Unclear message regarding param validation #26897
Description
In the context of #26896 I wrote a test and got a message which I'm really puzzled about. The error message says: ValueError: No valid specification of the columns. Only a scalar, list or slice of all integers or all strings, or boolean mask is allowed
This is the code, and the error message:
import numpy as np
from sklearn import set_config
from sklearn.model_selection import cross_validate
from sklearn.tests.test_metaestimators_metadata_routing import (
ConsumingClassifier,
ConsumingScorer,
ConsumingSplitter,
)
set_config(enable_metadata_routing=True)
X = np.ones((10, 2))
y = np.array([0, 0, 1, 1, 2, 2, 3, 3, 4, 4])
scorer = ConsumingScorer().set_score_request(
sample_weight="score_weights", metadata="score_metadata"
)
splitter = ConsumingSplitter().set_split_request(
groups="split_groups", metadata="split_metadata"
)
estimator = ConsumingClassifier().set_fit_request(
sample_weight="fit_sample_weight", metadata="fit_metadata"
)
n_samples = len(X)
rng = np.random.RandomState(0)
score_weights = rng.rand(n_samples)
score_metadata = rng.rand(n_samples)
split_groups = rng.randint(0, 3, n_samples)
split_metadata = rng.rand(n_samples)
fit_sample_weight = rng.rand(n_samples)
fit_metadata = rng.rand(n_samples)
cross_validate(
estimator,
X=X,
y=y,
scoring=scorer,
cv=splitter,
params=dict(
score_weights=score_weights,
score_metadata=score_metadata,
split_groups=split_groups,
split_metadata=split_metadata,
fit_sample_weight=fit_sample_weight,
fit_metadata=fit_metadata,
),
)And the error message:
$ python /tmp/1.py
Traceback (most recent call last):
File "/tmp/1.py", line 35, in <module>
cross_validate(
File "/home/adrin/Projects/sklearn/scikit-learn/sklearn/utils/_param_validation.py", line 211, in wrapper
return func(*args, **kwargs)
File "/home/adrin/Projects/sklearn/scikit-learn/sklearn/model_selection/_validation.py", line 406, in cross_validate
results = parallel(
File "/home/adrin/Projects/sklearn/scikit-learn/sklearn/utils/parallel.py", line 65, in __call__
return super().__call__(iterable_with_config)
File "/home/adrin/miniforge3/envs/sklearn/lib/python3.10/site-packages/joblib/parallel.py", line 1085, in __call__
if self.dispatch_one_batch(iterator):
File "/home/adrin/miniforge3/envs/sklearn/lib/python3.10/site-packages/joblib/parallel.py", line 901, in dispatch_one_batch
self._dispatch(tasks)
File "/home/adrin/miniforge3/envs/sklearn/lib/python3.10/site-packages/joblib/parallel.py", line 819, in _dispatch
job = self._backend.apply_async(batch, callback=cb)
File "/home/adrin/miniforge3/envs/sklearn/lib/python3.10/site-packages/joblib/_parallel_backends.py", line 208, in apply_async
result = ImmediateResult(func)
File "/home/adrin/miniforge3/envs/sklearn/lib/python3.10/site-packages/joblib/_parallel_backends.py", line 597, in __init__
self.results = batch()
File "/home/adrin/miniforge3/envs/sklearn/lib/python3.10/site-packages/joblib/parallel.py", line 288, in __call__
return [func(*args, **kwargs)
File "/home/adrin/miniforge3/envs/sklearn/lib/python3.10/site-packages/joblib/parallel.py", line 288, in <listcomp>
return [func(*args, **kwargs)
File "/home/adrin/Projects/sklearn/scikit-learn/sklearn/utils/parallel.py", line 127, in __call__
return self.function(*args, **kwargs)
File "/home/adrin/Projects/sklearn/scikit-learn/sklearn/model_selection/_validation.py", line 838, in _fit_and_score
fit_params = _check_method_params(X, params=fit_params, indices=train)
File "/home/adrin/Projects/sklearn/scikit-learn/sklearn/utils/validation.py", line 1983, in _check_method_params
method_params_validated[param_key] = _safe_indexing(
File "/home/adrin/Projects/sklearn/scikit-learn/sklearn/utils/__init__.py", line 341, in _safe_indexing
indices_dtype = _determine_key_type(indices)
File "/home/adrin/Projects/sklearn/scikit-learn/sklearn/utils/__init__.py", line 288, in _determine_key_type
raise ValueError(err_msg)
ValueError: No valid specification of the columns. Only a scalar, list or slice of all integers or all strings, or boolean mask is allowed
cc @jeremiedbb