text: Title: [BUG] sar_movielens.ipynb - top_k = model.recommend_k_items(test, top_k=TOP_K, remove_seen=True) error
  Body: ### Description
  <!--- Describe your issue/bug/request in detail -->
  I got error when running sar_movielens.ipynb notebooks from azure machine learning compute instance
  <img width="727" alt="image" src="https://github.com/recommenders-team/recommenders/assets/110788250/4a967e56-d122-4166-b493-a608670a7e9d">
  ```code
  2023-10-09 20:08:29,498 INFO     Calculating recommendation scores
  ---------------------------------------------------------------------------
  ValueError                                Traceback (most recent call last)
  Cell In[8], line 2
        1 with Timer() as test_time:
  ----> 2     top_k = model.recommend_k_items(test, top_k=TOP_K, remove_seen=True)
        4 print("Took {} seconds for prediction.".format(test_time.interval))
  
  File /anaconda/envs/msftrecsys2/lib/python3.9/site-packages/recommenders/models/sar/sar_singlenode.py:533, in SARSingleNode.recommend_k_items(self, test, top_k, sort_top_k, remove_seen)
      520 def recommend_k_items(self, test, top_k=10, sort_top_k=True, remove_seen=False):
      521     """Recommend top K items for all users which are in the test set
      522 
      523     Args:
     (...)
      530         pandas.DataFrame: top k recommendation items for each user
      531     """
  --> 533     test_scores = self.score(test, remove_seen=remove_seen)
      535     top_items, top_scores = get_top_k_scored_items(
      536         scores=test_scores, top_k=top_k, sort_top_k=sort_top_k
      537     )
      539     df = pd.DataFrame(
      540         {
      541             self.col_user: np.repeat(
     (...)
      546         }
      547     )
  
  File /anaconda/envs/msftrecsys2/lib/python3.9/site-packages/recommenders/models/sar/sar_singlenode.py:346, in SARSingleNode.score(self, test, remove_seen)
      344 # calculate raw scores with a matrix multiplication
      345 logger.info("Calculating recommendation scores")
  --> 346 test_scores = self.user_affinity[user_ids, :].dot(self.item_similarity)
      348 # ensure we're working with a dense ndarray
      349 if isinstance(test_scores, sparse.spmatrix):
  
  File /anaconda/envs/msftrecsys2/lib/python3.9/site-packages/scipy/sparse/_base.py:411, in _spbase.dot(self, other)
      409     return self * other
      410 else:
  --> 411     return self @ other
  
  File /anaconda/envs/msftrecsys2/lib/python3.9/site-packages/scipy/sparse/_base.py:622, in _spbase.__matmul__(self, other)
      620 def __matmul__(self, other):
      621     if isscalarlike(other):
  --> 622         raise ValueError("Scalar operands are not allowed, "
      623                          "use '*' instead")
      624     return self._mul_dispatch(other)
  
  ValueError: Scalar operands are not allowed, use '*' instead
  ```
  
  ### In which platform does it happen?
  <!--- Describe the platform where the issue is happening (use a list if needed) -->
  <!--- For example: -->
  <!--- * Azure Data Science Virtual Machine. -->
  <!--- * Azure Databricks.  -->
  <!--- * Other platforms.  -->
  It happen on Azure ML compute instance
  
  ### How do we replicate the issue?
  <!--- Please be specific as possible (use a list if needed). -->
  <!--- For example: -->
  <!--- * Create a conda environment for pyspark -->
  <!--- * Run unit test `test_sar_pyspark.py` with `pytest -m 'spark'` -->
  <!--- * ... -->
  This is setup script I use in AzureML :
  ```code
  # 1. Install gcc if it is not installed already. On Ubuntu, this could done by using the command
  # sudo apt install gcc
  
  # 2. Create and activate a new conda environment
  conda create -n msftrecsys2 python=3.9.16
  conda activate msftrecsys2
  
  # 3. Install the core recommenders package. It can run all the CPU notebooks.
  pip install recommenders
  pip install recommenders[gpu]
  # 4. create a Jupyter kernel
  python -m ipykernel install --user --name msftrecsys2 --display-name msftrecsys2
  
  # 5. Clone this repo within VSCode or using command line:
  git clone https://github.com/recommenders-team/recommenders.git
  ```
  this is my compute instance setting:
  <img width="1108" alt="image" src="https://github.com/recommenders-team/recommenders/assets/110788250/2c43df07-eb72-4f3a-82e2-56e48f4f594a">
  
  
  ### Expected behavior (i.e. solution)
  <!--- For example:  -->
  <!--- * The tests for SAR PySpark should pass successfully. -->
  Cell below should run without throwing error
  ```code
  with Timer() as test_time:
      top_k = model.recommend_k_items(test, top_k=TOP_K, remove_seen=True)
  
  print("Took {} seconds for prediction.".format(test_time.interval))
  ```
  
  ### Other Comments
  