diff --git a/docs/python_docs/python/tutorials/deploy/inference/image_classification_jetson.md b/docs/python_docs/python/tutorials/deploy/inference/image_classification_jetson.md new file mode 100644 index 000000000000..5a697ca7960e --- /dev/null +++ b/docs/python_docs/python/tutorials/deploy/inference/image_classification_jetson.md @@ -0,0 +1,117 @@ + + + + + + + + + + + + + + + + + +# Image Classication using pretrained ResNet-50 model on Jetson module + +This tutorial shows how to install MXNet v1.6 with Jetson support and use it to deploy a pre-trained MXNet model for image classification on a Jetson module. + +## What's in this tutorial? + +This tutorial shows how to: + +1. Install MXNet v1.6 along with its dependencies on a Jetson module (This tutorial has been tested on Jetson Xavier AGX and Jetson Nano modules) + +2. Deploy a pre-trained MXNet model for image classifcation on the module + +## Who's this tutorial for? + +This tutorial would benefit developers working on Jetson modules implementing deep learning applications. It assumes that readers have a Jetson module setup with Jetpack installed, are familiar with the Jetson working environment and are somewhat familiar with deep learning using MXNet. + +## Prerequisites + +To complete this tutorial, you need: + +* A [Jetson module](https://developer.nvidia.com/embedded/develop/hardware) setup with [Jetpack 4.4](https://docs.nvidia.com/jetson/jetpack/release-notes/) installed using NVIDIA [SDK Manager](https://developer.nvidia.com/nvidia-sdk-manager) + +* An SSH connection to the module OR display and keyboard setup to directly open shell on the module + +* [Swapfile](https://help.ubuntu.com/community/SwapFaq) installed, especially on Jetson Nano for additional memory (increase memory if the inference script terminates with a `Killed` message) + +## Installing MXNet v1.6 with Jetson support + +To install MXNet with Jetson support, you can follow the [installation guide](https://mxnet.apache.org/get_started/jetson_setup) on MXNet official website. + +Alternatively, you can also directly install MXNet v1.6 wheel with Jetson support, hosted on a public s3 bucket. Here are the steps to install this wheel: + +*WARNING: this MXNet wheel is provided for your convenience but it contains packages that are not provided nor endorsed by the Apache Software Foundation. +As such, they might contain software components with more restrictive licenses than the Apache License and you'll need to decide whether they are appropriate for your usage. Like all Apache Releases, the +official Apache MXNet (incubating) releases consist of source code only and are found at https://mxnet.apache.org/get_started/download .* + +We start by installing MXNet dependencies +```bash +sudo apt-get update +sudo apt-get install -y git build-essential libopenblas-dev libopencv-dev python3-pip +sudo pip3 install -U pip +``` + +Then we download and install MXNet v1.6 wheel with Jetson support +```bash +wget https://mxnet-public.s3.us-east-2.amazonaws.com/install/jetson/1.6.0/mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl +sudo pip3 install mxnet_cu102-1.6.0-py2.py3-none-linux_aarch64.whl +``` + +And we are done. You can test the installation now by importing mxnet from python3 +```bash +>>> python3 -c 'import mxnet' +``` + +## Running a pre-trained ResNet-50 model on Jetson + +We are now ready to run a pre-trained model and run inference on a Jetson module. In this tutorial we are using ResNet-50 model trained on Imagenet dataset. We run the following classification script with either cpu/gpu context using python3. + +```python +from mxnet import gluon +import mxnet as mx + +# set context +ctx = mx.gpu() + +# load pre-trained model +net = gluon.model_zoo.vision.resnet50_v1(pretrained=True, ctx=ctx) +net.hybridize(static_alloc=True, static_shape=True) + +# load labels +lbl_path = gluon.utils.download('http://data.mxnet.io/models/imagenet/synset.txt') +with open(lbl_path, 'r') as f: + labels = [l.rstrip() for l in f] + +# download and format image as (batch, RGB, width, height) +img_path = gluon.utils.download('https://github.com/dmlc/web-data/blob/master/mxnet/doc/tutorials/python/predict_image/cat.jpg?raw=true') +img = mx.image.imread(img_path) +img = mx.image.imresize(img, 224, 224) # resize +img = mx.image.color_normalize(img.astype(dtype='float32')/255, + mean=mx.nd.array([0.485, 0.456, 0.406]), + std=mx.nd.array([0.229, 0.224, 0.225])) # normalize +img = img.transpose((2, 0, 1)) # channel first +img = img.expand_dims(axis=0) # batchify +img = img.as_in_context(ctx) + +prob = net(img).softmax() # predict and normalize output +idx = prob.topk(k=5)[0] # get top 5 result +for i in idx: + i = int(i.asscalar()) + print('With prob = %.5f, it contains %s' % (prob[0,i].asscalar(), labels[i])) +``` + +After running the above script, you should get the following output showing the five classes that the image most relates to with probability: +```bash +With prob = 0.41940, it contains n02119789 kit fox, Vulpes macrotis +With prob = 0.28096, it contains n02119022 red fox, Vulpes vulpes +With prob = 0.06857, it contains n02124075 Egyptian cat +With prob = 0.03046, it contains n02120505 grey fox, gray fox, Urocyon cinereoargenteus +With prob = 0.02770, it contains n02441942 weasel +``` diff --git a/docs/static_site/src/_includes/get_started/cloud/cpu.md b/docs/static_site/src/_includes/get_started/cloud/cpu.md index 5415e96b6534..440582727b68 100644 --- a/docs/static_site/src/_includes/get_started/cloud/cpu.md +++ b/docs/static_site/src/_includes/get_started/cloud/cpu.md @@ -1,8 +1,16 @@ -MXNet should work on any cloud provider's CPU-only instances. Follow the Python pip install -instructions, -Docker instructions, or try the following preinstalled option. +MXNet should work on any cloud provider's CPU-only instances. Follow the Python +pip install instructions, Docker instructions, or try the following preinstalled +option. + +WARNING: the following cloud provider packages are provided for your convenience +but they point to packages that are *not* provided nor endorsed by the Apache +Software Foundation. As such, they might contain software components with more +restrictive licenses than the Apache License and you'll need to decide whether +they are appropriate for your usage. Like all Apache Releases, the official +Apache MXNet (incubating) releases consist of source code only and are found at +the [Download page](https://mxnet.apache.org/get_started/download). * **Amazon Web Services** - [AWS Deep Learning AMI](https://aws.amazon.com/machine-learning/amis/) - Preinstalled Conda environments -for Python 2 or 3 with MXNet and MKL-DNN. \ No newline at end of file +for Python 2 or 3 with MXNet and MKL-DNN. diff --git a/docs/static_site/src/_includes/get_started/cloud/gpu.md b/docs/static_site/src/_includes/get_started/cloud/gpu.md index 725d96581776..8f64a3ac5cba 100644 --- a/docs/static_site/src/_includes/get_started/cloud/gpu.md +++ b/docs/static_site/src/_includes/get_started/cloud/gpu.md @@ -1,7 +1,14 @@ -MXNet is available on several cloud providers with GPU support. You can also find -GPU/CPU-hybrid support for -use cases like scalable inference, or even fractional GPU support with AWS Elastic -Inference. +MXNet is available on several cloud providers with GPU support. You can also +find GPU/CPU-hybrid support for use cases like scalable inference, or even +fractional GPU support with AWS Elastic Inference. + +WARNING: the following cloud provider packages are provided for your convenience +but they point to packages that are *not* provided nor endorsed by the Apache +Software Foundation. As such, they might contain software components with more +restrictive licenses than the Apache License and you'll need to decide whether +they are appropriate for your usage. Like all Apache Releases, the official +Apache MXNet (incubating) releases consist of source code only and are found at +the [Download page](https://mxnet.apache.org/get_started/download). * **Alibaba** - [NVIDIA @@ -29,4 +36,4 @@ All NVIDIA VMs use the [NVIDIA MXNet Docker container](https://ngc.nvidia.com/catalog/containers/nvidia:mxnet). Follow the [container usage instructions](https://ngc.nvidia.com/catalog/containers/nvidia:mxnet) found in -[NVIDIA's container repository](https://ngc.nvidia.com/). \ No newline at end of file +[NVIDIA's container repository](https://ngc.nvidia.com/). diff --git a/docs/static_site/src/_includes/get_started/get_started.html b/docs/static_site/src/_includes/get_started/get_started.html index 772802fbaeb5..d8c7d3a42e5a 100644 --- a/docs/static_site/src/_includes/get_started/get_started.html +++ b/docs/static_site/src/_includes/get_started/get_started.html @@ -10,8 +10,10 @@
-

Installing MXNet

-

Indicate your preferred configuration. Then, follow the customized commands to install MXNet.

+

Platform and use-case specific instructions for using MXNet

+

+ Please indicate your preferred configuration below to see specific instructions. +



@@ -22,14 +24,15 @@

Installing MXNet

@@ -270,183 +249,155 @@

Installing MXNet

+
{% markdown %}{% include /get_started/macos/python/cpu/pip.md %}{% endmarkdown %} -
+
+
{% markdown %}{% include /get_started/macos/python/cpu/docker.md %}{% endmarkdown %}
+
{% markdown %}{% include /get_started/macos/python/cpu/build-from-source.md %}{% endmarkdown %} -
-
+
+
+ - +
-
- {% markdown %}{% include /get_started/macos/python/gpu/pip_docker.md %}{% endmarkdown %} -
-
- {% markdown %}{% include /get_started/macos/python/gpu/build-from-source.md %}{% endmarkdown %} + {% markdown %}{% include /get_started/macos/python/gpu/build-from-source.md %}{% endmarkdown %}
+ -
-
- {% markdown %}{% include /get_started/macos/r/cpu.md %}{% endmarkdown %} -
-
- {% markdown %}{% include /get_started/macos/r/gpu.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/macos/r/build-from-source.md %}{% endmarkdown %} +
+
-
- {% markdown %}{% include /get_started/macos/scala/cpu.md %}{% endmarkdown %} -
-
- {% markdown %}{% include /get_started/macos/scala/gpu.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/macos/scala/build-from-source.md %}{% endmarkdown %} +
+
-
- {% markdown %}{% include /get_started/macos/clojure/cpu.md %}{% endmarkdown %} -
-
- {% markdown %}{% include /get_started/macos/clojure/gpu.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/macos/clojure/build-from-source.md %}{% endmarkdown %} +
-
- {% markdown %}{% include /get_started/macos/java/cpu.md %}{% endmarkdown %} -
-
- {% markdown %}{% include /get_started/macos/java/gpu.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/macos/java/build-from-source.md %}{% endmarkdown %} +
-
-
-
- {% markdown %}{% include /get_started/macos/julia/pkg.md %}{% endmarkdown %} -
- -
- {% markdown %}{% include /get_started/macos/julia/build-from-source.md %}{% endmarkdown %} -
-
+
+ {% markdown %}{% include /get_started/macos/julia/build-from-source.md %}{% endmarkdown %} +
-
- {% markdown %}{% include /get_started/macos/perl/perl.md %}{% endmarkdown %} -
-
+
+ {% markdown %}{% include /get_started/macos/perl/build-from-source.md %}{% endmarkdown %} +
+
-
- {% markdown %}{% include /get_started/macos/cpp/cpp.md %}{% endmarkdown %} -
-
-
- For more installation options, refer to the MXNet macOS installation guide. - +
+ {% markdown %}{% include /get_started/macos/cpp/build-from-source.md %}{% endmarkdown %} +
+ + +
+
{% markdown %}{% include /get_started/windows/python/cpu/pip.md %}{% endmarkdown %}
-
- {% markdown %}{% include /get_started/windows/python/cpu/docker.md %}{% endmarkdown %} -
-
{% markdown %}{% include /get_started/windows/python/cpu/build-from-source.md %}{% endmarkdown %} -
-
+
+
+ +
{% markdown %}{% include /get_started/windows/python/gpu/pip.md %}{% endmarkdown %} -
+
- {% markdown %}{% include /get_started/windows/python/gpu/build-from-source.md %}{% endmarkdown %} -
- - - + {% markdown %}{% include /get_started/windows/python/gpu/build-from-source.md %}{% endmarkdown %} + + + + -
-
- {% markdown %}{% include /get_started/windows/r/cpu.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/windows/r/build-from-source.md %}{% endmarkdown %} +
+
-
- {% markdown %}{% include /get_started/windows/r/gpu.md %}{% endmarkdown %} -
-
-
- {% markdown %}{% include /get_started/windows/scala/scala.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/windows/scala/build-from-source.md %}{% endmarkdown %} +
+
-
- {% markdown %}{% include /get_started/windows/clojure/clojure.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/windows/clojure/build-from-source.md %}{% endmarkdown %} +
+
-
- {% markdown %}{% include /get_started/windows/java/java.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/windows/java/build-from-source.md %}{% endmarkdown %} +
-
-
- {% markdown %}{% include /get_started/windows/julia/pkg.md %}{% endmarkdown %} -
-
- {% markdown %}{% include /get_started/windows/julia/build-from-source.md %}{% endmarkdown %} -
-
+
+ {% markdown %}{% include /get_started/windows/julia/build-from-source.md %}{% endmarkdown %} +
-
- {% markdown %}{% include /get_started/windows/perl/perl.md %}{% endmarkdown %} -
+
+ {% markdown %}{% include /get_started/windows/perl/build-from-source.md %}{% endmarkdown %} +
-
- {% markdown %}{% include /get_started/windows/cpp/cpp.md %}{% endmarkdown %} -
-
- - For more installation options, refer to the MXNet Windows installation guide. - +
+ {% markdown %}{% include /get_started/windows/cpp/build-from-source.md %}{% endmarkdown %} +
+ + diff --git a/docs/static_site/src/_includes/get_started/linux/clojure/cpu.md b/docs/static_site/src/_includes/get_started/linux/clojure/build-from-source.md similarity index 100% rename from docs/static_site/src/_includes/get_started/linux/clojure/cpu.md rename to docs/static_site/src/_includes/get_started/linux/clojure/build-from-source.md diff --git a/docs/static_site/src/_includes/get_started/linux/clojure/gpu.md b/docs/static_site/src/_includes/get_started/linux/clojure/gpu.md deleted file mode 100644 index 26293f6e077f..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/clojure/gpu.md +++ /dev/null @@ -1,15 +0,0 @@ -You can use the Maven packages defined in the following dependency to include MXNet in your Clojure -project. To maximize leverage, the Clojure package has been built on the existing Scala package. Please -refer to the [MXNet-Scala setup guide]({{'/get_started/scala_setup'|relative_url}}) for a detailed set of instructions -to help you with the setup process that is required to use the Clojure dependency. - -maven badge - -{% highlight html %} - - org.apache.mxnet.contrib.clojure - clojure-mxnet-linux-gpu - -{% endhighlight %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/linux/cpp/build-from-source.md b/docs/static_site/src/_includes/get_started/linux/cpp/build-from-source.md new file mode 100644 index 000000000000..d37cf77a3afc --- /dev/null +++ b/docs/static_site/src/_includes/get_started/linux/cpp/build-from-source.md @@ -0,0 +1,2 @@ +To use the C++ package, build from source the `USE_CPP_PACKAGE=1` option. Please +refer to the build from source instructions linked above. diff --git a/docs/static_site/src/_includes/get_started/linux/cpp/cpp.md b/docs/static_site/src/_includes/get_started/linux/cpp/cpp.md deleted file mode 100644 index dc492d801262..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/cpp/cpp.md +++ /dev/null @@ -1,4 +0,0 @@ -To enable the C++ package, build from source using `make USE_CPP_PACKAGE=1`. -Refer to the [MXNet C++ setup guide](/get_started/cpp_setup.html) -for full instructions. - \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/linux/java/build-from-source.md b/docs/static_site/src/_includes/get_started/linux/java/build-from-source.md new file mode 100644 index 000000000000..585cc3e41890 --- /dev/null +++ b/docs/static_site/src/_includes/get_started/linux/java/build-from-source.md @@ -0,0 +1,6 @@ +Previously available binaries distributed via Maven have been removed as they +redistributed Category-X binaries in violation of Apache Software Foundation +(ASF) policies. + +At this point in time, no third-party binary Java packages are available. Please +follow the build from source instructions linked above. diff --git a/docs/static_site/src/_includes/get_started/linux/java/gpu.md b/docs/static_site/src/_includes/get_started/linux/java/gpu.md deleted file mode 100644 index 6f6757f6e2ea..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/java/gpu.md +++ /dev/null @@ -1,17 +0,0 @@ -You can use the Maven packages defined in the following dependency to include MXNet in your Java -project. The Java API is provided as a subset of the Scala API and is intended for inference only. -Please refer to the MXNet-Java setup guide for a detailed set of -instructions to help you with the setup process. - - - maven badge - - -{% highlight html %} - - org.apache.mxnet - mxnet-full_2.11-linux-x86_64-gpu - [1.5.0, ) - -{% endhighlight %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/linux/julia/build-from-source.md b/docs/static_site/src/_includes/get_started/linux/julia/build-from-source.md index 018aca9d7387..cef507527bfe 100644 --- a/docs/static_site/src/_includes/get_started/linux/julia/build-from-source.md +++ b/docs/static_site/src/_includes/get_started/linux/julia/build-from-source.md @@ -1,2 +1 @@ -Refer to the [Julia section of the MXNet Ubuntu installation guide](/get_started/ubuntu_setup#install-the-mxnet-package-for-julia). - +Please follow the build from source instructions linked above. diff --git a/docs/static_site/src/_includes/get_started/linux/julia/pkg.md b/docs/static_site/src/_includes/get_started/linux/julia/pkg.md deleted file mode 100644 index 35971305ee2d..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/julia/pkg.md +++ /dev/null @@ -1,10 +0,0 @@ -Install a pinned version of MXNet like this: - -{% highlight julia %} -]add MXNet#v1.5.0 -{% endhighlight %} - -Or directly install the latest release: -{% highlight julia %} -]add MXNet -{% endhighlight %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/linux/perl/build-from-source.md b/docs/static_site/src/_includes/get_started/linux/perl/build-from-source.md new file mode 100644 index 000000000000..cef507527bfe --- /dev/null +++ b/docs/static_site/src/_includes/get_started/linux/perl/build-from-source.md @@ -0,0 +1 @@ +Please follow the build from source instructions linked above. diff --git a/docs/static_site/src/_includes/get_started/linux/perl/perl.md b/docs/static_site/src/_includes/get_started/linux/perl/perl.md deleted file mode 100644 index 02d82e457726..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/perl/perl.md +++ /dev/null @@ -1 +0,0 @@ -Refer to the [Perl section of the MXNet Ubuntu installation guide](get_started/ubuntu_setup.html#install-the-mxnet-package-for-perl). \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/linux/python/cpu/build-from-source.md b/docs/static_site/src/_includes/get_started/linux/python/cpu/build-from-source.md index 4adf039739d5..cef507527bfe 100644 --- a/docs/static_site/src/_includes/get_started/linux/python/cpu/build-from-source.md +++ b/docs/static_site/src/_includes/get_started/linux/python/cpu/build-from-source.md @@ -1 +1 @@ -To build from source, refer to the [MXNet Ubuntu installation guide]({{'/get_started/ubuntu_setup' | relative_url}}). +Please follow the build from source instructions linked above. diff --git a/docs/static_site/src/_includes/get_started/linux/python/cpu/docker.md b/docs/static_site/src/_includes/get_started/linux/python/cpu/docker.md index 8f2c8eb143a4..7eab6d36dec2 100644 --- a/docs/static_site/src/_includes/get_started/linux/python/cpu/docker.md +++ b/docs/static_site/src/_includes/get_started/linux/python/cpu/docker.md @@ -1,22 +1,18 @@ -Docker images with *MXNet* are available at [DockerHub](https://hub.docker.com/r/mxnet/). - -**Step 1** Install Docker on your machine by following the [docker installation -instructions](https://docs.docker.com/engine/installation/linux/ubuntu/#install-using-the-repository). - -*Note* - You can install Community Edition (CE) to get started with *MXNet*. - -**Step 2** [Optional] Post installation steps to manage Docker as a non-root user. +WARNING: the following links and names of binary distributions are provided for +your convenience but they point to packages that are *not* provided nor endorsed +by the Apache Software Foundation. As such, they might contain software +components with more restrictive licenses than the Apache License and you'll +need to decide whether they are appropriate for your usage. Like all Apache +Releases, the official Apache MXNet (incubating) releases consist of source code +only and are found at +the [Download page](https://mxnet.apache.org/get_started/download). + -Follow the four steps in this [docker -documentation](https://docs.docker.com/engine/installation/linux/linux-postinstall/#manage-docker-as-a-non-root-user) -to allow managing docker containers without *sudo*. - -If you skip this step, you need to use *sudo* each time you invoke Docker. - -**Step 3** Pull the MXNet docker image. +Docker images with *MXNet* are available at [DockerHub](https://hub.docker.com/r/mxnet/). +After you installed Docker on your machine, you can use them via: {% highlight bash %} -$ docker pull mxnet/python # Use sudo if you skip Step 2 +$ docker pull mxnet/python {% endhighlight %} You can list docker images to see if mxnet/python docker image pull was successful. @@ -28,16 +24,4 @@ REPOSITORY TAG IMAGE ID CREATED SIZE mxnet/python latest 00d026968b3c 3 weeks ago 1.41 GB {% endhighlight %} -Using the latest MXNet with [Intel MKL-DNN](https://github.com/intel/mkl-dnn) is -recommended for the -fastest inference speeds with MXNet. - -{% highlight bash %} -$ docker pull mxnet/python:1.3.0_cpu_mkl # Use sudo if you skip Step 2 -$ docker images # Use sudo if you skip Step 2 - -REPOSITORY TAG IMAGE ID CREATED SIZE -mxnet/python 1.3.0_cpu_mkl deaf9bf61d29 4 days ago 678 MB -{% endhighlight %} - -**Step 4** Validate the installation. \ No newline at end of file +You can then validate the installation. diff --git a/docs/static_site/src/_includes/get_started/linux/python/cpu/pip.md b/docs/static_site/src/_includes/get_started/linux/python/cpu/pip.md index 81db75ea9038..83e86047dc4f 100644 --- a/docs/static_site/src/_includes/get_started/linux/python/cpu/pip.md +++ b/docs/static_site/src/_includes/get_started/linux/python/cpu/pip.md @@ -1,8 +1,31 @@ +WARNING: the following PyPI package names are provided for your convenience but +they point to packages that are *not* provided nor endorsed by the Apache +Software Foundation. As such, they might contain software components with more +restrictive licenses than the Apache License and you'll need to decide whether +they are appropriate for your usage. Like all Apache Releases, the official +Apache MXNet (incubating) releases consist of source code only and are found at +the [Download page](https://mxnet.apache.org/get_started/download). + Run the following command: -
+
+{% highlight bash %} +pip install mxnet +{% endhighlight %} + +MKL-DNN enabled pip packages are optimized for Intel hardware. You can find +performance numbers +in the MXNet tuning guide. + +{% highlight bash %} +pip install mxnet-mkl +{% endhighlight %} + +
+ +
{% highlight bash %} -$ pip install mxnet +pip install mxnet==1.5.1 {% endhighlight %} MKL-DNN enabled pip packages are optimized for Intel hardware. You can find @@ -10,15 +33,15 @@ performance numbers in the MXNet tuning guide. {% highlight bash %} -$ pip install mxnet-mkl +pip install mxnet-mkl==1.5.1 {% endhighlight %} -
+
{% highlight bash %} -$ pip install mxnet==1.4.1 +pip install mxnet==1.4.1 {% endhighlight %} MKL-DNN enabled pip packages are optimized for Intel hardware. You can find @@ -26,14 +49,14 @@ performance numbers in the MXNet tuning guide. {% highlight bash %} -$ pip install mxnet-mkl==1.4.1 +pip install mxnet-mkl==1.4.1 {% endhighlight %}
{% highlight bash %} -$ pip install mxnet==1.3.1 +pip install mxnet==1.3.1 {% endhighlight %} MKL-DNN enabled pip packages are optimized for Intel hardware. You can find @@ -41,14 +64,14 @@ performance numbers in the MXNet tuning guide. {% highlight bash %} -$ pip install mxnet-mkl==1.3.1 +pip install mxnet-mkl==1.3.1 {% endhighlight %}
{% highlight bash %} -$ pip install mxnet==1.2.1 +pip install mxnet==1.2.1 {% endhighlight %} MKL-DNN enabled pip packages are optimized for Intel hardware. You can find @@ -56,7 +79,7 @@ performance numbers in the MXNet tuning guide. {% highlight bash %} -$ pip install mxnet-mkl==1.2.1 +pip install mxnet-mkl==1.2.1 {% endhighlight %}
@@ -64,7 +87,7 @@ $ pip install mxnet-mkl==1.2.1
{% highlight bash %} -$ pip install mxnet==1.1.0 +pip install mxnet==1.1.0 {% endhighlight %}
@@ -72,7 +95,7 @@ $ pip install mxnet==1.1.0
{% highlight bash %} -$ pip install mxnet==1.0.0 +pip install mxnet==1.0.0 {% endhighlight %}
@@ -81,13 +104,13 @@ $ pip install mxnet==1.0.0
{% highlight bash %} -$ pip install mxnet==0.12.1 +pip install mxnet==0.12.1 {% endhighlight %} For MXNet 0.12.0: {% highlight bash %} -$ pip install mxnet==0.12.0 +pip install mxnet==0.12.0 {% endhighlight %}
@@ -95,27 +118,12 @@ $ pip install mxnet==0.12.0
{% highlight bash %} -$ pip install mxnet==0.11.0 +pip install mxnet==0.11.0 {% endhighlight %}
-
- -{% highlight bash %} -$ pip install mxnet --pre -{% endhighlight %} - -MKL-DNN enabled pip packages are optimized for Intel hardware. You can find -performance numbers -in the MXNet tuning guide. - -{% highlight bash %} -$ pip install mxnet-mkl --pre -{% endhighlight %} - -

-{% include /get_started/pip_snippet.md %} \ No newline at end of file +{% include /get_started/pip_snippet.md %} diff --git a/docs/static_site/src/_includes/get_started/linux/python/gpu/build-from-source.md b/docs/static_site/src/_includes/get_started/linux/python/gpu/build-from-source.md index 4adf039739d5..cef507527bfe 100644 --- a/docs/static_site/src/_includes/get_started/linux/python/gpu/build-from-source.md +++ b/docs/static_site/src/_includes/get_started/linux/python/gpu/build-from-source.md @@ -1 +1 @@ -To build from source, refer to the [MXNet Ubuntu installation guide]({{'/get_started/ubuntu_setup' | relative_url}}). +Please follow the build from source instructions linked above. diff --git a/docs/static_site/src/_includes/get_started/linux/python/gpu/docker.md b/docs/static_site/src/_includes/get_started/linux/python/gpu/docker.md index dc21cf10b4ef..f963bc9c58de 100644 --- a/docs/static_site/src/_includes/get_started/linux/python/gpu/docker.md +++ b/docs/static_site/src/_includes/get_started/linux/python/gpu/docker.md @@ -1,24 +1,19 @@ -Docker images with *MXNet* are available at [DockerHub](https://hub.docker.com/r/mxnet/). - -**Step 1** Install Docker on your machine by following the [docker installation -instructions](https://docs.docker.com/engine/installation/linux/ubuntu/#install-using-the-repository). - -*Note* - You can install Community Edition (CE) to get started with *MXNet*. - -**Step 2** [Optional] Post installation steps to manage Docker as a non-root user. +WARNING: the following links and names of binary distributions are provided for +your convenience but they point to packages that are *not* provided nor endorsed +by the Apache Software Foundation. As such, they might contain software +components with more restrictive licenses than the Apache License and you'll +need to decide whether they are appropriate for your usage. Like all Apache +Releases, the official Apache MXNet (incubating) releases consist of source code +only and are found at +the [Download page](https://mxnet.apache.org/get_started/download). -Follow the four steps in this [docker -documentation](https://docs.docker.com/engine/installation/linux/linux-postinstall/#manage-docker-as-a-non-root-user) -to allow managing docker containers without *sudo*. - -If you skip this step, you need to use *sudo* each time you invoke Docker. +Docker images with *MXNet* are available at [DockerHub](https://hub.docker.com/r/mxnet/). -**Step 3** Install *nvidia-docker-plugin* following the [installation -instructions](https://github.com/NVIDIA/nvidia-docker/wiki). *nvidia-docker-plugin* -is required to -enable the usage of GPUs from the docker containers. +Please follow the [NVidia Docker installation +instructions](https://github.com/NVIDIA/nvidia-docker/wiki) to enable the usage +of GPUs from the docker containers. -**Step 4** Pull the MXNet docker image. +After you installed Docker on your machine, you can use them via: {% highlight bash %} $ docker pull mxnet/python:gpu # Use sudo if you skip Step 2 @@ -33,16 +28,4 @@ REPOSITORY TAG IMAGE ID CREATED SIZE mxnet/python gpu 493b2683c269 3 weeks ago 4.77 GB {% endhighlight %} -Using the latest MXNet with [Intel MKL-DNN](https://github.com/intel/mkl-dnn) is -recommended for the -fastest inference speeds with MXNet. - -{% highlight bash %} -$ docker pull mxnet/python:1.3.0_cpu_mkl # Use sudo if you skip Step 2 -$ docker images # Use sudo if you skip Step 2 - -REPOSITORY TAG IMAGE ID CREATED SIZE -mxnet/python 1.3.0_gpu_cu92_mkl adcb3ab19f50 4 days ago 4.23 GB -{% endhighlight %} - -**Step 5** Validate the installation. \ No newline at end of file +You can then validate the installation. diff --git a/docs/static_site/src/_includes/get_started/linux/python/gpu/pip.md b/docs/static_site/src/_includes/get_started/linux/python/gpu/pip.md index 249cd5b54052..b47226c73977 100644 --- a/docs/static_site/src/_includes/get_started/linux/python/gpu/pip.md +++ b/docs/static_site/src/_includes/get_started/linux/python/gpu/pip.md @@ -1,11 +1,26 @@ +WARNING: the following PyPI package names are provided for your convenience but +they point to packages that are *not* provided nor endorsed by the Apache +Software Foundation. As such, they might contain software components with more +restrictive licenses than the Apache License and you'll need to decide whether +they are appropriate for your usage. Like all Apache Releases, the official +Apache MXNet (incubating) releases consist of source code only and are found at +the [Download page](https://mxnet.apache.org/get_started/download). + Run the following command: -
+
+{% highlight bash %} +$ pip install mxnet-cu102 +{% endhighlight %} + +
+ +
{% highlight bash %} -$ pip install mxnet-cu101 +$ pip install mxnet-cu101==1.5.1 {% endhighlight %} -
+
{% highlight bash %} @@ -60,15 +75,7 @@ $ pip install mxnet-cu80==0.11.0
-
- -{% highlight bash %} -$ pip install mxnet-cu101 --pre -{% endhighlight %} - -
-
{% include /get_started/pip_snippet.md %} -{% include /get_started/gpu_snippet.md %} \ No newline at end of file +{% include /get_started/gpu_snippet.md %} diff --git a/docs/static_site/src/_includes/get_started/linux/r/build-from-source.md b/docs/static_site/src/_includes/get_started/linux/r/build-from-source.md new file mode 100644 index 000000000000..1150a309223d --- /dev/null +++ b/docs/static_site/src/_includes/get_started/linux/r/build-from-source.md @@ -0,0 +1,2 @@ +You will need to R v3.4.4+ and build MXNet from source. Please follow the +instructions linked above. diff --git a/docs/static_site/src/_includes/get_started/linux/r/cpu.md b/docs/static_site/src/_includes/get_started/linux/r/cpu.md deleted file mode 100644 index 1077362c9a65..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/r/cpu.md +++ /dev/null @@ -1,10 +0,0 @@ -The default version of R that is installed with `apt-get` is insufficient. You will need -to first [install R v3.4.4+ and build MXNet from source](/get_started/ubuntu_setup.html#install-the-mxnet-package-for-r). - -After you have setup R v3.4.4+ and MXNet, you can build and install the MXNet R bindings with the following, assuming that `incubator-mxnet` is the source directory you used to build MXNet as follows: - -{% highlight bash %} -$ cd incubator-mxnet -$ mkdir build; cd build; cmake -DUSE_CUDA=OFF ..; make -j $(nproc); cd .. -$ make -f R-package/Makefile rpkg -{% endhighlight %} diff --git a/docs/static_site/src/_includes/get_started/linux/r/gpu.md b/docs/static_site/src/_includes/get_started/linux/r/gpu.md deleted file mode 100644 index 1ef16df25da5..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/r/gpu.md +++ /dev/null @@ -1,17 +0,0 @@ -The default version of R that is installed with `apt-get` is insufficient. You will need -to first -[install R v3.4.4+ and build MXNet from -source](/get_started/ubuntu_setup.html#install-the-mxnet-package-for-r). - -After you have setup R v3.4.4+ and MXNet, you can build and install the MXNet R bindings -with the -following, assuming that `incubator-mxnet` is the source directory you used to build -MXNet as follows: - -{% highlight bash %} -$ cd incubator-mxnet -$ mkdir build; cd build; cmake ..; make -j $(nproc); cd .. -$ make -f R-package/Makefile rpkg -{% endhighlight %} - -{% include /get_started/gpu_snippet.md %} diff --git a/docs/static_site/src/_includes/get_started/linux/java/cpu.md b/docs/static_site/src/_includes/get_started/linux/scala/build-from-source.md similarity index 100% rename from docs/static_site/src/_includes/get_started/linux/java/cpu.md rename to docs/static_site/src/_includes/get_started/linux/scala/build-from-source.md diff --git a/docs/static_site/src/_includes/get_started/linux/scala/cpu.md b/docs/static_site/src/_includes/get_started/linux/scala/cpu.md deleted file mode 100644 index 3cc96bade7df..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/scala/cpu.md +++ /dev/null @@ -1,14 +0,0 @@ -You can use the Maven packages defined in the following dependency to include MXNet in your Scala -project. Please refer to the [MXNet-Scala setup guide]({{'/get_started/scala_setup'|relative_url}}) for -a detailed set of instructions to help you with the setup process. - -maven badge - -{% highlight html %} - -org.apache.mxnet -mxnet-full_2.11-linux-x86_64-cpu - -{% endhighlight %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/linux/scala/gpu.md b/docs/static_site/src/_includes/get_started/linux/scala/gpu.md deleted file mode 100644 index 5e2f9b179205..000000000000 --- a/docs/static_site/src/_includes/get_started/linux/scala/gpu.md +++ /dev/null @@ -1,16 +0,0 @@ -You can use the Maven packages defined in the following dependency to include MXNet in -your Scala -project. Please refer to the MXNet-Scala setup guide for -a detailed set -of instructions to help you with the setup process. - -maven badge - -{% highlight html %} - -org.apache.mxnet -mxnet-full_2.11-linux-x86_64-gpu - -{% endhighlight %} diff --git a/docs/static_site/src/_includes/get_started/macos b/docs/static_site/src/_includes/get_started/macos new file mode 120000 index 000000000000..9c52cb36f47e --- /dev/null +++ b/docs/static_site/src/_includes/get_started/macos @@ -0,0 +1 @@ +linux \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/clojure/cpu.md b/docs/static_site/src/_includes/get_started/macos/clojure/cpu.md deleted file mode 100644 index 1e27af5e5dd7..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/clojure/cpu.md +++ /dev/null @@ -1,17 +0,0 @@ - -You can use the Maven packages defined in the following dependency to include MXNet in -your Clojure project. To maximize leverage, the Clojure package has been built on the existing Scala -package. Please refer to the [MXNet-Scala setup guide](scala_setup.html) for a detailed set -of instructions to help you with the setup process that is required to use the Clojure dependency. - -maven badge - -{% highlight html %} - - org.apache.mxnet.contrib.clojure - clojure-mxnet-osx-cpu - -{% endhighlight %} - diff --git a/docs/static_site/src/_includes/get_started/macos/clojure/gpu.md b/docs/static_site/src/_includes/get_started/macos/clojure/gpu.md deleted file mode 100644 index ccbc24db96e7..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/clojure/gpu.md +++ /dev/null @@ -1 +0,0 @@ -Not available at this time. diff --git a/docs/static_site/src/_includes/get_started/macos/cpp/cpp.md b/docs/static_site/src/_includes/get_started/macos/cpp/cpp.md deleted file mode 100644 index cb9e613928d9..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/cpp/cpp.md +++ /dev/null @@ -1,3 +0,0 @@ -To enable the C++ package, build from source using `make USE_CPP_PACKAGE=1`. -Refer to the [MXNet C++ setup guide](/get_started/cpp_setup.html) for full instructions. - \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/java/cpu.md b/docs/static_site/src/_includes/get_started/macos/java/cpu.md deleted file mode 100644 index 002037a15771..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/java/cpu.md +++ /dev/null @@ -1,16 +0,0 @@ -You can use the Maven packages defined in the following dependency to include MXNet in -your Java project. The Java API is provided as a subset of the Scala API and is intended for -inference only. -Please refer to the [MXNet-Java setup guide](/get_started/java_setup.html) for a detailed set of instructions to help you with the setup process. - - - -{% highlight html %} - - org.apache.mxnet - mxnet-full_2.11-linux-x86_64-cpu - [1.5.0, ) - -{% endhighlight %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/java/gpu.md b/docs/static_site/src/_includes/get_started/macos/java/gpu.md deleted file mode 100644 index b17ef33478ea..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/java/gpu.md +++ /dev/null @@ -1 +0,0 @@ -Not available at this time. \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/julia/build-from-source.md b/docs/static_site/src/_includes/get_started/macos/julia/build-from-source.md deleted file mode 100644 index b864d8a49086..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/julia/build-from-source.md +++ /dev/null @@ -1 +0,0 @@ -Refer to the [Julia section of the MXNet macOS installation guide](get_started/osx_setup.html#install-the-mxnet-package-for-julia). \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/julia/pkg.md b/docs/static_site/src/_includes/get_started/macos/julia/pkg.md deleted file mode 100644 index 35971305ee2d..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/julia/pkg.md +++ /dev/null @@ -1,10 +0,0 @@ -Install a pinned version of MXNet like this: - -{% highlight julia %} -]add MXNet#v1.5.0 -{% endhighlight %} - -Or directly install the latest release: -{% highlight julia %} -]add MXNet -{% endhighlight %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/perl/perl.md b/docs/static_site/src/_includes/get_started/macos/perl/perl.md deleted file mode 100644 index 45d59ddf78a6..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/perl/perl.md +++ /dev/null @@ -1 +0,0 @@ -Refer to the [Perl section of installation guide](/get_started/osx_setup.html#install-the-mxnet-package-for-perl). \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/python/cpu/build-from-source.md b/docs/static_site/src/_includes/get_started/macos/python/cpu/build-from-source.md deleted file mode 100644 index ee8e378ec20e..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/python/cpu/build-from-source.md +++ /dev/null @@ -1,2 +0,0 @@ -To build from source, refer to the [MXNet macOS installation guide](/get_started/osx_setup.html). -MXNet developers should refer to the MXNet wiki's [Developer Setup on Mac](https://cwiki.apache.org/confluence/display/MXNET/MXNet+Developer+Setup+on+Mac). diff --git a/docs/static_site/src/_includes/get_started/macos/python/cpu/docker.md b/docs/static_site/src/_includes/get_started/macos/python/cpu/docker.md deleted file mode 100644 index c8631ec26ab3..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/python/cpu/docker.md +++ /dev/null @@ -1,35 +0,0 @@ -Docker images with *MXNet* are available at [DockerHub](https://hub.docker.com/r/mxnet/). - -**Step 1** Install Docker on your machine by following the [docker installation -instructions](https://docs.docker.com/docker-for-mac/install/#install-and-run-docker-for-mac). - -*Note* - You can install Community Edition (CE) to get started with *MXNet*. - -**Step 2** Pull the MXNet docker image. - -{% highlight bash %} -$ docker pull mxnet/python -{% endhighlight %} - -You can list docker images to see if mxnet/python docker image pull was successful. - -{% highlight bash %} -$ docker images - -REPOSITORY TAG IMAGE ID CREATED SIZE -mxnet/python latest 00d026968b3c 3 weeks ago 1.41 GB -{% endhighlight %} - -Using the latest MXNet with [Intel MKL-DNN](https://github.com/intel/mkl-dnn) is -recommended for the -fastest inference speeds with MXNet. - -{% highlight bash %} -$ docker pull mxnet/python:1.3.0_cpu_mkl # Use sudo if you skip Step 2 -$ docker images # Use sudo if you skip Step 2 - -REPOSITORY TAG IMAGE ID CREATED SIZE -mxnet/python 1.3.0_cpu_mkl deaf9bf61d29 4 days ago 678 MB -{% endhighlight %} - -**Step 4** Validate the installation. \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/python/cpu/pip.md b/docs/static_site/src/_includes/get_started/macos/python/cpu/pip.md deleted file mode 100644 index beb5eb4fb797..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/python/cpu/pip.md +++ /dev/null @@ -1,73 +0,0 @@ -Run the following command: - -
- -{% highlight bash %} -$ pip install mxnet -{% endhighlight %} -
-
- -{% highlight bash %} -$ pip install mxnet==1.4.1 -{% endhighlight %} -
-
- -{% highlight bash %} -$ pip install mxnet==1.3.1 -{% endhighlight %} - -
-
- -{% highlight bash %} -$ pip install mxnet==1.2.1 -{% endhighlight %} - -
- - -
- -{% highlight bash %} -$ pip install mxnet==1.1.0 -{% endhighlight %} - -
- - -
- -{% highlight bash %} -$ pip install mxnet==1.0.0 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet=0.12.1 -{% endhighlight %} - -
- - -
- -{% highlight bash %} -$ pip install mxnet==0.11.0 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet --pre -{% endhighlight %} - -
- -{% include /get_started/pip_snippet.md %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/python/gpu/build-from-source.md b/docs/static_site/src/_includes/get_started/macos/python/gpu/build-from-source.md deleted file mode 100644 index ffcf88ecdd25..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/python/gpu/build-from-source.md +++ /dev/null @@ -1,2 +0,0 @@ -Refer to the [MXNet macOS installation guide](get_started/osx_setup.html). -MXNet developers should refer to the MXNet wiki's [Developer Setup on Mac](https://cwiki.apache.org/confluence/display/MXNET/MXNet+Developer+Setup+on+Mac). \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/python/gpu/pip_docker.md b/docs/static_site/src/_includes/get_started/macos/python/gpu/pip_docker.md deleted file mode 100644 index 87281fe85e38..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/python/gpu/pip_docker.md +++ /dev/null @@ -1 +0,0 @@ -This option is only available by building from source. Refer to the [MXNet macOS installation guide](get_started/osx_setup.html). \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/r/cpu.md b/docs/static_site/src/_includes/get_started/macos/r/cpu.md deleted file mode 100644 index 1e0d96b91ed7..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/r/cpu.md +++ /dev/null @@ -1,28 +0,0 @@ -To run MXNet you also should have OpenCV and OpenBLAS installed. You may install them with `brew` as follows: - -{% highlight bash %} -brew install opencv -brew install openblas -{% endhighlight %} - -To ensure MXNet R package runs with the version of OpenBLAS installed, create a symbolic link as follows: - -{% highlight bash %} -ln -sf /usr/local/opt/openblas/lib/libopenblas.dylib -/usr/local/opt/openblas/lib/libopenblasp-r0.3.1.dylib -{% endhighlight %} - -Note: packages for 3.6.x are not yet available. - -Install 3.5.x of R from [CRAN](https://cran.r-project.org/bin/macosx/). The latest is -[v3.5.3](https://cran.r-project.org/bin/macosx/R-3.5.3.pkg). - -You can [build MXNet-R from source](get_started/osx_setup.html#install-the-mxnet-package-for-r), or -you can use a pre-built binary: - -{% highlight r %} -cran <- getOption("repos") -cran["dmlc"] <- "https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/R/CRAN/" -options(repos = cran) -install.packages("mxnet") -{% endhighlight %} diff --git a/docs/static_site/src/_includes/get_started/macos/r/gpu.md b/docs/static_site/src/_includes/get_started/macos/r/gpu.md deleted file mode 100644 index 3fc556a8dd91..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/r/gpu.md +++ /dev/null @@ -1 +0,0 @@ -Be the first one to contribute this guide! \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/scala/cpu.md b/docs/static_site/src/_includes/get_started/macos/scala/cpu.md deleted file mode 100644 index 0bc69eb2e63e..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/scala/cpu.md +++ /dev/null @@ -1,14 +0,0 @@ -You can use the Maven packages defined in the following dependency to include MXNet in your Scala -project. Please refer to the [MXNet-Scala setup guide](/get_started/scala_setup.html) for a detailed set -of instructions to help you with the setup process. - -maven badge - -{% highlight html %} - - org.apache.mxnet - mxnet-full_2.11-osx-x86_64-cpu - -{% endhighlight %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos/scala/gpu.md b/docs/static_site/src/_includes/get_started/macos/scala/gpu.md deleted file mode 100644 index b17ef33478ea..000000000000 --- a/docs/static_site/src/_includes/get_started/macos/scala/gpu.md +++ /dev/null @@ -1 +0,0 @@ -Not available at this time. \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/macos~b6b40878f... Consolidate installation instructions on website and add disclaimer for non-ASF ressources (#18487) b/docs/static_site/src/_includes/get_started/macos~b6b40878f... Consolidate installation instructions on website and add disclaimer for non-ASF ressources (#18487) new file mode 120000 index 000000000000..9c52cb36f47e --- /dev/null +++ b/docs/static_site/src/_includes/get_started/macos~b6b40878f... Consolidate installation instructions on website and add disclaimer for non-ASF ressources (#18487) @@ -0,0 +1 @@ +linux \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/pip_snippet.md b/docs/static_site/src/_includes/get_started/pip_snippet.md index 2c4d932fc816..96ef52250a03 100644 --- a/docs/static_site/src/_includes/get_started/pip_snippet.md +++ b/docs/static_site/src/_includes/get_started/pip_snippet.md @@ -1,6 +1,4 @@ -MXNet offers MKL pip packages that will be much faster when running on Intel hardware. -Check the chart below for other options, refer to PyPI for -other MXNet pip packages, or validate your MXNet installation. +You can then validate your MXNet installation.
, or vali **NOTES:** -*mxnet-cu101mkl* means the package is built with CUDA/cuDNN and MKL-DNN enabled and the CUDA version is 10.1. +*mxnet-cu101* means the package is built with CUDA/cuDNN and the CUDA version is +10.1. All MKL pip packages are experimental prior to version 1.3.0. diff --git a/docs/static_site/src/_includes/get_started/windows b/docs/static_site/src/_includes/get_started/windows new file mode 120000 index 000000000000..9c52cb36f47e --- /dev/null +++ b/docs/static_site/src/_includes/get_started/windows @@ -0,0 +1 @@ +linux \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/clojure/clojure.md b/docs/static_site/src/_includes/get_started/windows/clojure/clojure.md deleted file mode 100644 index 0b25ab9018d3..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/clojure/clojure.md +++ /dev/null @@ -1 +0,0 @@ -MXNet-Clojure for Windows is not yet available. \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/cpp/cpp.md b/docs/static_site/src/_includes/get_started/windows/cpp/cpp.md deleted file mode 100644 index 023735b6c3b1..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/cpp/cpp.md +++ /dev/null @@ -1,3 +0,0 @@ -To enable the C++ package, build from source using `make USE_CPP_PACKAGE=1`. -Refer to the [MXNet C++ setup guide](/get_started/cpp_setup.html) for full instructions. - diff --git a/docs/static_site/src/_includes/get_started/windows/java/java.md b/docs/static_site/src/_includes/get_started/windows/java/java.md deleted file mode 100644 index 0db1f50590a2..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/java/java.md +++ /dev/null @@ -1 +0,0 @@ -MXNet-Java for Windows is not yet available. \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/julia/build-from-source.md b/docs/static_site/src/_includes/get_started/windows/julia/build-from-source.md deleted file mode 100644 index 4fc600468ad1..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/julia/build-from-source.md +++ /dev/null @@ -1 +0,0 @@ -Refer to the [Julia section of the MXNet Windows installation guide](/get_started/windows_setup.html#install-the-mxnet-package-for-julia). diff --git a/docs/static_site/src/_includes/get_started/windows/julia/pkg.md b/docs/static_site/src/_includes/get_started/windows/julia/pkg.md deleted file mode 100644 index cb79177e5bbe..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/julia/pkg.md +++ /dev/null @@ -1,10 +0,0 @@ -Install a pinned version of MXNet like this: - -{% highlight julia %} -]add MXNet#v1.5.0 -{% endhighlight %} - -Or directly install the latest release: -{% highlight julia %} -]add MXNet -{% endhighlight %} diff --git a/docs/static_site/src/_includes/get_started/windows/perl/perl.md b/docs/static_site/src/_includes/get_started/windows/perl/perl.md deleted file mode 100644 index 1a8eea5261ba..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/perl/perl.md +++ /dev/null @@ -1 +0,0 @@ -Refer to the [Perl section of the MXNet Windows installation guide](/get_started/windows_setup.html#install-the-mxnet-package-for-perl). \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/python/cpu/build-from-source.md b/docs/static_site/src/_includes/get_started/windows/python/cpu/build-from-source.md deleted file mode 100644 index af36205337d2..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/python/cpu/build-from-source.md +++ /dev/null @@ -1 +0,0 @@ -Refer to the [MXNet Windows installation guide](/get_started/windows_setup.html) \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/python/cpu/docker.md b/docs/static_site/src/_includes/get_started/windows/python/cpu/docker.md deleted file mode 100644 index a061b8bbab65..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/python/cpu/docker.md +++ /dev/null @@ -1,34 +0,0 @@ -Docker images with *MXNet* are available at [Docker Hub](https://hub.docker.com/r/mxnet/). - -**Step 1** Install Docker on your machine by following the docker installation instructions - -*Note* - You can install Community Edition (CE) to get started with *MXNet*. - -**Step 2** Pull the MXNet docker image. - -{% highlight bash %} -$ docker pull mxnet/python # Use sudo if you skip Step 2 -{% endhighlight %} - -You can list docker images to see if mxnet/python docker image pull was successful. - -{% highlight bash %} -$ docker images # Use sudo if you skip Step 2 - -REPOSITORY TAG IMAGE ID CREATED SIZE -mxnet/python latest 00d026968b3c 3 weeks ago 1.41 GB -{% endhighlight %} - -Using the latest MXNet with [Intel MKL-DNN](https://github.com/intel/mkl-dnn) is -recommended for the -fastest inference speeds with MXNet. - -{% highlight bash %} -$ docker pull mxnet/python:1.3.0_cpu_mkl # Use sudo if you skip Step 2 -$ docker images # Use sudo if you skip Step 2 - -REPOSITORY TAG IMAGE ID CREATED SIZE -mxnet/python 1.3.0_cpu_mkl deaf9bf61d29 4 days ago 678 MB -{% endhighlight %} - -**Step 4** Validate the installation. \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/python/cpu/pip.md b/docs/static_site/src/_includes/get_started/windows/python/cpu/pip.md deleted file mode 100644 index d5c7f1fd08f0..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/python/cpu/pip.md +++ /dev/null @@ -1,73 +0,0 @@ -Run the following command: - -
- -{% highlight bash %} -$ pip install mxnet -{% endhighlight %} - -
-
- -{% highlight bash %} -$ pip install mxnet==1.4.1 -{% endhighlight %} - -
-
- -{% highlight bash %} -$ pip install mxnet==1.3.1 -{% endhighlight %} - -
-
- -{% highlight bash %} -$ pip install mxnet==1.2.1 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet==1.1.0 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet==1.0.0 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet==0.12.1 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet==0.11.0 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet --pre -{% endhighlight %} - -
- -{% include /get_started/pip_snippet.md %} -{% include /get_started/gpu_snippet.md %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/python/gpu/build-from-source.md b/docs/static_site/src/_includes/get_started/windows/python/gpu/build-from-source.md deleted file mode 100644 index 55bca3a129d8..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/python/gpu/build-from-source.md +++ /dev/null @@ -1 +0,0 @@ -To build from source, refer to the [MXNet Windows installation guide](/get_started/windows_setup.html). diff --git a/docs/static_site/src/_includes/get_started/windows/python/gpu/pip.md b/docs/static_site/src/_includes/get_started/windows/python/gpu/pip.md deleted file mode 100644 index cbcd9d44d6af..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/python/gpu/pip.md +++ /dev/null @@ -1,74 +0,0 @@ -Run the following command: - -
- -{% highlight bash %} -$ pip install mxnet-cu101 -{% endhighlight %} - -
-
- -{% highlight bash %} -$ pip install mxnet-cu101==1.4.1 -{% endhighlight %} - -
-
- -{% highlight bash %} -$ pip install mxnet-cu92==1.3.1 -{% endhighlight %} - -
-
- -{% highlight bash %} -$ pip install mxnet-cu92==1.2.1 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet-cu91==1.1.0 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet-cu90==1.0.0 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet-cu90==0.12.1 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet-cu80==0.11.0 -{% endhighlight %} - -
- -
- -{% highlight bash %} -$ pip install mxnet-cu101 --pre -{% endhighlight %} - -
- - -{% include /get_started/pip_snippet.md %} -{% include /get_started/gpu_snippet.md %} \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/r/cpu.md b/docs/static_site/src/_includes/get_started/windows/r/cpu.md deleted file mode 100644 index 926b8355c984..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/r/cpu.md +++ /dev/null @@ -1,15 +0,0 @@ -Note: packages for 3.6.x are not yet available. -Install 3.5.x of R from [CRAN](https://cran.r-project.org/bin/windows/base/old/). - -You can [build MXNet-R from source](/get_started/windows_setup.html#install-mxnet-package-for-r), or -you can use a -pre-built binary: - -{% highlight r %} -cran <- getOption("repos") -cran["dmlc"] <- "https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/R/CRAN/" -options(repos = cran) -install.packages("mxnet") -{% endhighlight %} - -To run MXNet you also should have OpenCV and OpenBLAS installed. diff --git a/docs/static_site/src/_includes/get_started/windows/r/gpu.md b/docs/static_site/src/_includes/get_started/windows/r/gpu.md deleted file mode 100644 index 084f1a5a4012..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/r/gpu.md +++ /dev/null @@ -1,16 +0,0 @@ -You can [build MXNet-R from source](/get_started/windows_setup.html#install-mxnet-package-for-r), or -you can use a -pre-built binary: - -{% highlight r %} -cran <- getOption("repos") -cran["dmlc"] <- -"https://apache-mxnet.s3-accelerate.dualstack.amazonaws.com/R/CRAN/GPU/cu92" -options(repos = cran) -install.packages("mxnet") -{% endhighlight %} - -Change cu92 to cu90, cu91 or cuda100 based on your CUDA toolkit version. Currently, MXNet supports these versions of CUDA. -Note : You also need to have cuDNN installed on Windows. Check out this -[guide](https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#installwindows) -on the steps for installation. \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows/scala/scala.md b/docs/static_site/src/_includes/get_started/windows/scala/scala.md deleted file mode 100644 index 74b7d45c6d79..000000000000 --- a/docs/static_site/src/_includes/get_started/windows/scala/scala.md +++ /dev/null @@ -1 +0,0 @@ -MXNet-Scala for Windows is not yet available. \ No newline at end of file diff --git a/docs/static_site/src/_includes/get_started/windows~b6b40878f... Consolidate installation instructions on website and add disclaimer for non-ASF ressources (#18487) b/docs/static_site/src/_includes/get_started/windows~b6b40878f... Consolidate installation instructions on website and add disclaimer for non-ASF ressources (#18487) new file mode 120000 index 000000000000..9c52cb36f47e --- /dev/null +++ b/docs/static_site/src/_includes/get_started/windows~b6b40878f... Consolidate installation instructions on website and add disclaimer for non-ASF ressources (#18487) @@ -0,0 +1 @@ +linux \ No newline at end of file diff --git a/docs/static_site/src/pages/get_started/build_from_source.md b/docs/static_site/src/pages/get_started/build_from_source.md index 1dfa95a82ade..19f2f1a313ca 100644 --- a/docs/static_site/src/pages/get_started/build_from_source.md +++ b/docs/static_site/src/pages/get_started/build_from_source.md @@ -25,307 +25,381 @@ permalink: /get_started/build_from_source # Build MXNet from Source -This document explains how to build MXNet from source code. - -**For Java/Scala/Clojure, please follow [this guide instead](scala_setup)** - -## Overview - -Building from source follows this general two-step flow of building the shared library, then installing your preferred language binding. Use the following links to jump to the different sections of this guide. - -1. Build the MXNet shared library, `libmxnet.so`. - * [Clone the repository](#clone-the-mxnet-project) - * [Prerequisites](#prerequisites) - * [Math library selection](#math-library-selection) - * [Install GPU software](#install-gpu-software) - * [Install optional software](#install-optional-software) - * [Adjust your build configuration](#build-configurations) - * [Build MXNet](#build-mxnet) - * [with NCCL](#build-mxnet-with-nccl) (optional) - * [for C++](#build-mxnet-with-c++) (optional) - * [Usage Examples](#usage-examples) - * [systems with GPUs and Intel CPUs](#recommended-for-Systems-with-NVIDIA-GPUs-and-Intel-CPUs) - * [GPUs with non-Intel CPUs](#recommended-for-Systems-with-Intel-CPUs) - * [Intel CPUs](#recommended-for-Systems-with-Intel-CPUs) - * [non-Intel CPUs](#recommended-for-Systems-with-non-Intel-CPUs) -2. [Install the language API binding(s)](#installing-mxnet-language-bindings) you would like to use for MXNet. -MXNet's newest and most popular API is Gluon. Gluon is built into the Python binding. If Python isn't your preference, you still have more options. MXNet supports several other language APIs: - - [Python (includes Gluon)]({{'/api/python/docs/api/index.html'|relative_url}}) - - [C++]({{'/api/cpp'|relative_url}}) - - [Clojure]({{'/api/clojure'|relative_url}}) - - [Java]({{'/api/java'|relative_url}}) - - [Julia]({{'/api/julia'|relative_url}}) - - [Perl]({{'/api/perl'|relative_url}}) - - [R]({{'/api/r'|relative_url}}) - - [Scala]({{'/api/scala'|relative_url}}) +Building and installing MXNet from source is a three-step process. First, build +the shared `libmxnet` which provides the MXNet backend, then install your +preferred language binding and finally validate that MXNet was installed +correctly by running a small example. -
+1. [Obtaining the source](#obtaining-the-source-code) +2. [Installing MXNet's recommended dependencies](#installing-mxnet's-recommended-dependencies) +3. [Overview of optional dependencies and optional features](#overview-of-optional-dependencies-and-optional-features) +4. [Building MXNet](#building-mxnet) +5. [Install the language API binding(s)](#installing-mxnet-language-bindings) you would like to use for MXNet. -## Build Instructions by Operating System +MXNet's newest and most popular API is Gluon. Gluon is built into the Python +binding. If Python isn't your preference, you still have more options. MXNet +supports several other language bindings. Please see the [API Documentation +page](/api) for an overview of all supported languages and their APIs. -Detailed instructions are provided per operating system. Each of these guides also covers how to install the specific [Language Bindings](#installing-mxnet-language-bindings) you require. -You may jump to those, but it is recommended that you continue reading to understand more general "build from source" options. -* [Amazon Linux / CentOS / RHEL](centos_setup) -* [macOS](osx_setup) -* [Devices](index.html?&platform=devices&language=python&environ=pip&processor=cpu) -* [Ubuntu](ubuntu_setup) -* [Windows](windows_setup) +## Obtaining the source code +To obtain the source code of the latest Apache MXNet (incubating) release, +please access the [Download page](/get_started/download) and download the +`.tar.gz` source archive corresponding to the release you wish to build. -
+Developers can also obtain the unreleased development code from the git +repository via `git clone --recursive https://github.com/apache/incubator-mxnet mxnet` + +Building a MXNet 1.x release from source requires a C++11 compliant compiler. + +Building the development version of MXNet or any 2.x release from source +requires a C++17 compliant compiler. The oldest compiler versions tested during +MXNet 2 development are GCC 7, Clang 6 and MSVC 2019. -## Clone the MXNet Project +## Installing MXNet's recommended dependencies +To install the build tools and recommended dependencies, please run the +following commands respectively based on your Operating System. Please see the +next section for further explanations on the set of required and optional +dependencies of MXNet. -1. Clone or fork the MXNet project. +### Debian Linux derivatives (Debian, Ubuntu, ...) ```bash git clone --recursive https://github.com/apache/incubator-mxnet mxnet cd mxnet +sudo apt-get update +sudo apt-get install -y build-essential git ninja-build ccache libopenblas-dev libopencv-dev cmake ```
+### Red Hat Enterprise Linux derivatives (RHEL, CentOS, Fedora, ...) +```bash +sudo yum install epel-release centos-release-scl +sudo yum install git make ninja-build automake autoconf libtool protobuf-compiler protobuf-devel \ + atlas-devel openblas-devel lapack-devel opencv-devel openssl-devel zeromq-devel python3 \ + devtoolset-7 +source /opt/rh/devtoolset-7/enable +``` +Here `devtoolset-7` refers to the [Developer Toolset +7](https://www.softwarecollections.org/en/scls/rhscl/devtoolset-7/) created by +Red Hat for developers working on CentOS or Red Hat Enterprise Linux platform +and providing the GNU Compiler Collection 7. + +### macOS +```bash +# Install OS X Developer Tools +xcode-select --install -## Prerequisites +# Install Homebrew +/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)" + +# Install dependencies +brew install cmake ninja ccache opencv +``` + +Note: the compiler provided by Apple on macOS does not support OpenMP. To use +OpenMP on macOS you need to install for example the Clang compiler via `brew`: + +```bash +brew install llvm +``` -The following sections will help you decide which specific prerequisites you need to install. +### Windows +You can use Chocolatey software management solution to install some dependencies +on Windows. -#### Math Library Selection -It is useful to consider your math library selection prior to your other prerequisites. +```bash +choco install python git 7zip cmake ninja opencv +``` + +Currently OpenBLAS is not available from Chocolatey. You may download it from +from [the OpenBLAS release page](https://github.com/xianyi/OpenBLAS/releases) +and compile from source. Set the `OpenBLAS_HOME` environment variable to point +to the OpenBLAS directory that contains the `include` and `lib` directories for +example by typing `set OpenBLAS_HOME=C:\utils\OpenBLAS`. + +If you like to compile MXNet with Visual Studio compiler, please install at +least [VS2019](https://www.visualstudio.com/downloads/). + +## Overview of optional dependencies and optional features + +### Math Library Selection MXNet relies on the [BLAS](https://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms) (Basic -Linear Algebra Subprograms) library for numerical computations. -Those can be extended with [LAPACK (Linear Algebra Package)](https://github.com/Reference-LAPACK/lapack), an additional set of mathematical functions. +Linear Algebra Subprograms) library for numerical computations. In addition to +BLAS, some operators in MXNet rely on the [LAPACK (Linear Algebra +Package)](https://github.com/Reference-LAPACK/lapack), an additional set of +mathematical functions. + +Several BLAS and LAPACK implementations exist. Among them, MXNet is tested with: -MXNet supports multiple mathematical backends for computations on the CPU: * [Apple Accelerate](https://developer.apple.com/documentation/accelerate) * [ATLAS](http://math-atlas.sourceforge.net/) -* [MKL](https://software.intel.com/en-us/intel-mkl) (MKL, MKLML) -* [MKL-DNN](https://github.com/intel/mkl-dnn) +* [Intel MKL](https://software.intel.com/en-us/intel-mkl) * [OpenBLAS](https://www.openblas.net/) -The default order of choice for the libraries if found follows the path from the most -(recommended) to less performant backends. -The following lists show this order by library and `cmake` switch. +Apple Accelerate and MKL are proprietary. ATLAS and OpenBLAS are Open Source. If +you don't have any specific requirements, MXNet recommends OpenBLAS as it +typically outperforms ATLAS, is portable across many platforms, provides a +LAPACK implementation and has a permissive license. -For desktop platforms (x86_64): +### Optional GPU support -1. MKL-DNN (submodule) | `USE_MKLDNN` -2. MKL | `USE_MKL_IF_AVAILABLE` -3. MKLML (downloaded) | `USE_MKLML` -4. Apple Accelerate | `USE_APPLE_ACCELERATE_IF_AVAILABLE` | Mac only -5. OpenBLAS | `BLAS` | Options: Atlas, Open, MKL, Apple +MXNet optionally supports [NVDIA CUDA and +cuDNN](https://developer.nvidia.com/cuda-downloads) for better performance on +NVidia devices. MXNet releases in general are tested with the last two major +CUDA versions available at the time of the release. For example, CUDA 9.2 and +10.2. -Note: If `USE_MKL_IF_AVAILABLE` is set to False then MKLML and MKL-DNN will be disabled as well for configuration -backwards compatibility. +To compile MXNet with CUDA support, define the `USE_CUDA` option. If you compile +MXNet on a system with NVidia GPUs, the build system will automatically detect +the CUDA Architecture. If you are compiling on a system without NVidia GPUs, +please specify the `MXNET_CUDA_ARCH` option to select the CUDA Architecture and +avoid a lengthy build targeting all common CUDA Architectures. Please see the +MXNet build configuration instructions in the next step. -For embedded platforms (all other and if cross compiled): +MXNet also supports [NCCL](https://developer.nvidia.com/nccl) - NVIDIA's +Collective Communications Library. NCCL is useful when using MXNet on multiple +GPUs that require communication. Instructions for installing NCCL are found in +the following [Build MXNet with NCCL](#build-mxnet-with-nccl) section. -1. OpenBLAS | `BLAS` | Options: Atlas, Open, MKL, Apple +To enable building MXNet with NCCL, install NCCL and define the `USE_NCCL` +option in the MXNet build configuration in the next step. -You can set the BLAS library explicitly by setting the BLAS variable to: +After building with NCCL, you may optionally use the tests in +`tests/python/gpu/test_nccl.py` to ensure NCCL is enabled correctly. Please +first delete the line containing `skip(reason="Test requires NCCL library +installed and enabled during build")` before running the test. In MXNet 2.x +versions, the test can be run via `pytest --verbose +tests/python/gpu/test_nccl.py`. In MXNet 1.x it is run via `python +tests/python/gpu/test_nccl.py`. -* Atlas -* Open -* MKL -* Apple +To get the best performance out of NCCL it is recommended to set environment +variable `NCCL_LAUNCH_MODE=PARALLEL` when using NCCL version 2.1 or newer. -See the [cmake/ChooseBLAS.cmake](https://github.com/apache/incubator-mxnet/blob/master/cmake/ChooseBlas.cmake) file for the options. +### Optional OpenCV support -[Intel's MKL (Math Kernel Library)](https://software.intel.com/en-us/mkl) is one of the most powerful math libraries +MXNet's Image Loading and Augmentation features rely on +[OpenCV](http://opencv.org/). Image Loading and Augmentation -It has following flavors: +## Building MXNet -* MKL is a complete math library, containing all the functionality found in ATLAS, OpenBlas and LAPACK. It is free under -community support licensing (https://software.intel.com/en-us/articles/free-mkl), -but needs to be downloaded and installed manually. +MXNet 1.x can be built either with a classic Makefile setup or with the `cmake` +cross platform build system. Starting with MXNet 1.7, MXNet recommends using the +`cmake` cross platform build tool. -* MKLML is a subset of MKL. It contains a smaller number of functions to reduce the -size of the download and reduce the number of dynamic libraries user needs. +Note: The `cmake` build requires CMake 3.13 or higher. If you are running an +older version of CMake, you will see an error message like `CMake 3.13 or higher +is required. You are running version 3.10.2`. Please update CMake on your +system. You can download and install latest CMake from https://cmake.org or via +the Python package manager `pip` with `python3 -m pip install --user --upgrade +"cmake>=3.13.2"`. After installing cmake with `pip3`, it is usually available at +`~/.local/bin/cmake` or directly as `cmake`. - +Please see the [`cmake configuration +files`](https://github.com/apache/incubator-mxnet/tree/v1.x/config) files for +instructions on how to configure and build MXNet with cmake. -* MKL-DNN is a separate open-source library, it can be used separately from MKL or MKLML. It is -shipped as a subrepo with MXNet source code (see 3rdparty/mkldnn or the [MKL-DNN project](https://github.com/intel/mkl-dnn)) +Up to the MXNet 1.6 release, please follow the instructions in the +[`make/config.mk`](https://github.com/apache/incubator-mxnet/blob/v1.x/make/config.mk) +file on how to configure and compile MXNet. This method is supported on all 1.x +releases. -Since the full MKL library is almost always faster than any other BLAS library it's turned on by default, -however it needs to be downloaded and installed manually before doing `cmake` configuration. -Register and download on the [Intel performance libraries website](https://software.intel.com/en-us/performance-libraries). -You can also install MKL through [YUM](https://software.intel.com/en-us/articles/installing-intel-free-libs-and-python-yum-repo) -or [APT](https://software.intel.com/en-us/articles/installing-intel-free-libs-and-python-apt-repo) Repository. +To enable the optional MXNet C++ package, please set the `USE_CPP_PACKAGE=1` +option prior to compiling. See the [C++ guide](cpp_setup) for more information. -Note: MKL is supported only for desktop builds and the framework itself supports the following -hardware: -* Intel® Xeon Phi™ processor -* Intel® Xeon® processor -* Intel® Core™ processor family -* Intel Atom® processor +## Installing MXNet Language Bindings +After building MXNet's shared library, you can install other language bindings. -If you have a different processor you can still try to use MKL, but performance results are -unpredictable. +**NOTE:** The C++ API binding must be built when you build MXNet from source. See [Build MXNet with C++]({{'/api/cpp.html'|relative_url}}). +## Installing Language Packages for MXNet -#### Install GPU Software +After you have installed the MXNet core library. You may install MXNet interface +packages for the programming language of your choice: +- [Python](#install-mxnet-for-python) +- [C++](#install-the-mxnet-package-for-c++) +- [Clojure](#install-the-mxnet-package-for-clojure) +- [Julia](#install-the-mxnet-package-for-julia) +- [Perl](#install-the-mxnet-package-for-perl) +- [R](#install-the-mxnet-package-for-r) +- [Scala](#install-the-mxnet-package-for-scala) +- [Java](#install-the-mxnet-package-for-java) -If you want to run MXNet with GPUs, you must install [NVDIA CUDA and cuDNN](https://developer.nvidia.com/cuda-downloads). +### Install MXNet for Python -#### Install Optional Software +To install the MXNet Python binding navigate to the root of the MXNet folder then run the following: -These might be optional, but they're typically desirable as the extend or enhance MXNet's functionality. +```bash +python3 -m pip install --user -e ./python +``` -* [OpenCV](http://opencv.org/) - Image Loading and Augmentation. Each operating system has different packages and build from source options for OpenCV. Refer to your OS's link in the [Build Instructions by Operating System](#build-instructions-by-operating-system) section for further instructions. -* [NCCL](https://developer.nvidia.com/nccl) - NVIDIA's Collective Communications Library. Instructions for installing NCCL are found in the following [Build MXNet with NCCL](#build-mxnet-with-nccl) section. +Note that the `-e` flag is optional. It is equivalent to `--editable` and means +that if you edit the source files, these changes will be reflected in the +package installed. -More information on turning these features on or off are found in the following [build configurations](#build-configurations) section. +You may optionally install ```graphviz``` library that is used for visualizing +network graphs you build on MXNet. You may also install [Jupyter +Notebook](http://jupyter.readthedocs.io/) which is used for running MXNet +tutorials and examples. +```bash +python3 -m pip install --user graphviz==0.8.4 jupyter +``` -
+Please also see the [MXNet Python API](/api/python) page. -## Build Configurations +### Install the MXNet Package for C++ -There is a configuration file for make, -[`make/config.mk`](https://github.com/apache/incubator-mxnet/blob/master/make/config.mk), that contains all the compilation options. You can edit it and then run `make` or `cmake`. `cmake` is recommended for building MXNet (and is required to build with MKLDNN), however you may use `make` instead. For building with Java/Scala/Clojure, only `make` is supported. +To enable C++ package, just add `USE_CPP_PACKAGE=1` as build option when +building the MXNet shared library following the instructions from the previous +section. -**NOTE:** When certain set of build flags are set, MXNet archive increases to more than 4 GB. Since MXNet uses archive internally archive runs into a bug ("File Truncated": [bugreport](https://sourceware.org/bugzilla/show_bug.cgi?id=14625)) for archives greater than 4 GB. Please use ar version 2.27 or greater to overcome this bug. Please see https://github.com/apache/incubator-mxnet/issues/15084 for more details. +You can find C++ code examples in the `cpp-package/example` folder of the MXNet +project. The folder contains a README explaining how to build the examples. The +`predict-cpp` explains Image Classification using MXNet's C Predict API. -
+Please also see the [MXNet C++ API](/api/cpp) page. -## Build MXNet - -### Build MXNet with NCCL -- Download and install the latest NCCL library from NVIDIA. -- Note the directory path in which NCCL libraries and header files are installed. -- Ensure that the installation directory contains ```lib``` and ```include``` folders. -- Ensure that the prerequisites for using NCCL such as Cuda libraries are met. -- Append the ```config.mk``` file with following, in addition to the CUDA related options. -- USE_NCCL=1 -- USE_NCCL_PATH=path-to-nccl-installation-folder - -``` bash -echo "USE_NCCL=1" >> make/config.mk -echo "USE_NCCL_PATH=path-to-nccl-installation-folder" >> make/config.mk -cp make/config.mk . -``` -- Run make command -``` bash -make -j"$(nproc)" -``` -#### Validating NCCL -- Follow the steps to install MXNet Python binding. -- Comment the following line in ```test_nccl.py``` file at ```incubator-mxnet/tests/python/gpu/test_nccl.py``` -``` bash -@unittest.skip("Test requires NCCL library installed and enabled during build") -``` -- Run test_nccl.py script as follows. The test should complete. It does not produce any output. -``` bash -nosetests --verbose tests/python/gpu/test_nccl.py -``` +### Install the MXNet Package for Clojure -**Recommendation to get the best performance out of NCCL:** -It is recommended to set environment variable NCCL_LAUNCH_MODE to PARALLEL when using NCCL version 2.1 or newer. +Refer to the [Clojure setup +guide](https://github.com/apache/incubator-mxnet/tree/master/contrib/clojure-package). -
+Please also see the [MXNet Clojure API](/api/clojure) page. -### Build MXNet with C++ +### Install the MXNet Package for Julia -* To enable C++ package, just add `USE_CPP_PACKAGE=1` when you run `make` or `cmake` (see examples). +Make sure to install at least Julia 1.0.3. -
+To use the Julia binding you need to set the `MXNET_HOME` and `LD_LIBRARY_PATH` +environment variables. For example, -### Usage Examples +```bash +export MXNET_HOME=$HOME/incubator-mxnet +export LD_LIBRARY_PATH=$HOME/incubator-mxnet/build:$LD_LIBRARY_PATH +``` -For example, you can specify using all cores on Linux as follows: +Then install MXNet with Julia: ```bash -mkdir build && cd build -cmake -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v +julia --color=yes --project=./ -e \ + 'using Pkg; \ + Pkg.develop(PackageSpec(name="MXNet", path = joinpath(ENV["MXNET_HOME"], "julia")))' ``` +Please also see the [MXNet Julia API](/api/julia) page. + -#### Recommended for Systems with NVIDIA GPUs and Intel CPUs -* Build MXNet with `cmake` and install with MKL DNN, GPU, and OpenCV support: +### Install the MXNet Package for Perl +#### Installing perl package dependencies on Debian Linux derivatives (Debian, Ubuntu, ...) + +``` +sudo apt-get install libmouse-perl pdl cpanminus swig libgraphviz-perl +cpanm -q -L "${HOME}/perl5" Function::Parameters Hash::Ordered PDL::CCS +``` + +#### Installing perl package dependencies on macOS ```bash -mkdir build && cd build -cmake -DUSE_CUDA=1 -DUSE_CUDA_PATH=/usr/local/cuda -DUSE_CUDNN=1 -DUSE_MKLDNN=1 -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v +brew install swig +sudo sh -c 'curl -L https://cpanmin.us | perl - App::cpanminus' +sudo cpanm -q -n PDL Mouse Function::Parameters Hash::Ordered PDL::CCS ``` -#### Recommended for Systems with NVIDIA GPUs -* Build with both OpenBLAS, GPU, and OpenCV support: +#### Install the MXNet Package for Perl +After you build the shared library, run the following command from the MXNet +source root directory to build the MXNet Perl package: ```bash -mkdir build && cd build -cmake -DBLAS=open -DUSE_CUDA=1 -DUSE_CUDA_PATH=/usr/local/cuda -DUSE_CUDNN=1 -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v +MXNET_HOME=${PWD} +export LD_LIBRARY_PATH=${MXNET_HOME}/lib +export PERL5LIB=${HOME}/perl5/lib/perl5 + +cd ${MXNET_HOME}/perl-package/AI-MXNetCAPI/ +perl Makefile.PL INSTALL_BASE=${HOME}/perl5 +make install + +cd ${MXNET_HOME}/perl-package/AI-NNVMCAPI/ +perl Makefile.PL INSTALL_BASE=${HOME}/perl5 +make install + +cd ${MXNET_HOME}/perl-package/AI-MXNet/ +perl Makefile.PL INSTALL_BASE=${HOME}/perl5 +make install ``` -#### Recommended for Systems with Intel CPUs -* Build MXNet with `cmake` and install with MKL DNN, and OpenCV support: +Please also see the [MXNet Perl API](/api/perl) page. + +### Install the MXNet Package for R + +To install R and the devtools, run ```bash -mkdir build && cd build -cmake -DUSE_CUDA=0 -DUSE_MKLDNN=1 -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v +sudo apt-get update +sudo apt-get install -y r-base-core r-cran-devtools libcairo2-dev libxml2-dev ``` -#### Recommended for Systems with non-Intel CPUs -* Build MXNet with `cmake` and install with OpenBLAS and OpenCV support: +`libxml2-dev` is required for the `roxygen2` dependency and `libcairo2-dev` is +required for the suggested `imager` dependency. + +To generate documentation, it is also required to install `roxygen2`. ```bash -mkdir build && cd build -cmake -DUSE_CUDA=0 -DBLAS=open -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v +R +> install.packages("roxygen2") +> Would you like to use a personal library instead? (y/n) y +> Would you like to create a personal library ... to install packages into? (y/n) y ``` -#### Other Examples +Note: To successfully complete the next step, you need a personal R library. If +you were able to run `install.packages("roxygen2")` above, you either had +already, or you have successfully created a personal library just now. -* Build without using OpenCV: +To build and install the MXNet-R bindings, run: ```bash -mkdir build && cd build -cmake -DUSE_OPENCV=0 -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v +make -f R-package/Makefile rpkg ``` -* Build on **macOS** with the default BLAS library (Apple Accelerate) and Clang installed with `xcode` (OPENMP is disabled because it is not supported by the Apple version of Clang): +Please also see the [MXNet R API](/api/r) page. + +### Install the MXNet Package for Scala + +After building the MXNet shared library, you may simply run the following from +the MXNet scala-package folder: ```bash -mkdir build && cd build -cmake -DBLAS=apple -DUSE_OPENCV=0 -DUSE_OPENMP=0 -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v +mvn install ``` -* To use OpenMP on **macOS** you need to install the Clang compiler, `llvm` (the one provided by Apple does not support OpenMP): +This will install both the Java Inference API and the required MXNet-Scala package.
+ +Please also see the [MXNet Scala API](/api/scala) page. + +### Install the MXNet Package for Java + +After building the MXNet shared library, you may simply run the following from +the MXNet scala-package folder: ```bash -brew install llvm -mkdir build && cd build -cmake -DBLAS=apple -DUSE_OPENMP=1 -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v +mvn install ``` -
+This will install both the Java Inference API and the required MXNet-Scala package.
-## Installing MXNet Language Bindings -After building MXNet's shared library, you can install other language bindings. +Please also see the [MXNet Java API](/api/java) page. -**NOTE:** The C++ API binding must be built when you build MXNet from source. See [Build MXNet with C++]({{'/api/cpp'|relative_url}}). +## Contributions -The following table provides links to each language binding by operating system: +You are more than welcome to contribute easy installation scripts for other operating systems and programming languages. +See the [community contributions page]({{'/community/contribute'|relative_url}}) for further information. -| Language | [Ubuntu](ubuntu_setup) | [macOS](osx_setup) | [Windows](windows_setup) | -| --- | ---- | --- | ------- | -| Python | [Ubuntu guide](ubuntu_setup.html#install-mxnet-for-python) | [OSX guide](osx_setup) | [Windows guide](windows_setup.html#install-mxnet-for-python) | -| C++ | [C++ guide](cpp_setup) | [C++ guide](cpp_setup) | [C++ guide](cpp_setup) | -| Clojure | [Clojure guide](https://github.com/apache/incubator-mxnet/tree/master/contrib/clojure-package) | [Clojure guide](https://github.com/apache/incubator-mxnet/tree/master/contrib/clojure-package) | n/a | -| Julia | [Ubuntu guide](ubuntu_setup.html#install-the-mxnet-package-for-julia) | [OSX guide](osx_setup.html#install-the-mxnet-package-for-julia) | [Windows guide](windows_setup.html#install-the-mxnet-package-for-julia) | -| Perl | [Ubuntu guide](ubuntu_setup.html#install-the-mxnet-package-for-perl) | [OSX guide](osx_setup.html#install-the-mxnet-package-for-perl) | n/a | -| R | [Ubuntu guide](ubuntu_setup.html#install-the-mxnet-package-for-r) | [OSX guide](osx_setup.html#install-the-mxnet-package-for-r) | [Windows guide](windows_setup.html#install-the-mxnet-package-for-r) | -| Scala | [Scala guide](scala_setup.html) | [Scala guide](scala_setup.html) | n/a | -| Java | [Java guide](java_setup.html) | [Java Guide](java_setup.html) | n/a | +## Next Steps +* [Tutorials]({{'/api'|relative_url}}) +* [How To]({{'/api/faq/add_op_in_backend'|relative_url}}) +* [Architecture]({{'/api/architecture/overview'|relative_url}}) diff --git a/docs/static_site/src/pages/get_started/c_plus_plus.md b/docs/static_site/src/pages/get_started/c_plus_plus.md deleted file mode 100644 index 9f4800cd99bf..000000000000 --- a/docs/static_site/src/pages/get_started/c_plus_plus.md +++ /dev/null @@ -1,55 +0,0 @@ ---- -layout: page -title: C++ Setup -action: Get Started -action_url: /get_started -permalink: /get_started/cpp_setup ---- - - - - - - - - - - - - - - - - - - -## Build the C++ package -The C++ package has the same prerequisites as the MXNet library. - -To enable C++ package, just add `USE_CPP_PACKAGE=1` in the [build from source](build_from_source) options when building the MXNet shared library. - -For example to build MXNet with GPU support and the C++ package, OpenCV, and OpenBLAS, from the project root you would run: - -```bash -cmake -DUSE_CUDA=1 -DUSE_CUDA_PATH=/usr/local/cuda -DUSE_CUDNN=1 -DUSE_MKLDNN=1 -DUSE_CPP_PACKAGE=1 -DCMAKE_BUILD_TYPE=Release -GNinja .. -ninja -v -``` - -You may also want to add the MXNet shared library to your `LD_LIBRARY_PATH`: - -```bash -export LD_LIBRARY_PATH=~/incubator-mxnet/lib -``` - -Setting the `LD_LIBRARY_PATH` is required to run the examples mentioned in the following section. - -## C++ Example Code -You can find C++ code examples in the `cpp-package/example` folder of the MXNet project. Refer to the [cpp-package's README](https://github.com/apache/incubator-mxnet/tree/master/cpp-package) for instructions on building the examples. - -## Tutorials - -* [MXNet C++ API Basics]({{'/api/cpp/docs/tutorials/basics'|relative_url}}) - -## Related Topics - -* [Image Classification using MXNet's C Predict API](https://github.com/apache/incubator-mxnet/tree/master/example/image-classification/predict-cpp) diff --git a/docs/static_site/src/pages/get_started/centos_setup.md b/docs/static_site/src/pages/get_started/centos_setup.md deleted file mode 100644 index 315787d21f28..000000000000 --- a/docs/static_site/src/pages/get_started/centos_setup.md +++ /dev/null @@ -1,115 +0,0 @@ ---- -layout: page -title: CentOS setup -action: Get Started -action_url: /get_started -permalink: /get_started/centos_setup ---- - - - - - - - - - - - - - - - - - - -# Installing MXNet on CentOS and other non-Ubuntu Linux systems - -Step 1. Install build tools and git on `CentOS >= 7` and `Fedora >= 19`: - -```bash -sudo yum groupinstall -y "Development Tools" && sudo yum install -y git -``` - -Step 2. Install Atlas: - -```bash -sudo yum install atlas-devel -``` - -Installing both `git` and `cmake` or `make` by following instructions on the websites is -straightforward. Here we provide the instructions to build `gcc-4.8` from source codes. - -Step 3. Install the 32-bit `libc` with one of the following system-specific commands: - -```bash -sudo apt-get install libc6-dev-i386 # In Ubuntu -sudo yum install glibc-devel.i686 # In RHEL (Red Hat Linux) -sudo yum install glibc-devel.i386 # In CentOS 5.8 -sudo yum install glibc-devel.i686 # In CentOS 6/7 -``` - -Step 4. Download and extract the `gcc` source code with the prerequisites: - -```bash -wget http://mirrors.concertpass.com/gcc/releases/gcc-4.8.5/gcc-4.8.5.tar.gz -tar -zxf gcc-4.8.5.tar.gz -cd gcc-4.8.5 -./contrib/download_prerequisites -``` - -Step 5. Build `gcc` by using 10 threads and then install to `/usr/local` - -```bash -mkdir release && cd release -../configure --prefix=/usr/local --enable-languages=c,c++ -make -j10 -sudo make install -``` - -Step 6. Add the lib path to your configure file such as `~/.bashrc`: - -```bash -export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/lib64 -``` - -Step 7. Build [OpenBLAS from source](https://github.com/xianyi/OpenBLAS#installation-from-source). - -Step 8. Build OpenCV - -To build OpenCV from source code, you need the [cmake](https://cmake.org) library. - -* If you don't have cmake or if your version of cmake is earlier than 3.6.1, run the following commands to install a newer version of cmake: - -```bash -wget https://cmake.org/files/v3.6/cmake-3.6.1-Linux-x86_64.tar.gz -tar -zxvf cmake-3.6.1-Linux-x86_64.tar.gz -alias cmake="cmake-3.6.1-Linux-x86_64/bin/cmake" -``` - -* To download and extract the OpenCV source code, run the following commands: - -```bash -wget https://codeload.github.com/opencv/opencv/zip/2.4.13 -unzip 2.4.13 -cd opencv-2.4.13 -mkdir release -cd release/ -``` - -* Build OpenCV. The following commands build OpenCV with 10 threads. We -disabled GPU support, which might significantly slow down an MXNet program -running on a GPU processor. It also disables 1394 which might generate a -warning. Then install it on `/usr/local`. - -```bash -cmake -D BUILD_opencv_gpu=OFF -D WITH_CUDA=OFF -D WITH_1394=OFF -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local .. -make -j10 -sudo make install -``` - -* Add the lib path to your configuration such as `~/.bashrc`. - -```bash -export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig/ -``` diff --git a/docs/static_site/src/pages/get_started/download.md b/docs/static_site/src/pages/get_started/download.md index cf3f8c1ddf48..eb07b3b7dceb 100644 --- a/docs/static_site/src/pages/get_started/download.md +++ b/docs/static_site/src/pages/get_started/download.md @@ -25,16 +25,23 @@ permalink: /get_started/download # Source Download -These source archives are generated from tagged releases. Updates and patches will not have been applied. For any updates refer to the corresponding branches in the [GitHub repository](https://github.com/apache/incubator-mxnet). Choose your flavor of download from the following links: +The source archives listed on this page are official MXNet releases following +the [Apache Software Foundation Release +Policy](http://www.apache.org/legal/release-policy.html). + +If you would like to actively participate in the MXNet development, you are +encouraged to contribute to our development version on +[GitHub](https://github.com/apache/incubator-mxnet). | Version | Source | PGP | SHA | |---------|-------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------| -| 1.5.1 | [Download](https://www.apache.org/dyn/closer.cgi/incubator/mxnet/1.5.1/apache-mxnet-src-1.5.1-incubating.tar.gz) | [Download](https://apache.org/dist/incubator/mxnet/1.5.1/apache-mxnet-src-1.5.1-incubating.tar.gz.asc) | [Download](https://apache.org/dist/incubator/mxnet/1.5.1/apache-mxnet-src-1.5.1-incubating.tar.gz.sha512) | -| 1.5.0 | [Download](https://www.apache.org/dyn/closer.cgi/incubator/mxnet/1.5.0/apache-mxnet-src-1.5.0-incubating.tar.gz) | [Download](https://apache.org/dist/incubator/mxnet/1.5.0/apache-mxnet-src-1.5.0-incubating.tar.gz.asc) | [Download](https://apache.org/dist/incubator/mxnet/1.5.0/apache-mxnet-src-1.5.0-incubating.tar.gz.sha512) | -| 1.4.1 | [Download](https://www.apache.org/dyn/closer.cgi/incubator/mxnet/1.4.1/apache-mxnet-src-1.4.1-incubating.tar.gz) | [Download](https://apache.org/dist/incubator/mxnet/1.4.1/apache-mxnet-src-1.4.1-incubating.tar.gz.asc) | [Download](https://apache.org/dist/incubator/mxnet/1.4.1/apache-mxnet-src-1.4.1-incubating.tar.gz.sha512) | -| 1.4.0 | [Download](https://www.apache.org/dyn/closer.cgi/incubator/mxnet/1.4.0/apache-mxnet-src-1.4.0-incubating.tar.gz) | [Download](https://apache.org/dist/incubator/mxnet/1.4.0/apache-mxnet-src-1.4.0-incubating.tar.gz.asc) | [Download](https://apache.org/dist/incubator/mxnet/1.4.0/apache-mxnet-src-1.4.0-incubating.tar.gz.sha512) | -| 1.3.1 | [Download](https://www.apache.org/dyn/closer.cgi/incubator/mxnet/1.3.1/apache-mxnet-src-1.3.1-incubating.tar.gz) | [Download](https://apache.org/dist/incubator/mxnet/1.3.1/apache-mxnet-src-1.3.1-incubating.tar.gz.asc) | [Download](https://apache.org/dist/incubator/mxnet/1.3.1/apache-mxnet-src-1.3.1-incubating.tar.gz.sha512) | -| 1.3.0 | [Download](https://www.apache.org/dyn/closer.cgi/incubator/mxnet/1.3.0/apache-mxnet-src-1.3.0-incubating.tar.gz) | [Download](https://apache.org/dist/incubator/mxnet/1.3.0/apache-mxnet-src-1.3.0-incubating.tar.gz.asc) | [Download](https://apache.org/dist/incubator/mxnet/1.3.0/apache-mxnet-src-1.3.0-incubating.tar.gz.sha512) | +| 1.6.0 | [Download](https://www.apache.org/dyn/closer.cgi/incubator/mxnet/1.6.0/apache-mxnet-src-1.6.0-incubating.tar.gz) | [Download](https://downloads.apache.org/incubator/mxnet/1.6.0/apache-mxnet-src-1.6.0-incubating.tar.gz.asc) | [Download](https://downloads.apache.org/incubator/mxnet/1.6.0/apache-mxnet-src-1.6.0-incubating.tar.gz.sha512) | +| 1.5.1 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.5.1/apache-mxnet-src-1.5.1-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.5.1/apache-mxnet-src-1.5.1-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.5.1/apache-mxnet-src-1.5.1-incubating.tar.gz.sha512) | +| 1.5.0 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.5.0/apache-mxnet-src-1.5.0-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.5.0/apache-mxnet-src-1.5.0-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.5.0/apache-mxnet-src-1.5.0-incubating.tar.gz.sha512) | +| 1.4.1 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.4.1/apache-mxnet-src-1.4.1-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.4.1/apache-mxnet-src-1.4.1-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.4.1/apache-mxnet-src-1.4.1-incubating.tar.gz.sha512) | +| 1.4.0 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.4.0/apache-mxnet-src-1.4.0-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.4.0/apache-mxnet-src-1.4.0-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.4.0/apache-mxnet-src-1.4.0-incubating.tar.gz.sha512) | +| 1.3.1 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.3.1/apache-mxnet-src-1.3.1-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.3.1/apache-mxnet-src-1.3.1-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.3.1/apache-mxnet-src-1.3.1-incubating.tar.gz.sha512) | +| 1.3.0 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.3.0/apache-mxnet-src-1.3.0-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.3.0/apache-mxnet-src-1.3.0-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.3.0/apache-mxnet-src-1.3.0-incubating.tar.gz.sha512) | | 1.2.1 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.2.1/apache-mxnet-src-1.2.1-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.2.1/apache-mxnet-src-1.2.1-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.2.1/apache-mxnet-src-1.2.1-incubating.tar.gz.sha512) | | 1.2.0 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.2.0/apache-mxnet-src-1.2.0-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.2.0/apache-mxnet-src-1.2.0-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.2.0/apache-mxnet-src-1.2.0-incubating.tar.gz.sha512) | | 1.1.0 | [Download](https://archive.apache.org/dist/incubator/mxnet/1.1.0/apache-mxnet-src-1.1.0-incubating.tar.gz) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.1.0/apache-mxnet-src-1.1.0-incubating.tar.gz.asc) | [Download](https://archive.apache.org/dist/incubator/mxnet/1.1.0/apache-mxnet-src-1.1.0-incubating.tar.gz.sha512) | diff --git a/docs/static_site/src/pages/get_started/index.html b/docs/static_site/src/pages/get_started/index.html index 02e7cf1b8641..f83396e28e10 100644 --- a/docs/static_site/src/pages/get_started/index.html +++ b/docs/static_site/src/pages/get_started/index.html @@ -22,12 +22,18 @@ -{% include /get_started/get_started.html %} -
-

Download from source

-

The signed source code for Apache MXNet (incubating) is available for download here

+

Build and install Apache MXNet (incubating) from source

+

+ To build and install MXNet from the official Apache Software Foundation + signed source code please follow our Building From Source guide. +

+

+ The signed source releases are available here +

+ +{% include /get_started/get_started.html %} diff --git a/docs/static_site/src/pages/get_started/validate_mxnet.md b/docs/static_site/src/pages/get_started/validate_mxnet.md index d613c3bf0508..392682acc6e7 100644 --- a/docs/static_site/src/pages/get_started/validate_mxnet.md +++ b/docs/static_site/src/pages/get_started/validate_mxnet.md @@ -73,75 +73,6 @@ array([[ 3., 3., 3.], ``` -## Verify GPU Training - -From the MXNet root directory run: `python example/image-classification/train_mnist.py --network lenet --gpus 0` to test GPU training. - - -## Virtualenv - -Activate the virtualenv environment created for *MXNet*. - -```bash -$ source ~/mxnet/bin/activate -``` - -After activating the environment, you should see the prompt as below. - -```bash -(mxnet)$ -``` - -Start the python terminal. - -```bash -$ python -``` - -Run the previous Python example. - - -## Docker with CPU - -Launch a Docker container with `mxnet/python` image and run example *MXNet* python program on the terminal. - -```bash -$ docker run -it mxnet/python bash # Use sudo if you skip Step 2 in the installation instruction - -# Start a python terminal -root@4919c4f58cac:/# python -``` - -Run the previous Python example. - - -## Docker with GPU - -Launch a NVIDIA Docker container with `mxnet/python:gpu` image and run example *MXNet* python program on the terminal. - -```bash -$ nvidia-docker run -it mxnet/python:gpu bash # Use sudo if you skip Step 2 in the installation instruction - -# Start a python terminal -root@4919c4f58cac:/# python -``` - -Run the previous Python example and run the previous GPU examples. - - -## Cloud - -Login to the cloud instance you launched, with pre-installed *MXNet*, following the guide by corresponding cloud provider. - -Start the python terminal. - -```bash -$ python -``` - -Run the previous Python example, and for GPU instances run the previous GPU example. - - ## Alternative Language Bindings ### C++