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Running the pip installs in the notebook (as well as in offline environments) yields the following error:
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. tensorflow-datasets 4.9.2 requires protobuf>=3.20, but you have protobuf 3.19.6 which is incompatible. tensorflow-metadata 1.13.1 requires protobuf<5,>=3.20.3, but you have protobuf 3.19.6 which is incompatible.
And subsequently:
ImportError: cannot import name 'builder' from 'google.protobuf.internal' (/usr/local/lib/python3.10/dist-packages/google/protobuf/internal/__init__.py)
Side note: installing scann in an offline environment will currently force tensorflow 2.11, which will conflicht with modules like tensorflow_datasets and tensorflow_recommenders.
The text was updated successfully, but these errors were encountered:
The movie retrieval tutorial/notebook is broken due to a version conflict of the protobuf dependencies.
https://github.com/tensorflow/recommenders/blob/main/docs/examples/basic_retrieval.ipynb
Running the pip installs in the notebook (as well as in offline environments) yields the following error:
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. tensorflow-datasets 4.9.2 requires protobuf>=3.20, but you have protobuf 3.19.6 which is incompatible. tensorflow-metadata 1.13.1 requires protobuf<5,>=3.20.3, but you have protobuf 3.19.6 which is incompatible.
And subsequently:
ImportError: cannot import name 'builder' from 'google.protobuf.internal' (/usr/local/lib/python3.10/dist-packages/google/protobuf/internal/__init__.py)
Side note: installing scann in an offline environment will currently force tensorflow 2.11, which will conflicht with modules like tensorflow_datasets and tensorflow_recommenders.
The text was updated successfully, but these errors were encountered: