8000 [MRG] Fix sklearn.utils._param_validation._InstancesOf is insufficient for numpy data types by Diadochokinetic · Pull Request #23600 · scikit-learn/scikit-learn · GitHub
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[MRG] Fix sklearn.utils._param_validation._InstancesOf is insufficient for numpy data types #23600

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[MRG] Fix sklearn.utils._param_validation._InstancesOf is insufficient for numpy data types #23600

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12 changes: 6 additions & 6 deletions sklearn/utils/_param_validation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -173,12 +173,12 @@ class _InstancesOf(_Constraint):

Parameters
----------
type : type
The valid type.
param_type : param_type
The valid paramater type.
"""

def __init__(self, type):
self.type = type
def __init__(self, param_type):
self.param_type = param_type
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As commented in #23599 (comment):

The "type" here is not the builtin type anymore but the locally scoped "type". A simple Python example:

class A:
    def __init__(self, type):
        self.type = type
        
a = A(100)
print(a.type)
# 100

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Thank you for clarifiying


def _type_name(self, t):
"""Convert type into human readable string."""
Expand All @@ -193,10 +193,10 @@ def _type_name(self, t):
return f"{module}.{qualname}"

def is_satisfied_by(self, val):
return isinstance(val, self.type)
return isinstance(val, self.param_type)

def __str__(self):
return f"an instance of {self._type_name(self.type)!r}"
return f"an instance of {self._type_name(self.param_type)!r}"


class _NoneConstraint(_Constraint):
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0