Compiling Fails due to sklearn/metrics/pairwise.py

### Describe the bug

_This may be a duplicate of [29754](https://github.com/scikit-learn/scikit-learn/issues/29754)._ 

Having merged from upstream, the imports in `sklearn/metrics/pairwise.py` do not compile. 

I am getting error:
"sklearn/metrics/_dist_metrics.pyx", line 1, in init sklearn.metrics._dist_metrics"

I have tried rebuilding my conda environment and sklearn.


### Steps/Code to Reproduce

$ python -m sklearn.kernel_approximation

### Expected Results

not an error

### Actual Results

```python
Traceback (most recent call last):
  File "<frozen runpy>", line 198, in _run_module_as_main
  File "<frozen runpy>", line 88, in _run_code
  File "/Users/conradstevens/scikit-learn/sklearn/kernel_approximation.py", line 20, in <module>
    from .metrics.pairwise import KERNEL_PARAMS, PAIRWISE_KERNEL_FUNCTIONS, pairwise_kernels
  File "/Users/conradstevens/scikit-learn/sklearn/metrics/__init__.py", line 6, in <module>
    from . import cluster
  File "/Users/conradstevens/scikit-learn/sklearn/metrics/cluster/__init__.py", line 28, in <module>
    from ._unsupervised import (
  File "/Users/conradstevens/scikit-learn/sklearn/metrics/cluster/_unsupervised.py", line 21, in <module>
    from ..pairwise import _VALID_METRICS, pairwise_distances, pairwise_distances_chunked
  File "/Users/conradstevens/scikit-learn/sklearn/metrics/pairwise.py", line 46, in <module>
    from ._pairwise_distances_reduction import ArgKmin
  File "/Users/conradstevens/scikit-learn/sklearn/metrics/_pairwise_distances_reduction/__init__.py", line 97, in <module>
    from ._dispatcher import (
  File "/Users/conradstevens/scikit-learn/sklearn/metrics/_pairwise_distances_reduction/_dispatcher.py", line 11, in <module>
    from .._dist_metrics import (
  File "sklearn/metrics/_dist_metrics.pyx", line 1, in init sklearn.metrics._dist_metrics
ValueError: numpy.dtype size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject
```

### Versions

```shell
$ python -c "import sklearn; sklearn.show_versions()"

System:
    python: 3.12.5 | packaged by conda-forge | (main, Aug  8 2024, 18:31:54) [Clang 16.0.6 ]
executable: /opt/homebrew/Caskroom/miniconda/base/envs/sklearn-dev-3/bin/python
   machine: macOS-14.4.1-x86_64-i386-64bit

Python dependencies:
      sklearn: 1.6.dev0
          pip: 24.2
   setuptools: 72.2.0
        numpy: 2.1.0
        scipy: 1.14.1
       Cython: 3.0.11
       pandas: None
   matplotlib: None
       joblib: 1.4.2
threadpoolctl: 3.5.0

Built with OpenMP: True

threadpoolctl info:
       user_api: blas
   internal_api: openblas
    num_threads: 10
         prefix: libopenblas
       filepath: /opt/homebrew/Caskroom/miniconda/base/envs/sklearn-dev-3/lib/libopenblasp-r0.3.27.dylib
        version: 0.3.27
threading_layer: openmp
   architecture: Nehalem

       user_api: openmp
   internal_api: openmp
    num_threads: 10
         prefix: libomp
       filepath: /opt/homebrew/Caskroom/miniconda/base/envs/sklearn-dev-3/lib/libomp.dylib
        version: None
```

COMMENT:
Hey!
Here’s what I found and some steps you might try:

## Ensure Consistency Between NumPy and Scikit-learn Build: ##
 It looks like the problem might be due to a mismatch between the version of NumPy used when scikit-learn was built and the version that's currently installed. Reinstalling scikit-learn could help, ensuring it's built against the current version of NumPy in your environment.

## Rebuild Cython Extensions: ## 
Since the issue is tied to a Cython-compiled file `(_dist_metrics.pyx)`,  rebuilding the Cython extensions manually can usually fix this issue. 

## Check Version Compatibility: ## 
If rebuilding doesn’t help, you might want to try using an older version of NumPy to see if that resolves the issue. Sometimes the latest versions can introduce incompatibilities that haven’t been fully ironed out yet.

## Consider a Different Python Version: ##
 If all else fails, it might be worth trying Python 3.11 instead of 3.12, as newer Python versions can sometimes cause subtle issues with packages that haven’t been fully updated yet.

Hopefully this helps

Labels: Question