Update documentation regarding compatibility (#1562)

* Update documentation regarding compatibility

* Update README.md

Co-Authored-By: Gabriel de Marmiesse <[email protected]>

* Update README.md

Co-Authored-By: Gabriel de Marmiesse <[email protected]>

* Split compatibility matrix

Co-authored-by: Gabriel de Marmiesse <[email protected]>

Author: seanpmorgan

Diff for: README.md

@@ -63,13 +63,43 @@ import tensorflow as tf
 import tensorflow_addons as tfa
 ```
 
-#### Linux Build Matrix
-| Version    | Compatible With |Python versions  | Compiler  | cuDNN | CUDA | 
-|:----------------------- |:---|:---------- |:---------|:---------|:---------|
-| tfa-nightly | tensorflow==2.1.0 | 3.5-3.7 | GCC 7.3.1 | 7.6 | 10.1 |
-| tensorflow-addons-0.8.2 | tensorflow==2.1.0 |3.5-3.7 | GCC 7.3.1 | 7.6 | 10.1 |
-| tensorflow-addons-0.7.1 | tensorflow==2.1.0 | 2.7, 3.5-3.7 | GCC 7.3.1 | 7.6 | 10.1 |
-| tensorflow-addons-0.6.0 | tensorflow==2.0.0 | 2.7, 3.5-3.7 | GCC 7.3.1 | 7.4 | 10.0 |
+### Python Op Compatility
+TensorFlow Addons is actively working towards forward compatiblity with TF2.x. 
+However there are still a few private API uses within the respository so at the moment 
+we can only gurentee compatibility with the versions of TF which it was tested against. 
+Warnings will be emitted during TFA import if your TensorFlow version does not match 
+what it was tested against.
+
+#### Python-Op Compatibility Matrix
+| TFA Version    | TensorFlow | Python  |
+|:----------------------- |:---|:---------- |
+| tfa-nightly | 2.1, 2.2 | 3.5, 3.6, 3.7 | 
+| tensorflow-addons-0.8.3 | 2.1 |3.5, 3.6, 3.7 |
+| tensorflow-addons-0.7.1 | 2.1 | 2.7, 3.5, 3.6, 3.7 | 
+| tensorflow-addons-0.6.0 | 2.0 | 2.7, 3.5, 3.6, 3.7 |
+
+### C++ Custom Op Compatibility
+TensorFlow C++ APIs are not stable and thus we can only guarentee compatibility with the 
+version TFA was built against. It is possible custom-ops will work with multiple 
+versions of TF, but there is also a chance for segfault or other problematic crash.
+Warnings will be emitted when loading a custom op if your TensorFlow version does not match 
+what it was built against.
+
+Additionally, registering custom-ops does not have an ABI stable interface so it is 
+required that users have a compatible installation of TensorFlow even if the versions 
+match what we had build against. A simplification of this is that **TensorFlow Addons 
+custom-ops will work with pip installed TensorFlow** but will have issues with TF 
+compiled differently. A typical reason for this would be conda installed TensorFlow.
+[RFC #133](https://github.com/tensorflow/community/pull/133) aims to fix this.
+
+
+#### Custom-Op Compatibility Matrix
+| TFA Version    | TensorFlow | Compiler  | cuDNN | CUDA | 
+|:----------------------- |:---- |:---------|:---------|:---------|
+| tfa-nightly | 2.1 | GCC 7.3.1 | 7.6 | 10.1 |
+| tensorflow-addons-0.8.3 | 2.1  | GCC 7.3.1 | 7.6 | 10.1 |
+| tensorflow-addons-0.7.1 | 2.1  | GCC 7.3.1 | 7.6 | 10.1 |
+| tensorflow-addons-0.6.0 | 2.0  | GCC 7.3.1 | 7.4 | 10.0 |
 
 
 #### Nightly Builds
@@ -113,8 +143,9 @@ TF-Addons. In order to achieve these we require that our additions
 conform to established API patterns seen in core TensorFlow.
 
 #### GPU/CPU Custom-Ops
-A major benefit of TensorFlow Addons is that there are precompiled ops for CPU/GPU.
-Currently however, GPU custom ops only work for Linux distributions. For this reason Windows and MacOS will fallback to pure TensorFlow Python implementations whenever possible.
+TensorFlow Addons supports precompiled custom ops for CPU/GPU. Currently however, 
+GPU custom ops only work for Linux distributions. For this reason Windows and MacOS 
+will fallback to pure TensorFlow Python implementations whenever possible.
 
 The order of priority in MacOS/Windows:
 1) Pure TensorFlow + Python implementation (work on cpu+gpu)