ValueError: The shape of the target variable and the shape of the target value in `variable.assign(value)` must match in layers/factorized_top_k.py

Getting below error when trying Quickstart example.

File "/Users/terry/Documents/project/recommender/recommenders/collab_filtering_movie.py", line 245, in
index.index_from_dataset(
File "/Users/terry/Documents/project/recommender/recommenders/tensorflow_recommenders/layers/factorized_top_k.py", line 215, in index_from_dataset
return self.index(candidates, identifiers)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/terry/Documents/project/recommender/recommenders/tensorflow_recommenders/layers/factorized_top_k.py", line 564, in index
self._identifiers.assign(identifiers)
File "/Users/terry/Documents/project/recommender/recommenders/.venv/lib/python3.12/site-packages/keras/src/backend/common/variables.py", line 226, in assign
raise ValueError(
ValueError: The shape of the target variable and the shape of the target value in variable.assign(value) must match. variable.shape=(), Received: value.shape=(1682,). Target variable:

OSX 14.2.1
python 3.12
tensorflow 2.16.2
tensorflow-recommenders 0.7.3
tensorflow-datasets 4.9.6
keras 3.4.1

Reproduce the Quickstart example with the listed Python, TensorFlow, TensorFlow Recommenders, TensorFlow Datasets, and Keras versions. Start in layers/factorized_top_k.py at index_from_dataset around line 215 and index around line 564, then trace how identifiers are initialized before assign is called. Done means the example no longer raises the reported shape error, with the behavior verified against the affected versions.