fastai

trizko · Aug 21, 2020 · efff962 · efff962
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diff --git a/01_intro.ipynb b/01_intro.ipynb
@@ -568,7 +568,7 @@
     "#id first_training\n",
     "#caption Results from the first training\n",
     "# CLICK ME\n",
-    "from fastai2.vision.all import *\n",
+    "from fastai.vision.all import *\n",
     "path = untar_data(URLs.PETS)/'images'\n",
     "\n",
     "def is_cat(x): return x[0].isupper()\n",
@@ -1473,7 +1473,7 @@
     "The first line imports all of the fastai.vision library.\n",
     "\n",
     "```python\n",
-    "from fastai2.vision.all import *\n",
+    "from fastai.vision.all import *\n",
     "```\n",
     "\n",
     "This gives us all of the functions and classes we will need to create a wide variety of computer vision models."
@@ -2156,7 +2156,7 @@
     }
    ],
    "source": [
-    "from fastai2.text.all import *\n",
+    "from fastai.text.all import *\n",
     "\n",
     "dls = TextDataLoaders.from_folder(untar_data(URLs.IMDB), valid='test')\n",
     "learn = text_classifier_learner(dls, AWD_LSTM, drop_mult=0.5, metrics=accuracy)\n",
@@ -2171,7 +2171,7 @@
     "If you hit a \"CUDA out of memory error\" after running this cell, click on the menu Kernel, then restart. Instead of executing the cell above, copy and paste the following code in it:\n",
     "\n",
     "```\n",
-    "from fastai2.text.all import *\n",
+    "from fastai.text.all import *\n",
     "\n",
     "dls = TextDataLoaders.from_folder(untar_data(URLs.IMDB), valid='test', bs=32)\n",
     "learn = text_classifier_learner(dls, AWD_LSTM, drop_mult=0.5, metrics=accuracy)\n",
@@ -2241,7 +2241,7 @@
     "In a Jupyter notebook, the order in which you execute each cell is very important. It's not like Excel, where everything gets updated as soon as you type something anywhere—it has an inner state that gets updated each time you execute a cell. For instance, when you run the first cell of the notebook (with the \"CLICK ME\" comment), you create an object called `learn` that contains a model and data for an image classification problem. If we were to run the cell just shown in the text (the one that predicts if a review is good or not) straight after, we would get an error as this `learn` object does not contain a text classification model. This cell needs to be run after the one containing:\n",
     "\n",
     "```python\n",
-    "from fastai2.text.all import *\n",
+    "from fastai.text.all import *\n",
     "\n",
     "dls = TextDataLoaders.from_folder(untar_data(URLs.IMDB), valid='test')\n",
     "learn = text_classifier_learner(dls, AWD_LSTM, drop_mult=0.5, \n",
@@ -2307,7 +2307,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from fastai2.tabular.all import *\n",
+    "from fastai.tabular.all import *\n",
     "path = untar_data(URLs.ADULT_SAMPLE)\n",
     "\n",
     "dls = TabularDataLoaders.from_csv(path/'adult.csv', path=path, y_names=\"salary\",\n",
@@ -2516,7 +2516,7 @@
     }
    ],
    "source": [
-    "from fastai2.collab import *\n",
+    "from fastai.collab import *\n",
     "path = untar_data(URLs.ML_SAMPLE)\n",
     "dls = CollabDataLoaders.from_csv(path/'ratings.csv')\n",
     "learn = collab_learner(dls, y_range=(0.5,5.5))\n",
@@ -2932,6 +2932,31 @@
    "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": "3.7.7"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": false,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
   }
  },
  "nbformat": 4,

diff --git a/02_production.ipynb b/02_production.ipynb
@@ -20,7 +20,7 @@
    "source": [
     "#hide\n",
     "from fastbook import *\n",
-    "from fastai2.vision.widgets import *"
+    "from fastai.vision.widgets import *"
    ]
   },
   {
@@ -1976,6 +1976,31 @@
    "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": "3.7.7"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": false,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
   }
  },
  "nbformat": 4,

diff --git a/03_ethics.ipynb b/03_ethics.ipynb
@@ -1054,6 +1054,31 @@
    "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": "3.7.7"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": false,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
   }
  },
  "nbformat": 4,

diff --git a/04_mnist_basics.ipynb b/04_mnist_basics.ipynb
@@ -19,7 +19,7 @@
    "outputs": [],
    "source": [
     "#hide\n",
-    "from fastai2.vision.all import *\n",
+    "from fastai.vision.all import *\n",
     "from fastbook import *\n",
     "\n",
     "matplotlib.rc('image', cmap='Greys')"
@@ -5856,6 +5856,31 @@
    "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": "3.7.7"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": false,
+   "sideBar": true,
+   "skip_h1_title": true,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {},
+   "toc_section_display": true,
+   "toc_window_display": false
   }
  },
  "nbformat": 4,