Fix NNabla Tutorials

doc/python/tutorial.rst

@@ -11,9 +11,10 @@ If you want to run these step-by-step, follow the link and see the instruction f
 
     tutorial/by_examples.rst
     tutorial/python_api.rst
+    tutorial/model_finetuning.rst
+    tutorial/debugging.rst
     tutorial/dynamic_and_static_nn.rst
     tutorial/mixed_precision_training.rst
     tutorial/multi_device_training.rst
-    tutorial/debugging.rst
     tutorial/graph_converter_for_inference.rst
     tutorial/function_list_and_converter.rst

tutorial/README.md

@@ -21,3 +21,18 @@ Then, follow the instruction printed on your terminal to connect the server
 on your browser.
 
 Open the `.ipynb` files to start tutorials.
+
+
+You can also run it directly on [Colab](https://colab.research.google.com/) from the links in the table below.
+
+
+| Name        | Notebook           | Doc  |
+|:------------------------------------------------:|:-------------:|:-----:|
+| NNabla By Examples      | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sony/nnabla/blob/master/tutorial/by_examples.ipynb) | [read](https://nnabla.readthedocs.io/en/latest/python/tutorial/by_examples.html) |
+| NNabla Python API     | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sony/nnabla/blob/master/tutorial/python_api.ipynb) | [read](https://nnabla.readthedocs.io/en/latest/python/tutorial/python_api.html) |
+| Model Finetuning      | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sony/nnabla/blob/master/tutorial/model_finetuning.ipynb) | [read](https://nnabla.readthedocs.io/en/latest/python/tutorial/model_finetuning.html) |
+| Debugging      | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sony/nnabla/blob/master/tutorial/debugging.ipynb) | [read](https://nnabla.readthedocs.io/en/latest/python/tutorial/debugging.html) |
+| Static vs. Dynamic Neural Network in NNabla      | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/sony/nnabla/blob/master/tutorial/dynamic_and_static_nn.ipynb) | [read](https://nnabla.readthedocs.io/en/latest/python/tutorial/dynamic_and_static_nn.html) |
+| Mixed Precision Training      |  | [read](https://nnabla.readthedocs.io/en/latest/python/tutorial/mixed_precision_training.html) |
+| Data Parallel Distributed Training      |  | [read](https://nnabla.readthedocs.io/en/latest/python/tutorial/multi_device_training.html) |
+| Graph Converter for Inference      |  | [read](https://nnabla.readthedocs.io/en/latest/python/tutorial/graph_converter_for_inference.html) |

tutorial/by_examples.ipynb

@@ -28,6 +28,20 @@
     "First let us prepare some dependencies."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# If you run this notebook on Google Colab, uncomment and run the following to set up dependencies.\n",
+    "# !pip install nnabla-ext-cuda100\n",
+    "# !git clone https://github.com/sony/nnabla.git\n",
+    "# %cd nnabla/tutorial"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

tutorial/debugging.ipynb

@@ -29,6 +29,34 @@
     "We will go over each technique, but first prepare the following reference model."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# If you run this notebook on Google Colab, uncomment and run the following to set up dependencies.\n",
+    "# !pip install nnabla-ext-cuda100\n",
+    "# !git clone https://github.com/sony/nnabla.git\n",
+    "# %cd nnabla/tutorial"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# Python2/3 compatibility\n",
+    "from __future__ import print_function\n",
+    "from __future__ import absolute_import\n",
+    "from __future__ import division"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

tutorial/dynamic_and_static_nn.ipynb

@@ -11,6 +11,20 @@
     "This tutorial compares both computation graphs."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# If you run this notebook on Google Colab, uncomment and run the following to set up dependencies.\n",
+    "# !pip install nnabla-ext-cuda100\n",
+    "# !git clone https://github.com/sony/nnabla.git\n",
+    "# %cd nnabla/tutorial"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

tutorial/model_finetuning.ipynb

@@ -9,6 +9,20 @@
     "Here we demonstrate how to perform finetuning using nnabla's pre-trained models."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# If you run this notebook on Google Colab, uncomment and run the following to set up dependencies.\n",
+    "# !pip install nnabla-ext-cuda100\n",
+    "# !git clone https://github.com/sony/nnabla.git\n",
+    "# %cd nnabla/tutorial"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

tutorial/python_api.ipynb

@@ -9,6 +9,20 @@
     "Let us import nnabla first, and some additional useful tools."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# If you run this notebook on Google Colab, uncomment and run the following to set up dependencies.\n",
+    "# !pip install nnabla-ext-cuda100\n",
+    "# !git clone https://github.com/sony/nnabla.git\n",
+    "# %cd nnabla/tutorial"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,