For a while now, the most reliable two ways to get TensorFlow installed is to either use the pip package, or compile from source.
Compiling TensorFlow from source takes hours, and still prone to errors (see "Failed Attempts at Building TensorFlow GPU from Source"). While the pip package is relatively easier, getting the GPU version of TensorFlow installed using pip was a hassle.
But not anymore. Because the conda native TensorFlow packages are here now.
Installing is quite easy.
Note: Don't install the pip and conda versions of TensorFlow on the same conda environment. If you already have the pip version installed uninstall it using,
pip uninstall tensorflow
To install the CPU version of TensorFlow, just run,
conda install tensorflow
To install the GPU version,
conda install tensorflow-gpu
And the best part is, you DON'T need to have GUDA Toolkit or the cuDNN library already installed!
The conda package installer will install isolated versions of CUDA and cuDNN within your conda environment automatically as part of the installation without interfering with any other CUDA installations in the system.
You can see that in the package installation list,
---------------------------|-----------------
mkl-2019.0 | 118 178.1 MB
mkl_fft-1.0.6 | py36hdbbee80_0 120 KB
python-3.6.6 | hea74fb7_0 21.6 MB
termcolor-1.1.0 | py36_1 8 KB
astor-0.7.1 | py36_0 44 KB
cudatoolkit-9.0 | 1 339.8 MB
setuptools-40.4.3 | py36_0 576 KB
intel-openmp-2019.0 | 118 1.7 MB
grpcio-1.12.1 | py36h1a1b453_0 1.4 MB
protobuf-3.6.0 | py36he025d50_0 517 KB
vs2015_runtime-14.15.26706 | h3a45250_0 2.2 MB
_tflow_1100_select-0.0.1 | gpu 3 KB
tensorflow-base-1.10.0 |gpu_py36h6e53903_0 172.0 MB
numpy-1.15.2 | py36ha559c80_0 48 KB
six-1.11.0 | py36_1 21 KB
tensorboard-1.10.0 | py36he025d50_0 3.3 MB
gast-0.2.0 | py36_0 15 KB
cudnn-7.1.4 | cuda9.0_0 192.3 MB
tensorflow-gpu-1.10.0 | hf154084_0 3 KB
absl-py-0.5.0 | py36_0 146 KB
numpy-base-1.15.2 | py36h8128ebf_0 3.9 MB
vc-14.1 | h0510ff6_4 6 KB
markdown-2.6.11 | py36_0 122 KB
mkl_random-1.0.1 | py36h77b88f5_1 268 KB
wheel-0.32.1 | py36_0 52 KB
tensorflow-1.10.0 |gpu_py36h3514669_0 4 KB
libprotobuf-3.6.0 | h1a1b453_0 2.0 MB
------------------------------------------------------------
Total: 920.0 MB
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| TensorFlow Conda packages being installed |
Check the full installation steps here,
The conda versions of the TensorFlow packages were compiled with the Intel® MKL-DNN library (Math Kernel Library), which can give up to 8X performance boost in certain workloads.
 |
| TensorFlow Conda synthetic benchmarks (source) |
We'll be doing our own set of benchmarks soon.
Related links
- https://www.anaconda.com/blog/developer-blog/tensorflow-in-anaconda/
- https://towardsdatascience.com/stop-installing-tensorflow-using-pip-for-performance-sake-5854f9d9eb0c
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