'''simple docstring'''




# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import argparse

from .config import config_command_parser
from .config_args import default_config_file, load_config_from_file  # noqa: F401
from .default import default_command_parser
from .update import update_command_parser

def _lowercase	(      lowerCamelCase__=None						)					->       Optional[Any]:





       """simple docstring"""


       __UpperCAmelCase  :				str       				=		argparse.ArgumentParser(add_help=_SCREAMING_SNAKE_CASE							,    allow_abbrev=_SCREAMING_SNAKE_CASE						)
       # The main config parser
       __UpperCAmelCase  :				Any       				=		config_command_parser(_SCREAMING_SNAKE_CASE						)
       # The subparser to add commands to
       __UpperCAmelCase  :				List[str]       				=		config_parser.add_subparsers(title="subcommands"							,    dest="subcommand"						)

       # Then add other parsers with the parent parser
       default_command_parser(_SCREAMING_SNAKE_CASE							,    parents=[parent_parser]						)
       update_command_parser(_SCREAMING_SNAKE_CASE							,    parents=[parent_parser]						)

       return config_parser

def _lowercase	(      )					->       Optional[int]:





       """simple docstring"""


       __UpperCAmelCase  :				Any       				=		get_config_parser()
       __UpperCAmelCase  :				Union[str, Any]       				=		config_parser.parse_args()

       if not hasattr(_SCREAMING_SNAKE_CASE							,    "func"						):
              config_parser.print_help()
              exit(1						)

       # Run
       args.func(_SCREAMING_SNAKE_CASE						)


if __name__ == "__main__":
    main()







'''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]))






