tensorflow should not be listed as dependency in setup.py

Describe the bug The stellargraph library includes tensorflow (i.e., "tensorflow>=1.14,<1.15") as a dependency in setup.py. If a user has tensorflow-gpu installed, then pip3 install stellargraph installs tensorflow, which overwrites things and causes all models to be trained on CPU instead of GPU. To fix, users must remove the tensorflow* installations and reinstall tensorflow-gpu. This was true for TF 1.14 at least, and I think may hold true with TF 2.0.

To Reproduce Steps to reproduce the behavior: On a system where tensorflow-gpu is installed, install stellargraph with: pip3 install stellargraph

Expected behavior Installing stellargraph shouldn’t corrupt existing tensorflow-gpu installations.

Solution The tensorflow entry should be removed as a dependency in setup.py and requirements. Instead, the Installation section in the stellargraph README should include a note about installing tensorflow (or tensorflow-gpu) separately when installing stellargraph. This is how other libraries typically handle it. For instance, see the installation instructions for graph_nets:

To install the Graph Nets library for CPU, run:

$ pip install graph_nets “tensorflow>=1.15,<2” tensorflow_probability

To install the Graph Nets library for GPU, run:

$ pip install graph_nets “tensorflow_gpu>=1.15,<2” tensorflow_probability

In setup.py of graph_nets:

    # Additional "tensorflow" and "tensorflow_probability" requirements should
    # be installed separately (See README).
    install_requires=[
        "absl-py",
        "dm-sonnet<2",
        "future",
        "networkx",
        "numpy",
        "setuptools",
        "six",
    ],

[adocherty]

Hi @amaiya,

Thanks for trying the library! We understand the issue and will look at updating the setup.py file to remove a hard dependency on tensorflow. I am thinking instead of removing tensorflow as a requirement we can add it as a ‘extra’ requirement, so that you can specify stellargraph either with gpu or cpu support, for example:

To install stellargraph + tensorflow-gpu you can use the following:

pip install stellargraph[gpu]

To install stellargraph + tensorflow you can use the following:

pip install stellargraph[cpu]

Finally, to install stellargraph without change to your existing tensorflow libraries:

pip install stellargraph

However, there should be a warning in the latter case if tensorflow is not installed, or an incompatible version of tensorflow is installed. This will help users who install StellarGraph without reading the fine print so they do not face unexplained errors.

[shauryauppal]

I am still facing this issue stellar graph is not using GPU, I am working with Watch Your Step Embedding Method.