Many packages build on TensorFlow. For example, our work in Edward uses tensorflow>=1.0.0a0 as an install requirement.
However, this conflicts with tensorflow-gpu, which can no longer be installed because of the requirement specifically on tensorflow. What do you suggest is the best way to handle this?
One option suggested by @gokceneraslan (blei-lab/edward#428 (comment)) is to hack in the dependency according to whether the user has a GPU. Another option, which PrettyTensor and Keras employ, is to not even require TensorFlow. (Both options sound not good.)
Also see blei-lab/edward#428. also looping in GPflow devs (@jameshensman, @alexggmatthews) in case they have the same problem. (Note I'm raising this as an issue instead of asking on a mailing list, in case this is something that should be changed on TensorFlow's end and not our end.)
Many packages build on TensorFlow. For example, our work in Edward uses
tensorflow>=1.0.0a0as an install requirement.However, this conflicts with
tensorflow-gpu, which can no longer be installed because of the requirement specifically ontensorflow. What do you suggest is the best way to handle this?One option suggested by @gokceneraslan (blei-lab/edward#428 (comment)) is to hack in the dependency according to whether the user has a GPU. Another option, which PrettyTensor and Keras employ, is to not even require TensorFlow. (Both options sound not good.)
Also see blei-lab/edward#428. also looping in GPflow devs (@jameshensman, @alexggmatthews) in case they have the same problem. (Note I'm raising this as an issue instead of asking on a mailing list, in case this is something that should be changed on TensorFlow's end and not our end.)