Open bjfar opened 6 years ago
Looks like the function no longer exists in TF 1.7.0. Following the commit, we may be able to just remove it in the ed.copy
implementation (https://github.com/tensorflow/tensorflow/commit/9fc9f19428e497f3a297538059804f69996a612e#diff-66fbf57743aed7c8407bcb218db3c491L2477).
I'm having the same issue, any updates on this?
TF 1.8.0 has been released, I wonder how much other changes have been in TF that Edward would need.. :/
I tried to use the lower versions of TF and edward, then I can import both TF and edward successfully now. But for TF1.7.0 and 1.8.0, the same problem with you.
Any fix yet?
Having the same problem with tensorflow 1.8.0 built from source
If you follow this PR you'll see followups. I'm not sure if there's a discussion on another platform (if there is please let me know I'd love to see and contribute to solving this issue)
I noticed that set_shapes_for_outputs
now (since 9fc9f19428e497f3a) seems to be called set_shape_and_handle_data_for_outputs
See a kludge solution here
@larsr Can you try running the tests? Because I'm pretty sure I tried that and it failed the copy tests
@IanQS yeah, I did cd edward/tests; pytest .
and got "86 failed, 240 passed, 44 warnings". In particular pytest util/copy_test.py
got 20 failed and 3 passed. Alas, there are more things to take care of.
I installed TensorFlow via pip and still got this problem.
I created a pull request here: https://github.com/blei-lab/edward/pull/894
@devinbostIL Because it still fails the tests
yeah I don't think Master still has it pulled in eh
Having the same issue. Is there a work around for now?
Having the same issue. Is there a work around for now?
workaround is to use an older version of Tensorflow (Edward should work with it up to tf 1.6)
Any estimated time to get this fixed? More importantly when the fix will be released to the pip channel? I know google is releasing TF at a rapid pace. Unfortunately I can't revert back to an older version of TF simply because of Edward.
I'm having the same issue, any fix?
Same issue here, any possible alternative?
having the same issue.Is there any solution?
Same issue :) The only thing that works is reverting to the tensorflow==1.5.0, which is not a solution at all since I need tensorflow 1.7.0
same issue. confirm it works fine with tensorflow==1.5.0.
unfortunately unusable atm if you need tf 1.7
Hi, any idea when the compatibility issue with version TF>=1.7 is going to be resolved?
Many thanks
Almost certain that development on upgrading to new TF is not gonna happen any longer since Edward is now a part of TFP
Indeed, most of the functionality has been ported to https://www.tensorflow.org/probability/. See https://github.com/tensorflow/probability/blob/master/tensorflow_probability/python/edward2/Upgrading_From_Edward_To_Edward2.md
Having the same issue with TensorFlow 1.9.0
same issue with tf 1.11.0
And 1.12.0 today.
It seems like newcomers should learn TensorFlow Probability/Edward2 rather than Edward 1, even though there's no mention of it on the Edward website.
It seems like newcomers should learn TensorFlow Probability/Edward2 rather than Edward 1, even though there's no mention of it on the Edward website.
This should definitely be advised on the Edward website.
My solution is : 1)find file: edward/util/random_variables.py 2)replace the import line: from tensorflow.python.framework.ops import set_shape_and_handle_data_for_outputs as set_shapes_for_outputs It works.
@fjssharpsword indeed, it worked.
@fjssharpsword Thanks! It worked :D
I have tensorflow 1.7.0 built from source and installed, and it seems to work ok by itself, but I cannot import edward:
I am on Ubuntu 16.04 LTS and using the edward version installed via pip, which appears to be 1.3.5:
I was going to try building edward from source, but the latest tagged version seems to be 1.3.5 anyway so I guess this will not help. My Python version is 3.6.4.
edit: Ah, although if I install tensorflow via pip (which also seems to be version 1.7.0) then edward does work. This seems odd to me... I guess something could be wrong with my tensorflow build, but it seems to work. I wanted to build it from source since the pip version doesn't use various vectorisation options that my CPU can do.