ColumnTransformers don't honor set_config(transform_output="pandas") when multiprocessing with n_jobs>1

### Describe the bug

I'm trying to do a grid search with `n_jobs=-1`, working with pandas output, and it fails despite `set_config(transform_output = "pandas")`

I have to manually `.set_output(transform='pandas')` in the ColumnTransformer for it to work.

### Steps/Code to Reproduce

#### Preparation
```python
import pandas as pd
import numpy as np
from sklearn.model_selection import GridSearchCV
from sklearn.base import TransformerMixin, BaseEstimator
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import make_pipeline
from sklearn.compose import make_column_transformer, make_column_selector

from sklearn import set_config
set_config(transform_output = "pandas")

# Toy dataframe
df = pd.DataFrame(np.random.randn(100, 4), columns=list('ABCD'))
X, y = df.drop(columns='D'), df['D']>0

# Custom transformer that needs dataframe
class CustomTransformer(BaseEstimator, TransformerMixin):
    def fit(self, X, y=None):
        assert isinstance(X, pd.DataFrame), "Fit failed"
        self.cols = X.columns
        return self
    
    def transform(self, X, y=None):
        assert isinstance(X, pd.DataFrame), "Transform failed"
        return X.copy()
    
    def get_feature_names_out(self):
        return self.cols


prepro = CustomTransformer()
model = LogisticRegression()

param_grid = {'logisticregression__C': np.logspace(3,-3, num=50)}
```

This WORKS (`n_jobs=1`):
```python
drop = make_column_transformer(('drop', [0]), remainder='passthrough')
pipe = make_pipeline(drop, prepro,  model)

gs = GridSearchCV(pipe, param_grid, cv=10, n_jobs=1)
gs.fit(X,y)
```

This FAILS (`n_jobs=-1`):
```python
drop = make_column_transformer(('drop', [0]), remainder='passthrough')
pipe = make_pipeline(drop, prepro,  model)

gs = GridSearchCV(pipe, param_grid, cv=10, n_jobs=-1)
gs.fit(X,y)
```


This WORKS again (`n_jobs=-1` and force output):
```python
drop = make_column_transformer(('drop', [0]), remainder='passthrough').set_output(transform='pandas')
pipe = make_pipeline(drop, prepro,  model)

gs = GridSearchCV(pipe, param_grid, cv=10, n_jobs=-1)
gs.fit(X,y)
```



### Actual Results

AssertionError: Fit failed

### Versions

```shell
System:
    python: 3.11.1 (main, Dec  7 2022, 08:49:13) [GCC 12.2.0]
executable: /home/susensio/.local/share/venv/bin/python3
   machine: Linux-6.0.0-6-amd64-x86_64-with-glibc2.36

Python dependencies:
      sklearn: 1.2.0
          pip: 22.3.1
   setuptools: 65.6.3
        numpy: 1.24.1
        scipy: 1.9.3
       Cython: None
       pandas: 1.5.2
   matplotlib: 3.6.2
       joblib: 1.2.0
threadpoolctl: 3.1.0

Built with OpenMP: True

threadpoolctl info:
       user_api: openmp
   internal_api: openmp
         prefix: libgomp
       filepath: /home/susensio/.local/share/venv/lib/python3.11/site-packages/scikit_learn.libs/libgomp-a34b3233.so.1.0.0
        version: None
    num_threads: 8

       user_api: blas
   internal_api: openblas
         prefix: libopenblas
       filepath: /home/susensio/.local/share/venv/lib/python3.11/site-packages/numpy.libs/libopenblas64_p-r0-15028c96.3.21.so
        version: 0.3.21
threading_layer: pthreads
   architecture: Haswell
    num_threads: 8

       user_api: blas
   internal_api: openblas
         prefix: libopenblas
       filepath: /home/susensio/.local/share/venv/lib/python3.11/site-packages/scipy.libs/libopenblasp-r0-41284840.3.18.so
        version: 0.3.18
threading_layer: pthreads
   architecture: Haswell
    num_threads: 8
```

COMMENT:
Taking the minimal example in #17634, we can reproduce the issue, so we need to have more tasks than `n_jobs` to trigger the issue which was not the case probably in the non-regression test.

```python
In [1]: from joblib import Parallel
   ...: from sklearn.utils.fixes import delayed
   ...: from sklearn import get_config, config_context
   ...: 
   ...: def get_working_memory():
   ...:     return get_config()['working_memory']
   ...: 
   ...: with config_context(working_memory=123):
   ...:     results = Parallel(n_jobs=2)(
   ...:         delayed(get_working_memory)() for _ in range(10)
   ...:     )
   ...: 
   ...: results
Out[1]: [123, 123, 123, 123, 1024, 1024, 1024, 1024, 1024, 1024]
```

Labels: Bug, module:compose