add TF 2.0 + CUDA 10.1 build (compat with PyTorch)

README.md

@@ -16,33 +16,35 @@ The builds enable CPU optimizations such as `SSE4`, `AVX2`, and `FMA`. If you ha
 Additionally, build enables [XLA](https://www.tensorflow.org/xla/) - an Accelerated Linear Algebra domain-specific just-in-time compiler, and [MPI](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/mpi) - a faster way to run distributed TensorFlow than what is offered built-in.
 
 ## Available Wheels
-|TensorFlow|CUDA|CuDNN|TensorRT|Python|NCCL|Compute Capability|OS|Link|
+|TensorFlow|Python|CUDA|CuDNN|TensorRT|NCCL|Compute Capability|OS|Link|
 |---:|---:|---:|---:|---:|---:|---:|:---:|:---:|
-|2.0.0a0|10.0|7.5|5.0|3.7|2.4|5.0, 6.1, 7.0|Linux|[tensorflow-2.0.0a0-cp37-cp37m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v2.0.0a0/tensorflow-2.0.0a0-cp37-cp37m-linux_x86_64.whl)|
-|1.13.1|10.0|7.5|5.0|3.7|2.4|5.0, 6.1, 7.0|Linux|[tensorflow-1.13.1-cp37-cp37m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.13.1-py37/tensorflow-1.13.1-cp37-cp37m-linux_x86_64.whl)|
-|1.13.1|10.0|7.3|N/A|3.6|2.3|5.0, 6.1, 7.0|Linux|[tensorflow-1.13.1-cp36-cp36m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.13.1/tensorflow-1.13.1-cp36-cp36m-linux_x86_64.whl)|
-|1.12.0|10.0|7.3|N/A|3.6|2.3|5.0, 6.1, 7.0|Linux|[tensorflow-1.12.0-cp36-cp36m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.12.0/tensorflow-1.12.0-cp36-cp36m-linux_x86_64.whl)|
-|1.11.0|10.0|7.3|N/A|3.6|2.3|6.1|Linux|[tensorflow-1.11.0-cp36-cp36m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.11.0/tensorflow-1.11.0-cp36-cp36m-linux_x86_64.whl)|
-|1.10.0|9.2|7.2|N/A|3.6|2.2|6.1|Linux|[tensorflow-1.10.0-cp36-cp36m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.10.0/tensorflow-1.10.0-cp36-cp36m-linux_x86_64.whl)|
+|2.0.0|3.7|10.1|7.5|N/A|2.4|5.0,6.1,7.0|Linux|[tensorflow-2.0.0-cp37-cp37m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v2.0.0/tensorflow-2.0.0-cp37-cp37m-linux_x86_64.whl)|
+|1.13.1|3.7|10.0|7.5|5.0|2.4|5.0,6.1,7.0|Linux|[tensorflow-1.13.1-cp37-cp37m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.13.1-py37/tensorflow-1.13.1-cp37-cp37m-linux_x86_64.whl)|
+|1.13.1|3.6|10.0|7.3|N/A|2.3|5.0,6.1,7.0|Linux|[tensorflow-1.13.1-cp36-cp36m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.13.1/tensorflow-1.13.1-cp36-cp36m-linux_x86_64.whl)|
+|1.12.0|3.6|10.0|7.3|N/A|2.3|5.0,6.1,7.0|Linux|[tensorflow-1.12.0-cp36-cp36m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.12.0/tensorflow-1.12.0-cp36-cp36m-linux_x86_64.whl)|
+|1.11.0|3.6|10.0|7.3|N/A|2.3|6.1|Linux|[tensorflow-1.11.0-cp36-cp36m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.11.0/tensorflow-1.11.0-cp36-cp36m-linux_x86_64.whl)|
+|1.10.0|3.6|9.2|7.2|N/A|2.2|6.1|Linux|[tensorflow-1.10.0-cp36-cp36m-linux_x86_64.whl](https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v1.10.0/tensorflow-1.10.0-cp36-cp36m-linux_x86_64.whl)|
 
 
 ## Installation
 
 Assuming you have all the requirements, you can install the wheel directly via pip:
 
 ```
-pip install https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v2.0.0a0/tensorflow-2.0.0a0-cp37-cp37m-linux_x86_64.whl
+pip install https://github.com/inoryy/tensorflow-optimized-wheels/releases/download/v2.0.0/tensorflow-2.0.0-cp37-cp37m-linux_x86_64.whl
 ```
 And verify the installation (notice no warning messages):
 
 ```
-python
-Python 3.7.1 | packaged by conda-forge | (default, Mar 13 2019, 12:57:14) 
-[GCC 7.3.0] :: Anaconda, Inc. on linux
-Type "help", "copyright", "credits" or "license" for more information.
 >>> import tensorflow as tf
 >>> tf.__version__
-'2.0.0-alpha0'
+'2.0.0'
+>>> tf.executing_eagerly()
+True
+>>> tf.constant([123]) + tf.constant([321])
+2019-12-30 17:47:56.055840: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
+...
+<tf.Tensor: id=2, shape=(1,), dtype=int32, numpy=array([444], dtype=int32)>
 ```
 
 ## Requests