So far we only released source code in past tvm releases, and we will continue 
to do so.

As we continue to develop tvm, we also see some demand for convenient binary 
packages, such as wheel or docker binaries. One important factor of such binary 
packages is the potential links with third party SDKs, a typical example is 
CUDA for Nvidia GPUs. Because some resulting binaries are subject to additional 
terms(e.g. CUDA EULA), the resulting binaries may not be Apache license 
compatible.

Notably, it is acceptable for users to use the binary package, as they already 
accepted the CUDA EULA when they install the CUDA dependencies. This is one 
benefit for producing source release, we can make sure that the source release 
is 100% ALv2 compatible from the licensing point of view.

The current ASF policy disallows non-apache compatible binaries to use the 
project name. As an Apache project, it is important for us to comply and 
protect the Apache brand. As a result, we will not use tvm to name the binary 
artifact.

ASF does allow third-party releases to be created using a different name, e.g. 
Foo, powered by Apache TVM.

To better help the community while complying with the ASF policy, we(as a group 
of individual volunteers) decided to create tlcpack -- tensor learning compiler 
binary package powered by Apache TVM. tlcpack **does not** contain any 
additional source code addons, and is only a collection of binary builds that 
build from the official tvm source by turning on different build 
configurations. Notably, the only difference is in the package naming, the idea 
is that the users can do

```
pip install tlcpack -f https://tlcpack.ai/wheels.html
python
>> import tvm # tvm will be available.
```

There are 4 versions of tlcpack wheels: tlcpack (for cpu only), tlcpack-cu100 
(for CUDA 10.0), tlcpack-cu101 (for CUDA 10.1), and tlcpack-cu102 (for CUDA 
10.2). The supported Python versions are 3.6, 3.7, and 3.8. Currently, only the 
linux platform is supported. The wheels for MacOS and Windows will be released 
in the future. We plan to update the wheels every month to keep up with the 
latest updates in the TVM.

We also provide docker images to provide convenient services to the community 
developers who want to use them. Notably, the volunteers are releasing tlcpack 
not wearing Apache hats. We have clear disclaimers that these binary releases 
are not official Apache releases. The name tlcpack is picked so that it is 
clearly distinguished from the official Apache source release.

Wearing ASF hats, we will continue to work together with the community to 
produce high-quality source releases that comply with the Apache release policy.

co-author @tqchen





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