


'''simple docstring'''


import importlib.metadata
import operator
import re
import sys
from typing import Optional

from packaging import version


lowerCamelCase__    	=     {
    '<': operator.lt,
    '<=': operator.le,
    '==': operator.eq,
    '!=': operator.ne,
    '>=': operator.ge,
    '>': operator.gt,
}






def  __lowerCAmelCase (__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase   ):
		if got_ver is None or want_ver is None:
				raise ValueError(
				    F"""Unable to compare versions for {requirement}: need={want_ver} found={got_ver}. This is unusual. Consider"""
				    F""" reinstalling {pkg}."""   )
		if not ops[op](version.parse(__lowerCAmelCase   )      , version.parse(__lowerCAmelCase   )   ):
				raise ImportError(
				    F"""{requirement} is required for a normal functioning of this module, but found {pkg}=={got_ver}.{hint}"""   )






def  __lowerCAmelCase (__lowerCAmelCase      , __lowerCAmelCase = None   ):
		_UpperCAmelCase		:       Optional[Any]								=      F"""\n{hint}""" if hint is not None else ""

		# non-versioned check
		if re.match(R"^[\w_\-\d]+$"      , __lowerCAmelCase   ):
				_UpperCAmelCase		:       Optional[Any]								=      requirement, None, None
		else:
				_UpperCAmelCase		:       Union[str, Any]								=      re.findall(R"^([^!=<>\s]+)([\s!=<>]{1,2}.+)"      , __lowerCAmelCase   )
				if not match:
						raise ValueError(
						    "requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23, but"
						    F""" got {requirement}"""   )
				_UpperCAmelCase		:       Optional[Any]								=      match[0]
				_UpperCAmelCase		:       str								=      want_full.split(","   )  # there could be multiple requirements
				_UpperCAmelCase		:       List[str]								=      {}
				for w in want_range:
						_UpperCAmelCase		:       Optional[int]								=      re.findall(R"^([\s!=<>]{1,2})(.+)"      , __lowerCAmelCase   )
						if not match:
								raise ValueError(
								    "requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23,"
								    F""" but got {requirement}"""   )
						_UpperCAmelCase		:       Optional[Any]								=      match[0]
						_UpperCAmelCase		:       Any								=      want_ver
						if op not in ops:
								raise ValueError(F"""{requirement}: need one of {list(ops.keys()   )}, but got {op}"""   )

    # special case
		if pkg == "python":
				_UpperCAmelCase		:       List[str]								=      ".".join([str(__lowerCAmelCase   ) for x in sys.version_info[:3]]   )
				for op, want_ver in wanted.items():
						_compare_versions(__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase   )
				return

		# check if any version is installed
		try:
				_UpperCAmelCase		:       List[Any]								=      importlib.metadata.version(__lowerCAmelCase   )
		except importlib.metadata.PackageNotFoundError:
				raise importlib.metadata.PackageNotFoundError(
				    F"""The '{requirement}' distribution was not found and is required by this application. {hint}"""   )

		# check that the right version is installed if version number or a range was provided
		if want_ver is not None:
				for op, want_ver in wanted.items():
						_compare_versions(__lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase      , __lowerCAmelCase   )






def  __lowerCAmelCase (__lowerCAmelCase   ):
		_UpperCAmelCase		:       int								=      "Try: pip install transformers -U or pip install -e '.[dev]' if you're working with git main"
		return require_version(__lowerCAmelCase      , __lowerCAmelCase   )







'''simple docstring'''


from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm






def  __lowerCAmelCase (__lowerCAmelCase      , __lowerCAmelCase   ):
		return math.sqrt(sum(pow(a - b      , 2   ) for a, b in zip(__lowerCAmelCase      , __lowerCAmelCase   )   )   )






def  __lowerCAmelCase (__lowerCAmelCase      , __lowerCAmelCase   ):

		if dataset.ndim != value_array.ndim:
				_UpperCAmelCase		:       Optional[Any]								=      (
				    "Wrong input data's dimensions... "
				    F"""dataset : {dataset.ndim}, value_array : {value_array.ndim}"""
				)
				raise ValueError(__lowerCAmelCase   )

		try:
				if dataset.shape[1] != value_array.shape[1]:
						_UpperCAmelCase		:       Optional[int]								=      (
						    "Wrong input data's shape... "
						    F"""dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}"""
						)
						raise ValueError(__lowerCAmelCase   )
		except IndexError:
				if dataset.ndim != value_array.ndim:
						raise TypeError("Wrong shape"   )

		if dataset.dtype != value_array.dtype:
				_UpperCAmelCase		:       Union[str, Any]								=      (
				    "Input data have different datatype... "
				    F"""dataset : {dataset.dtype}, value_array : {value_array.dtype}"""
				)
				raise TypeError(__lowerCAmelCase   )

		_UpperCAmelCase		:       Optional[int]								=      []

		for value in value_array:
				_UpperCAmelCase		:       List[str]								=      euclidean(__lowerCAmelCase      , dataset[0]   )
				_UpperCAmelCase		:       Dict								=      dataset[0].tolist()

				for dataset_value in dataset[1:]:
						_UpperCAmelCase		:       int								=      euclidean(__lowerCAmelCase      , __lowerCAmelCase   )

						if dist > temp_dist:
								_UpperCAmelCase		:       Tuple								=      temp_dist
								_UpperCAmelCase		:       Dict								=      dataset_value.tolist()

				answer.append([vector, dist]   )

		return answer






def  __lowerCAmelCase (__lowerCAmelCase      , __lowerCAmelCase   ):
		return np.dot(__lowerCAmelCase      , __lowerCAmelCase   ) / (norm(__lowerCAmelCase   ) * norm(__lowerCAmelCase   ))


if __name__ == "__main__":
						import doctest

						doctest.testmod()



