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Doc: Nano installation panel (#6852)

Browse source 
* add nano installation panel

* try fix

* try fix again

* fix typo

* add versions

* try fix second

* try fix second again

* fix col width

* rollback

* rollback again

* fix syntax error

* fix syntax error again

* fix syntax error last

* fix syntax

* fix syntax

* fix syntax again

* add some comment

* try fix

* try fix

* try fix again

* try fix

* fix typo

* fix some error

* fix typo

* some optimization

* change width

* change width again

* change width again

* change width again

* last width change

* fix description error

* change inference default to yes

* switch inferenceyes and inferenceno
This commit is contained in:
liangs6212 2022-12-07 14:30:11 +08:00 committed by GitHub
parent b96d39db4a
commit ae7160790d
3 changed files with 275 additions and 15 deletions
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52
docs/readthedocs/source/_static/css/nano_installation_guide.css Normal file
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@ -0,0 +1,52 @@
.displayed {
display: block;
text-align: center;
margin-left: auto;
margin-right: auto;
}
#table-1 {
border-bottom-width: 0px;
margin:auto;
}
#table-1 tr, td{
background-color: var(--pst-color-on-surface);
height: 30px;
border-width: 2px;
border-style: solid;
border-color: white ;
padding: 5px;
}
#table-1 tr td:first-child{
font-weight: 600;
}
#table-1 td{
font-size: 16px;
font-family: Verdana;
color: var(--pst-color-text-base);
text-align: center;
/* height: 56px;
line-height: 56px; */
width: 160px;
}
#table-1 button {
font-size: 16px;
border-color: transparent;
width: 100%;
height: 100%;
background-color: transparent;
cursor: pointer;
}
#table-1 #cmd {
height: 2em;
text-align: left;
}
#table-1 .taller_tr {
height: 71px;
}

177
docs/readthedocs/source/_static/js/nano_installation_guide.js Normal file
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@ -0,0 +1,177 @@
var inferences=["inferenceyes", "inferenceno"];
var frameworks=["pytorch", "tensorflow"];
var versions=["pytorch_110", "pytorch_111", "pytorch_112", "pytorch_113", "tf2_270"];
var releases=["stable", "nightly"];
var inference="inferenceyes";
var framework="pytorch";
var version="pytorch_112";
var release="nightly";
function refresh_cmd(){
reset_color(frameworks);
reset_color(inferences);
reset_color(releases);
set_color(framework);
set_color(inference);
set_color(release);
var cmd="NA";
$("#version").empty();
if(framework=="pytorch"){
$("#version").append("<td colspan='1'>Pytorch Version</td>\
<td colspan='1'><button id='pytorch_113'>1.13</button></td>\
<td colspan='1'><button id='pytorch_112'>1.12</button></td>\
<td colspan='1'><button id='pytorch_111'>1.11</button></td>\
<td colspan='1'><button id='pytorch_110'>1.10</button></td>");
}
else if(framework=="tensorflow"){
$("#version").append("<td colspan='1'>Tensorflow Version</td>\
<td colspan='4'><button id='tf2_270'>2.7</button></td>");
}
reset_color(versions);
set_color(version);
if(release!="nightly"){
disable(versions);
disable(inferences);
}
else{
enable(versions);
enable(inferences);
}
if (framework=="pytorch"){
document.getElementById("cmd").style.whiteSpace = "normal";
}
else{
document.getElementById('cmd').style.whiteSpace = "nowrap";
}
if(framework=="pytorch"){
if(release=="stable"){
cmd="pip install bigdl-nano[pytorch]==2.1.0";
}else if(release=="nightly"){
if(inference=="inferenceyes"){
if(version=="pytorch_110"){
cmd="pip install --pre --upgrade bigdl-nano[pytorch_110,inference]";
}else if(version=="pytorch_111"){
cmd="pip install --pre --upgrade bigdl-nano[pytorch_111,inference]";
}else if(version=="pytorch_112"){
cmd="pip install --pre --upgrade bigdl-nano[pytorch,inference]";
}else if(version=="pytorch_113"){
cmd="pip install --pre --upgrade bigdl-nano[pytorch_113,inference] pip install neural_compressor==1.14";
}
}else if(inference="inferenceno"){
if(version=="pytorch_110"){
cmd="pip install --pre --upgrade bigdl-nano[pytorch_110]";
}else if(version=="pytorch_111"){
cmd="pip install --pre --upgrade bigdl-nano[pytorch_111]";
}else if(version=="pytorch_112"){
cmd="pip install --pre --upgrade bigdl-nano[pytorch]";
}else if(version=="pytorch_113"){
cmd="pip install --pre --upgrade bigdl-nano[pytorch_113]";
}
}
}
}else if(framework="tensorflow"){
if(inference=="inferenceyes"){
if (version=="tf2_270"){
if (release=="nightly"){
cmd="pip install --pre --upgrade bigdl-nano[tensorflow,inference]";
}else if(release=="stable"){
cmd="pip install bigdl-nano[tensorflow]==2.1.0";
}
}
}else if(inference=="inferenceno"){
if(version=="tf2_270"){
if(release=="nightly"){
cmd="pip install --pre --upgrade bigdl-nano[tensorflow]";
}else if(release=="stable"){
cmd="pip install bigdl-nano[tensorflow]==2.1.0";
}
}
}
}
$("#cmd").html(cmd);
}
function set_color(id){
$("#"+id).parent().css("background-color","var(--pst-color-primary)");
$("#"+id).css("color","var(--pst-color-primary-text)");
$("#"+id).addClass("isset");
}
//reset the color of unselected buttons
function reset_color(list){
for (btn in list){
$("#"+list[btn]).parent().css("background-color","transparent");
$("#"+list[btn]).css("color","var(--pst-color-text-base)");
$("#"+list[btn]).removeClass("isset");
}
}
//disable buttons
function disable(list){
for(btn in list){
$("#"+list[btn]).css("text-decoration","line-through");
$("#"+list[btn]).attr("disabled","true");
}
reset_color(list);
for(btn in list){
$("#"+list[btn]).parent().css("background-color","var(--pst-color-muted)");
}
}
//enable buttons
function enable(list){
for(btn in list){
$("#"+list[btn]).css("text-decoration","none");
$("#"+list[btn]).attr("disabled",false);
}
}
//when clicked a button, update variables
$(document).on('click',"button",function(){
var id = $(this).attr("id");
if (frameworks.indexOf(id)>=0){
framework=id;
if (framework=="tensorflow"){
version="tf2_270";
}else{
version="pytorch_112";
}
}
else if (releases.indexOf(id)>=0){
release=id;
}
else if (inferences.indexOf(id)>=0){
inference=id;
}
else if (versions.indexOf(id)>=0){
version=id;
}
refresh_cmd();
})
//func to add button hover effect
$(document).on({
mouseenter: function () {
if($(this).prop("disabled")!=true){
$(this).parent().css("background-color","var(--pst-color-primary)");
$(this).css("color","var(--pst-color-primary-text)");
}
},
mouseleave: function () {
if(!$(this).hasClass("isset") && $(this).prop("disabled")!=true){
$(this).parent().css("background-color","transparent");
$(this).css("color","var(--pst-color-text-base)");
}
}
}, "button");
refresh_cmd();

61
docs/readthedocs/source/doc/Nano/Overview/install.md
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@ -5,20 +5,48 @@ Note: For windows users, we recommend using Windows Subsystem for Linux 2 (WSL2)
BigDL-Nano can be installed using pip and we recommend installing BigDL-Nano in a conda environment.
For PyTorch Users, you can install bigdl-nano along with some dependencies specific to PyTorch using the following commands.
You can select bigdl-nano along with some dependencies specific to PyTorch or Tensorflow using the following panel.
```bash
conda create -n env
conda activate env
pip install --pre --upgrade bigdl-nano[pytorch]
```
```eval_rst
.. raw:: html
For TensorFlow users, you can install bigdl-nano along with some dependencies specific to TensorFlow using the following commands.
<link rel="stylesheet" type="text/css" href="../../../_static/css/nano_installation_guide.css" />
```bash
conda create -n env
conda activate env
pip install --pre --upgrade bigdl-nano[tensorflow]
<div class="displayed">
<table id="table-1">
<tbody>
<tr>
<td colspan="1">FrameWork</td>
<td colspan="2"><button id="pytorch">Pytorch</button></td>
<td colspan="2"><button id="tensorflow">Tensorflow</button></td>
</tr>
<tr id="version" class="taller_tr">
<td colspan="1">Version</td>
<td colspan="1"><button id="pytorch_113">1.13</button></td>
<td colspan="1"><button id="pytorch_112">1.12</button></td>
<td colspan="1"><button id="pytorch_111">1.11</button></td>
<td colspan="1"><button id="pytorch_110">1.10</button></td>
</tr>
<tr>
<td colspan="1">Inference Optimization</td>
<td colspan="2"><button id="inferenceyes">Yes</button></td>
<td colspan="2"><button id="inferenceno">No</button></td>
</td>
</tr>
<tr>
<td colspan="1">Release</td>
<td colspan="2"><button id="nightly">Nightly</button></td>
<td colspan="2"><button id="stable">Stable</button></td>
</tr>
<tr class="tallet_tr">
<td colspan="1">Install CMD</td>
<td colspan="4" id="cmd">NA</td>
</tr>
</tbody>
</table>
</div>
<script src="../../../_static/js/nano_installation_guide.js"></script>
```
We also partially support M-series chip users with no guarantee of acceleration with same API. Currently only tensorflow is experimentally supported.
@ -37,16 +65,19 @@ pip install --pre --upgrade bigdl-nano[tensorflow]
For stable version, please refer to the document and installation guide `here <https://bigdl.readthedocs.io/en/v2.1.0/doc/Nano/Overview/nano.html>`_ .
```
After installing bigdl-nano, you can run the following command to setup a few environment variables.
```bash
conda create -n env
conda activate env
# select your preference in above panel to find the proper command to replace the below command, e.g.
pip install --pre --upgrade bigdl-chronos[pytorch]
# after installing bigdl-nano, you can run the following command to setup a few environment variables.
source bigdl-nano-init
```
The `bigdl-nano-init` scripts will export a few environment variable according to your hardware to maximize performance.
In a conda environment, `source bigdl-nano-init` will also be added to `$CONDA_PREFIX/etc/conda/activate.d/`, which will automaticly run when you activate your current environment.
In a conda environment, when you run `source bigdl-nano-init` manually, this command will also be added to `$CONDA_PREFIX/etc/conda/activate.d/`, which will automaticly run when you activate your current environment.
In a pure pip environment, you need to run `source bigdl-nano-init` every time you open a new shell to get optimal performance and run `source bigdl-nano-unset-env` if you want to unset these environment variables.
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