'''simple docstring'''




import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version

def _lowercase	(      *lowerCamelCase__							,    lowerCamelCase__ = None							,    lowerCamelCase__=True							,    lowerCamelCase__=2						)					->       Any:





       """simple docstring"""


       from .. import __version__

       __UpperCAmelCase  :				Optional[Any]       				=		take_from
       __UpperCAmelCase  :				Any       				=		()
       if not isinstance(args[0]							,    lowerCamelCase__						):
              __UpperCAmelCase  :				Optional[int]       				=		(args,)

       for attribute, version_name, message in args:
              if version.parse(version.parse(lowerCamelCase__						).base_version						) >= version.parse(lowerCamelCase__						):
                     raise ValueError(
                         f"""The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers'"""
                         f""" version {__version__} is >= {version_name}"""						)

              __UpperCAmelCase  :				List[Any]       				=		None
              if isinstance(lowerCamelCase__							,    lowerCamelCase__						) and attribute in deprecated_kwargs:
                     values += (deprecated_kwargs.pop(lowerCamelCase__						),)
                     __UpperCAmelCase  :				List[Any]       				=		f"""The `{attribute}` argument is deprecated and will be removed in version {version_name}."""
              elif hasattr(lowerCamelCase__							,    lowerCamelCase__						):
                     values += (getattr(lowerCamelCase__							,    lowerCamelCase__						),)
                     __UpperCAmelCase  :				Any       				=		f"""The `{attribute}` attribute is deprecated and will be removed in version {version_name}."""
              elif deprecated_kwargs is None:
                     __UpperCAmelCase  :				Optional[int]       				=		f"""`{attribute}` is deprecated and will be removed in version {version_name}."""

              if warning is not None:
                     __UpperCAmelCase  :				Optional[int]       				=		warning + " " if standard_warn else ""
                     warnings.warn(warning + message							,    lowerCamelCase__							,    stacklevel=lowerCamelCase__						)

       if isinstance(lowerCamelCase__							,    lowerCamelCase__						) and len(lowerCamelCase__						) > 0:
              __UpperCAmelCase  :				str       				=		inspect.getouterframes(inspect.currentframe()						)[1]
              __UpperCAmelCase  :				Union[str, Any]       				=		call_frame.filename
              __UpperCAmelCase  :				List[str]       				=		call_frame.lineno
              __UpperCAmelCase  :				Dict       				=		call_frame.function
              __UpperCAmelCase				, __UpperCAmelCase  :				Tuple       				=		next(iter(deprecated_kwargs.items()						)						)
              raise TypeError(f"""{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`"""						)

       if len(lowerCamelCase__						) == 0:
              return
       elif len(lowerCamelCase__						) == 1:
              return values[0]
       return values







'''simple docstring'''




from collections import Counter

import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split

_a   :	str 							=   datasets.load_iris()

_a   :	List[Any] 							=   np.array(data["data"])
_a   :	Optional[Any] 							=   np.array(data["target"])
_a   :	Dict 							=   data["target_names"]

_a							,					_a							,					_a							,					_a   :	Any 							=   train_test_split(X, y)

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__						)					->       Tuple:





       """simple docstring"""


       return np.linalg.norm(np.array(lowerCamelCase__						) - np.array(lowerCamelCase__						)						)

def _lowercase	(      lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__							,    lowerCamelCase__=5						)					->       int:





       """simple docstring"""


       __UpperCAmelCase  :				List[Any]       				=		zip(lowerCamelCase__							,    lowerCamelCase__						)
       # List of distances of all points from the point to be classified
       __UpperCAmelCase  :				int       				=		[]
       for data_point in data:
              __UpperCAmelCase  :				Optional[Any]       				=		euclidean_distance(data_point[0]							,    lowerCamelCase__						)
              distances.append((distance, data_point[1])						)
       # Choosing 'k' points with the least distances.
       __UpperCAmelCase  :				Union[str, Any]       				=		[i[1] for i in sorted(lowerCamelCase__						)[:k]]
       # Most commonly occurring class among them
       # is the class into which the point is classified
       __UpperCAmelCase  :				Dict       				=		Counter(lowerCamelCase__						).most_common(1						)[0][0]
       return classes[result]


if __name__ == "__main__":
   print(classifier(X_train, y_train, classes, [4.4, 3.1, 1.3, 1.4]))






