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[Doc] Change the description for pip packages #12584

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[Doc] Change the description for pip packages #12584

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fix doc
TaoLv Sep 18, 2018
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TaoLv Sep 18, 2018
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fix comment
TaoLv Sep 19, 2018
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Merge branch 'master' of https://github.com/apache/incubator-mxnet in…
TaoLv Sep 19, 2018
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36 changes: 30 additions & 6 deletions docs/install/index.md
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Expand Up @@ -141,11 +141,17 @@ $ pip install mxnet --pre

</div> <!-- End of master-->
<hr> <!-- pip footer -->
Most MXNet versions offer an experimental MKL pip package that will be much faster when running on Intel hardware.
Check the chart below for other options, refer to <a href="https://pypi.org/project/mxnet/">PyPI for other MXNet pip packages</a>, or <a href="validate_mxnet.html">validate your MXNet installation</a>.
MXNet offers MKL pip packages that will be much faster when running on Intel hardware.
Check the chart below for other options, refer to <a href="https://pypi.org/project/mxnet/">PyPI for other MXNet pip packages</a>, or <a href="validate_mxnet.html">validate your MXNet installation</a>.

<img src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/install/pip-packages-1.3.0.png" alt="pip packages"/>

**NOTES:**

*mxnet-cu92mkl* means the package is built with CUDA/cuDNN and MKL-DNN enabled and the CUDA version is 9.2.

MKL pip package is experimental in some old versions of MXNet.
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Wouldn't it be more accurate to say "All MKL pip packages are experimental prior to version x.y.z."

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I'm not sure. But I think MKL pip packages should once be GA in some old versions, before it's changed to MKL-DNN backend. @szha May I have your comments?

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@szha szha Sep 19, 2018 •
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the pip packages w/ direct mklml integration has always been experimental until being replaced by mkldnn. the USE_MKLML_EXPERIMENTAL flag was on in all of them.

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Thanks for the clarification. Will change the doc.


</div> <!-- End of pip -->


Expand Down Expand Up @@ -252,13 +258,17 @@ $ pip install mxnet-cu92 --pre

</div> <!-- End of master-->
<hr> <!-- pip footer -->
Most MXNet versions offer an experimental MKL pip package that will be much faster when running on Intel hardware.
MXNet offers MKL pip packages that will be much faster when running on Intel hardware.
Check the chart below for other options, refer to <a href="https://pypi.org/project/mxnet/">PyPI for other MXNet pip packages</a>, or <a href="validate_mxnet.html">validate your MXNet installation</a>.

<img src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/install/pip-packages-1.3.0.png" alt="pip packages"/>

**NOTES:**

*mxnet-cu92mkl* means the package is built with CUDA/cuDNN and MKL-DNN enabled and the CUDA version is 9.2.

MKL pip package is experimental in some old versions of MXNet.

CUDA should be installed first. Instructions can be found in the <a href="ubuntu_setup.html#cuda-dependencies">CUDA dependencies section of the MXNet Ubuntu installation guide</a>.

**Important:** Make sure your installed CUDA version matches the CUDA version in the pip package. Check your CUDA version with the following command:
Expand Down Expand Up @@ -478,11 +488,16 @@ $ pip install mxnet --pre

</div> <!-- End of master-->
<hr> <!-- pip footer -->
Most MXNet versions offer an experimental MKL pip package that will be much faster when running on Intel hardware.
MXNet offers MKL pip packages that will be much faster when running on Intel hardware.
Check the chart below for other options, refer to <a href="https://pypi.org/project/mxnet/">PyPI for other MXNet pip packages</a>, or <a href="validate_mxnet.html">validate your MXNet installation</a>.

<img src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/install/pip-packages-1.3.0.png" alt="pip packages"/>

**NOTES:**

*mxnet-cu92mkl* means the package is built with CUDA/cuDNN and MKL-DNN enabled and the CUDA version is 9.2.

MKL pip package is experimental in some old versions of MXNet.

</div> <!-- END of pip -->

Expand Down Expand Up @@ -686,11 +701,16 @@ $ pip install mxnet --pre

</div> <!-- End of master-->
<hr> <!-- pip footer -->
Most MXNet versions offer an experimental MKL pip package that will be much faster when running on Intel hardware.
MXNet offers MKL pip packages that will be much faster when running on Intel hardware.
Check the chart below for other options, refer to <a href="https://pypi.org/project/mxnet/">PyPI for other MXNet pip packages</a>, or <a href="validate_mxnet.html">validate your MXNet installation</a>.

<img src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/install/pip-packages-1.3.0.png" alt="pip packages"/>

**NOTES:**

*mxnet-cu92mkl* means the package is built with CUDA/cuDNN and MKL-DNN enabled and the CUDA version is 9.2.

MKL pip package is experimental in some old versions of MXNet.

</div> <!-- End of pip -->

Expand Down Expand Up @@ -762,13 +782,17 @@ $ pip install mxnet-cu92 --pre

</div> <!-- End of master-->
<hr> <!-- pip footer -->
Most MXNet versions offer an experimental MKL pip package that will be much faster when running on Intel hardware.
MXNet offers MKL pip packages that will be much faster when running on Intel hardware.
Check the chart below for other options, refer to <a href="https://pypi.org/project/mxnet/">PyPI for other MXNet pip packages</a>, or <a href="validate_mxnet.html">validate your MXNet installation</a>.

<img src="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/install/pip-packages-1.3.0.png" alt="pip packages"/>

**NOTES:**

*mxnet-cu92mkl* means the package is built with CUDA/cuDNN and MKL-DNN enabled and the CUDA version is 9.2.

MKL pip package is experimental in some old versions of MXNet.

[Anaconda](https://www.anaconda.com/download/) is recommended.

CUDA should be installed first. Instructions can be found in the <a href="ubuntu_setup.html#cuda-dependencies">CUDA dependencies section of the MXNet Ubuntu installation guide</a>.
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2 changes: 1 addition & 1 deletion docs/install/windows_setup.md
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Expand Up @@ -117,7 +117,7 @@ We provide two primary options to build and install MXNet yourself using [Micros

**NOTE:** Visual Studio 2017's compiler is `vc15`. This is not to be confused with Visual Studio 2015's compiler, `vc14`.

You also have the option to install MXNet with MKL or MKLDNN. In this case it is recommended that you refer to the [MKLDNN_README](https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md).
You also have the option to install MXNet with MKL or MKL-DNN. In this case it is recommended that you refer to the [MKLDNN_README](https://github.com/apache/incubator-mxnet/blob/master/MKLDNN_README.md).

**Option 1: Build with Microsoft Visual Studio 2017 (VS2017)**

Expand Down