Moved line with "from __future__ import" instruction to the top of ea…

…ch notebook Moved line with "from __future__ import" instruction to the top of each notebook where it was not already correctly positioned.
wuqixiaobai · May 2, 2017 · e5453db · e5453db
1 parent 11c967b
commit e5453db
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Showing 11 changed files with 445 additions and 50 deletions.
diff --git a/nbs/char-rnn.ipynb b/nbs/char-rnn.ipynb
@@ -16,11 +16,11 @@
  }
  ],
  "source": [
+ "from __future__ import division, print_function\n",
  "%matplotlib inline\n",
  "from importlib import reload # Python 3\n",
  "import utils; reload(utils)\n",
- "from utils import *\n",
- "from __future__ import division, print_function"
+ "from utils import *"
  ]
  },
  {

diff --git a/nbs/convolution-intro.ipynb b/nbs/convolution-intro.ipynb
@@ -8,6 +8,7 @@
  },
  "outputs": [],
  "source": [
+ "from __future__ import division, print_function\n",
  "%matplotlib inline\n",
  "import math,sys,os,numpy as np\n",
  "from numpy.linalg import norm\n",

diff --git a/nbs/dogs_cats_redux.ipynb b/nbs/dogs_cats_redux.ipynb
@@ -69,6 +69,8 @@
  }
  ],
  "source": [
+ "from __future__ import division, print_function\n",
+ "\n",
  "#Verify we are in the lesson1 directory\n",
  "%pwd"
  ]
@@ -634,7 +636,9 @@
  {
  "cell_type": "code",
  "execution_count": 34,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "from keras.preprocessing import image\n",
@@ -1042,7 +1046,9 @@
  {
  "cell_type": "code",
  "execution_count": 71,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "#So to play it safe, we use a sneaky trick to round down our edge predictions\n",
@@ -1178,7 +1184,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.6.0"
+ "version": "3.5.2"
  },
  "nav_menu": {},
  "nbpresent": {

diff --git a/nbs/dogscats-ensemble.ipynb b/nbs/dogscats-ensemble.ipynb
diff --git a/nbs/imagenet_batchnorm.ipynb b/nbs/imagenet_batchnorm.ipynb
@@ -10,14 +10,16 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
+ "from __future__ import division, print_function\n",
  "%matplotlib inline\n",
  "from importlib import reload\n",
  "import utils; reload(utils)\n",
- "from utils import *\n",
- "from __future__ import print_function, division"
+ "from utils import *"
  ]
  },
  {
@@ -101,7 +103,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "# %pushd data/imagenet\n",
@@ -146,6 +150,7 @@
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
+ "collapsed": true,
  "scrolled": true
  },
  "outputs": [],
@@ -173,7 +178,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "%popd"
@@ -225,7 +232,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "samp_trn = get_data(sample_path+'train')\n",
@@ -260,6 +269,7 @@
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
+ "collapsed": true,
  "scrolled": true
  },
  "outputs": [],
@@ -271,7 +281,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "(samp_val_classes, samp_trn_classes, samp_val_labels, samp_trn_labels, \n",
@@ -381,6 +393,7 @@
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
+ "collapsed": true,
  "scrolled": true
  },
  "outputs": [],
@@ -478,7 +491,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "dense_model.evaluate(samp_conv_val_feat, samp_val_labels)"
@@ -498,7 +513,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "# should be identical to above\n",
@@ -508,7 +525,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "# should be a little better than above, since VGG authors overfit\n",
@@ -639,7 +658,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "bn_model = insert_layer(dense_model, nl2, 5)\n",
@@ -698,7 +719,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "bn_model.evaluate(samp_conv_val_feat, samp_val_labels)"
@@ -707,7 +730,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "bn_model.evaluate(samp_conv_feat, samp_trn_labels)"
@@ -730,7 +755,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "feat_bc = bcolz.open(fast_path+'trn_features.dat')"
@@ -829,7 +856,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "new_layers = copy_layers(bn_model.layers)\n",
@@ -862,7 +891,9 @@
  {
  "cell_type": "code",
  "execution_count": null,
- "metadata": {},
+ "metadata": {
+ "collapsed": true
+ },
  "outputs": [],
  "source": [
  "conv_model.evaluate(samp_val, samp_val_labels)"

diff --git a/nbs/lesson1.ipynb b/nbs/lesson1.ipynb
@@ -52,6 +52,8 @@
  },
  "outputs": [],
  "source": [
+ "from __future__ import division, print_function\n",
+ "\n",
  "%matplotlib inline"
  ]
  },
@@ -89,8 +91,6 @@
  },
  "outputs": [],
  "source": [
- "from __future__ import division,print_function\n",
- "\n",
  "import os, json\n",
  "from glob import glob\n",
  "import numpy as np\n",

diff --git a/nbs/lesson2.ipynb b/nbs/lesson2.ipynb
@@ -23,6 +23,7 @@
  }
  ],
  "source": [
+ "from __future__ import division, print_function\n",
  "# Rather than importing everything manually, we'll make things easy\n",
  "# and load them all in utils.py, and just import them from there.\n",
  "%matplotlib inline\n",
@@ -68,8 +69,6 @@
  },
  "outputs": [],
  "source": [
- "%matplotlib inline\n",
- "from __future__ import division,print_function\n",
  "import os, json\n",
  "from glob import glob\n",
  "import numpy as np\n",
@@ -78,7 +77,6 @@
  "from sklearn.metrics import confusion_matrix\n",
  "np.set_printoptions(precision=4, linewidth=100)\n",
  "from matplotlib import pyplot as plt\n",
- "import utils; reload(utils)\n",
  "from utils import plots, get_batches, plot_confusion_matrix, get_data"
  ]
  },

diff --git a/nbs/lesson3.ipynb b/nbs/lesson3.ipynb
@@ -23,6 +23,7 @@
  }
  ],
  "source": [
+ "from __future__ import division, print_function\n",
  "%matplotlib inline\n",
  "from importlib import reload # Python 3\n",
  "import utils; reload(utils)\n",

diff --git a/nbs/lesson6.ipynb b/nbs/lesson6.ipynb
@@ -16,11 +16,11 @@
  }
  ],
  "source": [
+ "from __future__ import division, print_function\n",
  "%matplotlib inline\n",
  "from importlib import reload # Python 3\n",
  "import utils; reload(utils)\n",
- "from utils import *\n",
- "from __future__ import division, print_function"
+ "from utils import *"
  ]
  },
  {