  File \"/usr/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py\", line 440, in _handle_events\n",
      "    self._handle_recv()\n",
      "  File \"/usr/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py\", line 472, in _handle_recv\n",
      "    self._run_callback(callback, msg)\n",
      "  File \"/usr/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py\", line 414, in _run_callback\n",
      "    callback(*args, **kwargs)\n",
      "  File \"/usr/lib/python3.6/site-packages/tornado/stack_context.py\", line 277, in null_wrapper\n",
      "    return fn(*args, **kwargs)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/kernelbase.py\", line 283, in dispatcher\n",
      "    return self.dispatch_shell(stream, msg)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/kernelbase.py\", line 235, in dispatch_shell\n",
      "    handler(stream, idents, msg)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/kernelbase.py\", line 399, in execute_request\n",
      "    user_expressions, allow_stdin)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/ipkernel.py\", line 196, in do_execute\n",
      "    res = shell.run_cell(code, store_history=store_history, silent=silent)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/zmqshell.py\", line 533, in run_cell\n",
      "    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n",
      "  File \"/usr/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2728, in run_cell\n",
      "    interactivity=interactivity, compiler=compiler, result=result)\n",
      "  File \"/usr/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2850, in run_ast_nodes\n",
      "    if self.run_code(code, result):\n",
      "  File \"/usr/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2910, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-2-e8a56c5ddf16>\", line 1, in <module>\n",
      "    model = EncoderDecoderModel()\n",
      "  File \"/home/two-a-day/research/bioinformatics/pneumonia-detection/encoder_decoder_model.py\", line 48, in __init__\n",
      "    self.load_data()\n",
      "  File \"/home/two-a-day/research/bioinformatics/pneumonia-detection/encoder_decoder_model.py\", line 132, in load_data\n",
      "    logging.info('n train samples', len(self.train_filenames))\n",
      "Message: 'n train samples'\n",
      "Arguments: (23124,)\n",
      "--- Logging error ---\n",
      "Traceback (most recent call last):\n",
      "  File \"/usr/lib/python3.6/logging/__init__.py\", line 992, in emit\n",
      "    msg = self.format(record)\n",
      "  File \"/usr/lib/python3.6/logging/__init__.py\", line 838, in format\n",
      "    return fmt.format(record)\n",
      "  File \"/usr/lib/python3.6/logging/__init__.py\", line 575, in format\n",
      "    record.message = record.getMessage()\n",
      "  File \"/usr/lib/python3.6/logging/__init__.py\", line 338, in getMessage\n",
      "    msg = msg % self.args\n",
      "TypeError: not all arguments converted during string formatting\n",
      "Call stack:\n",
      "  File \"/usr/lib/python3.6/runpy.py\", line 193, in _run_module_as_main\n",
      "    \"__main__\", mod_spec)\n",
      "  File \"/usr/lib/python3.6/runpy.py\", line 85, in _run_code\n",
      "    exec(code, run_globals)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel_launcher.py\", line 16, in <module>\n",
      "    app.launch_new_instance()\n",
      "  File \"/usr/lib/python3.6/site-packages/traitlets/config/application.py\", line 658, in launch_instance\n",
      "    app.start()\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/kernelapp.py\", line 477, in start\n",
      "    ioloop.IOLoop.instance().start()\n",
      "  File \"/usr/lib/python3.6/site-packages/zmq/eventloop/ioloop.py\", line 177, in start\n",
      "    super(ZMQIOLoop, self).start()\n",
      "  File \"/usr/lib/python3.6/site-packages/tornado/ioloop.py\", line 888, in start\n",
      "    handler_func(fd_obj, events)\n",
      "  File \"/usr/lib/python3.6/site-packages/tornado/stack_context.py\", line 277, in null_wrapper\n",
      "    return fn(*args, **kwargs)\n",
      "  File \"/usr/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py\", line 440, in _handle_events\n",
      "    self._handle_recv()\n",
      "  File \"/usr/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py\", line 472, in _handle_recv\n",
      "    self._run_callback(callback, msg)\n",
      "  File \"/usr/lib/python3.6/site-packages/zmq/eventloop/zmqstream.py\", line 414, in _run_callback\n",
      "    callback(*args, **kwargs)\n",
      "  File \"/usr/lib/python3.6/site-packages/tornado/stack_context.py\", line 277, in null_wrapper\n",
      "    return fn(*args, **kwargs)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/kernelbase.py\", line 283, in dispatcher\n",
      "    return self.dispatch_shell(stream, msg)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/kernelbase.py\", line 235, in dispatch_shell\n",
      "    handler(stream, idents, msg)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/kernelbase.py\", line 399, in execute_request\n",
      "    user_expressions, allow_stdin)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/ipkernel.py\", line 196, in do_execute\n",
      "    res = shell.run_cell(code, store_history=store_history, silent=silent)\n",
      "  File \"/usr/lib/python3.6/site-packages/ipykernel/zmqshell.py\", line 533, in run_cell\n",
      "    return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)\n",
      "  File \"/usr/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2728, in run_cell\n",
      "    interactivity=interactivity, compiler=compiler, result=result)\n",
      "  File \"/usr/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2850, in run_ast_nodes\n",
      "    if self.run_code(code, result):\n",
      "  File \"/usr/lib/python3.6/site-packages/IPython/core/interactiveshell.py\", line 2910, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-2-e8a56c5ddf16>\", line 1, in <module>\n",
      "    model = EncoderDecoderModel()\n",
      "  File \"/home/two-a-day/research/bioinformatics/pneumonia-detection/encoder_decoder_model.py\", line 48, in __init__\n",
      "    self.load_data()\n",
      "  File \"/home/two-a-day/research/bioinformatics/pneumonia-detection/encoder_decoder_model.py\", line 133, in load_data\n",
      "    logging.info('n valid samples', len(self.valid_filenames))\n",
      "Message: 'n valid samples'\n",
      "Arguments: (2560,)\n",
      "2018-09-09 18:15:55,053 : INFO : Loaded data, 23124 training samples.\n"
     ]
    }
   ],
   "source": [
    "model = EncoderDecoderModel(nb_epochs=15) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA1gAAAJRCAYAAABY5xbUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEYkSFSwREREREZEo+f9T+YOicUEgUQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa49193ee48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Epoch 00005: ReduceLROnPlateau reducing learning rate to 0.00010000000474974513.\n",
      "Epoch 6/10\n",
      "  91/1445 [>.............................] - ETA: 11:23 - loss: 0.4589 - acc: 0.9667 - mean_iou: 0.6153"
     ]
    }
   ],
   "source": [
    "model.train()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.generate_submission()"
   ]
  }
 ],
 "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": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}