





from typing import Callable, Optional

from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream

class  __A(						__UpperCAmelCase ):

     def __init__(      self,       A,       A = None,       A = None,       A = False,       A = False,       A = None,       A = None,       **A,       ):





            """simple docstring"""

            super().__init__(
                features=A,       cache_dir=A,       keep_in_memory=A,       streaming=A,       num_proc=A,       **A,       )
            _UpperCamelCase              =						Generator(
                cache_dir=A,       features=A,       generator=A,       gen_kwargs=A,       **A,       )



     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            if self.streaming:
                   _UpperCamelCase              =						self.builder.as_streaming_dataset(split='''train'''      )
            # Build regular (map-style) dataset
            else:
                   _UpperCamelCase              =						None
                   _UpperCamelCase              =						None
                   _UpperCamelCase              =						None
                   _UpperCamelCase              =						None

                   self.builder.download_and_prepare(
                       download_config=A,       download_mode=A,       verification_mode=A,       base_path=A,       num_proc=self.num_proc,       )
                   _UpperCamelCase              =						self.builder.as_dataset(
                       split='''train''',       verification_mode=A,       in_memory=self.keep_in_memory      )
            return dataset













from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm


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


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase					):

       if dataset.ndim != value_array.ndim:
              _UpperCamelCase              =						(
                  '''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              =						(
                         '''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              =						(
                  '''Input data have different datatype... '''
                  f'''dataset : {dataset.dtype}, value_array : {value_array.dtype}'''
              )
              raise TypeError(lowerCAmelCase					)

       _UpperCamelCase              =						[]

       for value in value_array:
              _UpperCamelCase              =						euclidean(lowerCAmelCase    ,       dataset[0]					)
              _UpperCamelCase              =						dataset[0].tolist()

              for dataset_value in dataset[1:]:
                     _UpperCamelCase              =						euclidean(lowerCAmelCase    ,       lowerCAmelCase					)

                     if dist > temp_dist:
                            _UpperCamelCase              =						temp_dist
                            _UpperCamelCase              =						dataset_value.tolist()

              answer.append([vector, dist]					)

       return answer


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


if __name__ == "__main__":
       import doctest

       doctest.testmod()






