Errors with TF 2.0

[gndowns]

This issue is meant to be a place to discuss all issues related to usage with Tensorflow 2.0, and potential robust solutions

Issues

1. tensorflow has no attribute reset_default_graph

command:

>>> import mltest
>>> mltest.setup()

output:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/gdowns/venv_mltest/lib/python3.7/site-packages/mltest/mltest.py", line 39, in setup
    tf.reset_default_graph()
AttributeError: module 'tensorflow' has no attribute 'reset_default_graph'

Potential Long-Term Solutions

• Modifying mltest to fit TF2.0 API
• Creating a fork mltest2.0

[ucalyptus]

for my machine with Python 3.6.8 and now TF 1.14.0

import mltest mltest.setup() gives the warning of deprecation for reset_default_graph()

and suggests to use tf.compat.v1.reset_default_graph() Guess I'll add that

[ucalyptus]

@gndowns any updates?

[gndowns]

@ucalyptus Sorry but I am no longer working on this.

[chaserileyroberts]

I think it sadly has come time to deprecate this library...

[bmiselis]

Are you planning to create a new version of it or know any alternatives?

[chaserileyroberts]

At this time no.

Many of the things we were testing against are ready features of Keras, mainly the "make sure all variables get trained" has been in keras even before this library existed.

However, if someone wishes to port this to TF2, I'd gladly link it here like I did with the Pytorch version.

[zaccharieramzi]

@Thenerdstation do you know if those ready features of Keras were ported to tf.keras in Tf 2.x?

I have been looking around a bit in here but didn't find anything satisfactory.