Would it be possible to relax the requirements?

Hi,

this issue is primarily along the lines of https://github.com/tensorflow/tensorflow/commit/a90383a867a2337600c775d67842f308da9d118b. I was wondering if the tight pins in requirements.txt are primarily due to functionality or solvability? Reason is, that I’m thinking about adding this package to conda-forge but the restrictions currently make this difficult. It seems like things like the numpy pin are primarily to make solving easier but I just wanted to double check if this is correct? Thanks!

[MichaelBroughton]

We use the version of protoc provided by TensorFlow in our project (via bazel dependencies) when developing code:

1. We use this protobuf for Codegen + Compilation in C++
2. We also use it for Codegen in python When actually running code all we require is that you use a version of this that happens to also work with the current version of protoc used in TensorFlow. Right now protoc 3.9.2 is used, but for the ease of our users we can allow the pip install to slide all the way up to 3.17.3

This is a problem TensorFlow also has and is working on fixing here

[lockwo]

Any updates on this issue or can it be closed?