ElasticNetCV does not handle sample weights as expected

### Describe the bug

It seems that the _alpha_grid computations ignore sample weights and as a result the model coefficients do not match after fitting on two versions of the same data, one with weighted samples and the other with repeated samples.

### Steps/Code to Reproduce

```python
import numpy as np
from sklearn.datasets import make_regression
from sklearn.linear_model import ElasticNet, ElasticNetCV

rng = np.random.RandomState(0)

X, y = make_regression(
        n_samples=100, n_features=5, random_state=10
    )

sample_weight = rng.randint(0, 5, size=X.shape[0])
X_resampled_by_weights = np.repeat(X, sample_weight, axis=0)
y_resampled_by_weights = np.repeat(y, sample_weight, axis=0)

est_weighted = ElasticNet(selection='cyclic').fit(X,y,sample_weight=sample_weight)
est_repeated = ElasticNet(selection='cyclic').fit(X_resampled_by_weights,y_resampled_by_weights)

np.testing.assert_allclose(est_weighted.coef_, est_repeated.coef_)

est_weighted = ElasticNetCV(selection='cyclic').fit(X,y,sample_weight=sample_weight)
est_repeated = ElasticNetCV(selection='cyclic').fit(X_resampled_by_weights,y_resampled_by_weights)

np.testing.assert_allclose(est_weighted.alphas_, est_repeated.alphas_)
```

### Expected Results

No error is thrown

### Actual Results

Assertion on the coef_ for ElasticNet (without CV) is fine
Assertion on the ElasticNetCV alphas_ fails with the following error message

```
AssertionError: 
Not equal to tolerance rtol=1e-07, atol=0

Mismatched elements: 100 / 100 (100%)
Max absolute difference: 28.39466113
Max relative difference: 0.20225973
 x: array([111.992461, 104.444544,  97.405331,  90.840538,  84.71819 ,
        79.008467,  73.683561,  68.717536,  64.086204,  59.767008,
        55.738912,  51.982296,  48.478863,  45.21155 ,  42.164443,...
 y: array([140.387122, 130.9255  , 122.10156 , 113.872323, 106.19771 ,
        99.04034 ,  92.365352,  86.140237,  80.334673,  74.920385,
        69.871002,  65.16193 ,  60.770234,  56.674524,  52.85485 ,...
```

### Versions

```shell
System:
    python: 3.12.0 (main, Nov 17 2023, 17:04:21) [Clang 15.0.0 (clang-1500.0.40.1)]
executable: /Users/shrutinath/.pyenv/versions/3.12.0/envs/tf_2023/bin/python
   machine: macOS-14.1.1-arm64-arm-64bit

Python dependencies:
      sklearn: 1.5.dev0
          pip: 23.3.1
   setuptools: 68.2.2
        numpy: 1.26.2
        scipy: 1.11.3
       Cython: 3.0.9
       pandas: 2.1.3
   matplotlib: 3.8.1
       joblib: 1.3.2
threadpoolctl: 3.2.0

Built with OpenMP: True

threadpoolctl info:
       user_api: blas
   internal_api: openblas
    num_threads: 8
         prefix: libopenblas
       filepath: /Users/shrutinath/.pyenv/versions/3.12.0/envs/tf_2023/lib/python3.12/site-packages/numpy/.dylibs/libopenblas64_.0.dylib
        version: 0.3.23.dev
threading_layer: pthreads
   architecture: armv8

       user_api: openmp
   internal_api: openmp
    num_threads: 8
         prefix: libomp
       filepath: /opt/homebrew/Cellar/libomp/18.1.2/lib/libomp.dylib
        version: None

       user_api: blas
   internal_api: openblas
    num_threads: 8
         prefix: libopenblas
       filepath: /Users/shrutinath/.pyenv/versions/3.12.0/envs/tf_2023/lib/python3.12/site-packages/scipy/.dylibs/libopenblas.0.dylib
        version: 0.3.21.dev
threading_layer: pthreads
   architecture: armv8
```

COMMENT:
It probably was resolved by https://github.com/scikit-learn/scikit-learn/pull/29442

Labels: Bug