TypeError: cpu_count() got an unexpected keyword argument 'only_physical_cores'

### Describe the bug

I am running the KNeighbordsClassifier inside a framework of pytorch_lightning. I am fitting the model correctly, but when I try to predict new results I have an error.

### Steps/Code to Reproduce

```python
estimators = dict(svm=SVC(kernel='rbf', C=1e5, gamma=1.),
                  knn=KNeighborsClassifier(n_neighbors=3))

for key, estimator in estimators.items():
    estimator.fit(x_train, c_train)
    c_hat_test = np.concatenate([estimator.predict(x_te) for x_te in x_test_split], axis=0)
```

### Expected Results

No error is thrown

### Actual Results

```python
File "sklearn/metrics/_pairwise_distances_reduction/_argkmin.pyx", line 556, in sklearn.metrics._pairwise_distances_reduction._argkmin.ArgKmin32.compute
  File "sklearn/metrics/_pairwise_distances_reduction/_argkmin.pyx", line 820, in sklearn.metrics._pairwise_distances_reduction._argkmin.EuclideanArgKmin32.__init__
  File "sklearn/metrics/_pairwise_distances_reduction/_argkmin.pyx", line 590, in sklearn.metrics._pairwise_distances_reduction._argkmin.ArgKmin32.__init__
  File "sklearn/metrics/_pairwise_distances_reduction/_base.pyx", line 547, in sklearn.metrics._pairwise_distances_reduction._base.BaseDistancesReduction32.__init__
  File "sklearn/utils/_openmp_helpers.pyx", line 21, in sklearn.utils._openmp_helpers._openmp_effective_n_threads
  File "sklearn/utils/_openmp_helpers.pyx", line 68, in sklearn.utils._openmp_helpers._openmp_effective_n_threads
TypeError: cpu_count() got an unexpected keyword argument 'only_physical_cores'
```

### Versions

```shell
System:
    python: 3.10.13 (main, Sep 11 2023, 13:44:35) [GCC 11.2.0]
executable: /home/myuser/anaconda3/envs/pt12/bin/python
   machine: Linux-6.5.0-21-generic-x86_64-with-glibc2.35
Python dependencies:
      sklearn: 1.4.1.post1
          pip: 23.3.1
   setuptools: 68.2.2
        numpy: 1.26.4
        scipy: 1.12.0
       Cython: 3.0.8
       pandas: 2.2.1
   matplotlib: 3.8.3
       joblib: 1.3.2
threadpoolctl: 3.3.0
Built with OpenMP: True
threadpoolctl info:
       user_api: openmp
   internal_api: openmp
    num_threads: 12
         prefix: libgomp
       filepath: /home/myuser/anaconda3/envs/pt12/lib/python3.10/site-packages/scikit_learn.libs/libgomp-a34b3233.so.1.0.0
        version: None
       user_api: blas
   internal_api: openblas
    num_threads: 12
         prefix: libopenblas
       filepath: /home/myuser/anaconda3/envs/pt12/lib/python3.10/site-packages/numpy.libs/libopenblas64_p-r0-0cf96a72.3.23.dev.so
        version: 0.3.23.dev
threading_layer: pthreads
   architecture: Zen
       user_api: blas
   internal_api: openblas
    num_threads: 12
         prefix: libopenblas
       filepath: /home/myuser/anaconda3/envs/pt12/lib/python3.10/site-packages/scipy.libs/libopenblasp-r0-23e5df77.3.21.dev.so
        version: 0.3.21.dev
threading_layer: pthreads
   architecture: Zen
```

COMMENT:
> I see that we load 2 libopenblas here. Do you have an idea how can get to this stage?

when numpy and scipy are installed using wheels, from pypi for instance, they both come with an openblas. But this issue is not related to openblas.

Labels: Bug