Closed andrew-zzz closed 10 months ago
@Lifann @sunshinenum @rhdong please help
Hi @andrew-zzz, I just checked the Keras demo and tutorial of dynamic embedding and I confirmed they work well, Here is the demo's log: tfra0.6.0_amazon-video-games-keras-eager-6_17_2023.log
As we mentioned in README: the conda is not recommended: https://github.com/tensorflow/recommenders-addons#compatibility-with-tensorflow
BTW, you shouldn't say that to anyone in Github. You're not welcome to us.
Hi @andrew-zzz, I just checked the Keras demo and tutorial of dynamic embedding and I confirmed they work well, Here is the demo's log: tfra0.6.0_amazon-video-games-keras-eager-6_17_2023.log
As we mentioned in README: the conda is not recommended: https://github.com/tensorflow/recommenders-addons#compatibility-with-tensorflow
BTW, you shouldn't say that to anyone in Github. You're not welcome to us.
I am sorry for that I am broken down that time, thank you for your reply that's a good project and I will still use it
Has the bug been fixed? May I close this issue? @andrew-zzz
This issue has been solved by following the demo instructions.
I am running into this issue and I'm not sure what the resolution was from this issue?
Hi @andrew-zzz, I just checked the Keras demo and tutorial of dynamic embedding and I confirmed they work well, Here is the demo's log: tfra0.6.0_amazon-video-games-keras-eager-6_17_2023.log
As we mentioned in README: the conda is not recommended: https://github.com/tensorflow/recommenders-addons#compatibility-with-tensorflow
BTW, you shouldn't say that to anyone in Github. You're not welcome to us.
@alykhantejani This issue could be caused by the wrong way of use
ok let me open a new issue as Im running into this.
@alykhantejani It is better to provide a minimum reproducible code.
System information Linux version 3.10.0 TensorFlow version 2.8.3,binary TensorFlow-Recommenders-Addons version 0.6 binary Python version:3.8 *Is GPU used? (yes/no):no
Describe the bug model.save() error that NotImplementedError: return_trainable currently is not implemented when using tf.function, i have set return_trainable=False both in de.embedding_lookup and de.embedding_lookup_sparse
Code to reproduce the issue
Provide a reproducible test case that is the bare minimum necessary to generate the problem.
Other info / logs