diff --git a/docs-src/docs/jupyter.md b/docs-src/docs/jupyter.md
index 6e4e08222bb90e9050a3aaccf84f61e8d5ccb4dc..e6e4add6fa55af2fdd6e5e4380ad71cab15b14a7 100755
--- a/docs-src/docs/jupyter.md
+++ b/docs-src/docs/jupyter.md
@@ -22,7 +22,7 @@ $ jupyter nbextension enable --py --sys-prefix qgrid
There are all kinds of options to use when launching Jupyter which you can use. The example below tells the server to listen to connections from any IP address, and not to launch the browser window, but of course, you are free to launch Jupyter any way you want.<br>
Consult the [user's guide](http://jupyter.readthedocs.io/en/latest/running.html) for more details.
```
-$ jupyter-notebook --ip=* --no-browser
+$ jupyter-notebook --ip=0.0.0.0 --no-browser
```
## Using the Distiller notebooks
diff --git a/docs/index.html b/docs/index.html
index a498037f7ee1e5bee76d2caeccc2c112c5f4bb8c..51682aea0274063b195a7d2cb73ac76946444f2f 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -250,5 +250,5 @@ And of course, if we used a sparse or compressed representation, then we are red
<!--
MkDocs version : 0.17.2
-Build Date UTC : 2018-09-16 14:12:27
+Build Date UTC : 2018-10-03 17:13:40
-->
diff --git a/docs/jupyter/index.html b/docs/jupyter/index.html
index 56da7227e4704d202fbe3f28afb151c47eec7bef..35cbe13246aa3f1ce964236b09fa345c0834f0e7 100644
--- a/docs/jupyter/index.html
+++ b/docs/jupyter/index.html
@@ -186,7 +186,7 @@ However, to use the ipywidgets extension, you will need to enable it:</p>
<h2 id="launching-the-jupyter-server">Launching the Jupyter server</h2>
<p>There are all kinds of options to use when launching Jupyter which you can use. The example below tells the server to listen to connections from any IP address, and not to launch the browser window, but of course, you are free to launch Jupyter any way you want.<br>
Consult the <a href="http://jupyter.readthedocs.io/en/latest/running.html">user's guide</a> for more details.</p>
-<pre><code>$ jupyter-notebook --ip=* --no-browser
+<pre><code>$ jupyter-notebook --ip=0.0.0.0 --no-browser
</code></pre>
<h2 id="using-the-distiller-notebooks">Using the Distiller notebooks</h2>
diff --git a/docs/search/search_index.json b/docs/search/search_index.json
index dc45075775aacf7d5a96eb7f79d2c7736204043c..04ede462541c8edec2d14fceb4fc4a87df5c59dc 100644
--- a/docs/search/search_index.json
+++ b/docs/search/search_index.json
@@ -517,7 +517,7 @@
},
{
"location": "/jupyter/index.html",
- "text": "Jupyter environment\n\n\nThe Jupyter notebooks environment allows us to plan our compression session and load Distiller data summaries to study and analyze compression results.\n\n\nEach notebook has embedded instructions and explanations, so here we provide only a brief description of each notebook.\n\n\nInstallation\n\n\nJupyter and its dependencies are included as part of the main \nrequirements.txt\n file, so there is no need for a dedicated installation step.\n\nHowever, to use the ipywidgets extension, you will need to enable it:\n\n\n$ jupyter nbextension enable --py widgetsnbextension --sys-prefix\n\n\n\n\nYou may want to refer to the \nipywidgets extension installation documentation\n.\n\n\nAnother extension which requires special installation handling is \nQgrid\n. Qgrid is a Jupyter notebook widget that adds interactive features, such as sorting, to Panadas DataFrames rendering. To enable Qgrid:\n\n\n$ jupyter nbextension enable --py --sys-prefix qgrid\n\n\n\n\nLaunching the Jupyter server\n\n\nThere are all kinds of options to use when launching Jupyter which you can use. The example below tells the server to listen to connections from any IP address, and not to launch the browser window, but of course, you are free to launch Jupyter any way you want.\n\nConsult the \nuser's guide\n for more details.\n\n\n$ jupyter-notebook --ip=* --no-browser\n\n\n\n\nUsing the Distiller notebooks\n\n\nThe Distiller Jupyter notebooks are located in the \ndistiller/jupyter\n directory.\n\nThey are provided as tools that you can use to prepare your compression experiments and study their results.\nWe welcome new ideas and implementations of Jupyter.\n\n\nRoughly, the notebooks can be divided into three categories.\n\n\nTheory\n\n\n\n\njupyter/L1-regularization.ipynb\n: Experience hands-on how L1 and L2 regularization affect the solution of a toy loss-minimization problem, to get a better grasp on the interaction between regularization and sparsity.\n\n\njupyter/alexnet_insights.ipynb\n: This notebook reviews and compares a couple of pruning sessions on Alexnet. We compare distributions, performance, statistics and show some visualizations of the weights tensors.\n\n\n\n\nPreparation for compression\n\n\n\n\njupyter/model_summary.ipynb\n: Begin by getting familiar with your model. Examine the sizes and properties of layers and connections. Study which layers are compute-bound, and which are bandwidth-bound, and decide how to prune or regularize the model.\n\n\njupyter/sensitivity_analysis.ipynb\n: If you performed pruning sensitivity analysis on your model, this notebook can help you load the results and graphically study how the layers behave.\n\n\njupyter/interactive_lr_scheduler.ipynb\n: The learning rate decay policy affects pruning results, perhaps as much as it affects training results. Graph a few LR-decay policies to see how they behave.\n\n\njupyter/jupyter/agp_schedule.ipynb\n: If you are using the Automated Gradual Pruner, this notebook can help you tune the schedule.\n\n\n\n\nReviewing experiment results\n\n\n\n\njupyter/compare_executions.ipynb\n: This is a simple notebook to help you graphically compare the results of executions of several experiments.\n\n\njupyter/compression_insights.ipynb\n: This notebook is packed with code, tables and graphs to us understand the results of a compression session. Distiller provides \nsummaries\n, which are Pandas dataframes, which contain statistical information about you model. We chose to use Pandas dataframes because they can be sliced, queried, summarized and graphed with a few lines of code.",
+ "text": "Jupyter environment\n\n\nThe Jupyter notebooks environment allows us to plan our compression session and load Distiller data summaries to study and analyze compression results.\n\n\nEach notebook has embedded instructions and explanations, so here we provide only a brief description of each notebook.\n\n\nInstallation\n\n\nJupyter and its dependencies are included as part of the main \nrequirements.txt\n file, so there is no need for a dedicated installation step.\n\nHowever, to use the ipywidgets extension, you will need to enable it:\n\n\n$ jupyter nbextension enable --py widgetsnbextension --sys-prefix\n\n\n\n\nYou may want to refer to the \nipywidgets extension installation documentation\n.\n\n\nAnother extension which requires special installation handling is \nQgrid\n. Qgrid is a Jupyter notebook widget that adds interactive features, such as sorting, to Panadas DataFrames rendering. To enable Qgrid:\n\n\n$ jupyter nbextension enable --py --sys-prefix qgrid\n\n\n\n\nLaunching the Jupyter server\n\n\nThere are all kinds of options to use when launching Jupyter which you can use. The example below tells the server to listen to connections from any IP address, and not to launch the browser window, but of course, you are free to launch Jupyter any way you want.\n\nConsult the \nuser's guide\n for more details.\n\n\n$ jupyter-notebook --ip=0.0.0.0 --no-browser\n\n\n\n\nUsing the Distiller notebooks\n\n\nThe Distiller Jupyter notebooks are located in the \ndistiller/jupyter\n directory.\n\nThey are provided as tools that you can use to prepare your compression experiments and study their results.\nWe welcome new ideas and implementations of Jupyter.\n\n\nRoughly, the notebooks can be divided into three categories.\n\n\nTheory\n\n\n\n\njupyter/L1-regularization.ipynb\n: Experience hands-on how L1 and L2 regularization affect the solution of a toy loss-minimization problem, to get a better grasp on the interaction between regularization and sparsity.\n\n\njupyter/alexnet_insights.ipynb\n: This notebook reviews and compares a couple of pruning sessions on Alexnet. We compare distributions, performance, statistics and show some visualizations of the weights tensors.\n\n\n\n\nPreparation for compression\n\n\n\n\njupyter/model_summary.ipynb\n: Begin by getting familiar with your model. Examine the sizes and properties of layers and connections. Study which layers are compute-bound, and which are bandwidth-bound, and decide how to prune or regularize the model.\n\n\njupyter/sensitivity_analysis.ipynb\n: If you performed pruning sensitivity analysis on your model, this notebook can help you load the results and graphically study how the layers behave.\n\n\njupyter/interactive_lr_scheduler.ipynb\n: The learning rate decay policy affects pruning results, perhaps as much as it affects training results. Graph a few LR-decay policies to see how they behave.\n\n\njupyter/jupyter/agp_schedule.ipynb\n: If you are using the Automated Gradual Pruner, this notebook can help you tune the schedule.\n\n\n\n\nReviewing experiment results\n\n\n\n\njupyter/compare_executions.ipynb\n: This is a simple notebook to help you graphically compare the results of executions of several experiments.\n\n\njupyter/compression_insights.ipynb\n: This notebook is packed with code, tables and graphs to us understand the results of a compression session. Distiller provides \nsummaries\n, which are Pandas dataframes, which contain statistical information about you model. We chose to use Pandas dataframes because they can be sliced, queried, summarized and graphed with a few lines of code.",
"title": "Jupyter notebooks"
},
{
@@ -532,7 +532,7 @@
},
{
"location": "/jupyter/index.html#launching-the-jupyter-server",
- "text": "There are all kinds of options to use when launching Jupyter which you can use. The example below tells the server to listen to connections from any IP address, and not to launch the browser window, but of course, you are free to launch Jupyter any way you want. \nConsult the user's guide for more details. $ jupyter-notebook --ip=* --no-browser",
+ "text": "There are all kinds of options to use when launching Jupyter which you can use. The example below tells the server to listen to connections from any IP address, and not to launch the browser window, but of course, you are free to launch Jupyter any way you want. \nConsult the user's guide for more details. $ jupyter-notebook --ip=0.0.0.0 --no-browser",
"title": "Launching the Jupyter server"
},
{
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
index 8e744cbd96c2f2ca93c3ef61bc589aab6c39aa70..3e57f31dbb50ef61acf0413ce765a70b40a3ef16 100644
--- a/docs/sitemap.xml
+++ b/docs/sitemap.xml
@@ -4,7 +4,7 @@
<url>
<loc>/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
@@ -12,7 +12,7 @@
<url>
<loc>/install/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
@@ -20,7 +20,7 @@
<url>
<loc>/usage/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
@@ -28,7 +28,7 @@
<url>
<loc>/schedule/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
@@ -37,25 +37,25 @@
<url>
<loc>/pruning/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
<url>
<loc>/regularization/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
<url>
<loc>/quantization/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
<url>
<loc>/knowledge_distillation/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
@@ -65,13 +65,13 @@
<url>
<loc>/algo_pruning/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
<url>
<loc>/algo_quantization/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
@@ -80,7 +80,7 @@
<url>
<loc>/model_zoo/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
@@ -88,7 +88,7 @@
<url>
<loc>/jupyter/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>
@@ -96,7 +96,7 @@
<url>
<loc>/design/index.html</loc>
- <lastmod>2018-09-16</lastmod>
+ <lastmod>2018-10-03</lastmod>
<changefreq>daily</changefreq>
</url>