Closed tanujjain closed 2 years ago
Hey looking good. Overall I believe that setting tf>1.0 is not the right approach. TensorFlow has many upward/downward compatibility problems. Could imagine that tf >= 3.0 will break everything but then we can change it accordingly to 1.0 < tf =<2.0.
@datitran We would no longer be able to support py3.6 after this fix is shipped. Just want to confirm if you're onboard with that?
I think that should be okay until we find a long-term fix. We should find a better solution on this.
@tanujjain Is this going to be merged with main any time soon?
Running python setup.py install on the dev branch fails.
Tensorflow and numpy aren't playing well with each other. Leave tf>1.0 in setup.py with no mention of numpy (i.e., relying on tf to get numpy) leads to an error since tf 2.4.1 gets installed along with numpy 1.20.1 (due to pip resolver algo), but tf 2.4.1 needs numpy=~1.9.2. Explicitly mentioning numpy <1.20.0, makes the installation work. Additionally, newer versions of numpy (1.20.1), scipy (1.6 onwards) and matplotlib do not support python 3.6 anymore. The changes proposed in this PR will also work from Python 3.7 onwards.