Hi all,

I've encountered a compatibility issue when upgrading TensorFlow from version 2.x to 2.15.0. The upgrade process fails due to dependency conflicts, specifically with protobuf and numpy versions. Attempting to downgrade TensorFlow to an earlier 2.x release also results in similar errors.

Steps to reproduce:

1. Install TensorFlow 2.x via pip.
2. Attempt to upgrade to 2.15.0 (pip install --upgrade tensorflow==2.15.0).
3. Observe dependency resolution errors related to protobuf and numpy.
4. Attempt downgrade with pip install tensorflow==2.13.0 and encounter the same issue.

Error message:

ERROR: Cannot install tensorflow==2.15.0 because these package versions have conflicting dependencies:
tensorflow 2.15.0 requires protobuf>=3.20.3, but you have protobuf 3.19.0 which is incompatible.

Has anyone successfully resolved this upgrade/downgrade compatibility problem? Are there recommended dependency pinning strategies or workarounds for this TensorFlow version conflict scenario?

Any guidance would be appreciated!

Related topics: version conflict, upgrade error, dependency mismatch, compatibility downgrade, pip install
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