






'''simple docstring'''

import pytest

import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""",						[None, 400 * 2**20, 600 * 2**20]     )
@pytest.mark.parametrize("""input_in_memory_max_size""",						["""default""", 0, 100 * 2**20, 900 * 2**20]     )
def     __lowercase  (_lowercase,						_lowercase,						_lowercase     )   ->     Union[str, Any]:


     """simple docstring"""
     if input_in_memory_max_size != "default":
          monkeypatch.setattr(datasets.config,						"""IN_MEMORY_MAX_SIZE""",						_lowercase     )
     __lowerCamelCase						:       Optional[Any]				   =				datasets.config.IN_MEMORY_MAX_SIZE
     if input_in_memory_max_size == "default":
          assert in_memory_max_size == 0
     else:
          assert in_memory_max_size == input_in_memory_max_size
     if dataset_size and in_memory_max_size:
          __lowerCamelCase						:       Tuple				   =				dataset_size < in_memory_max_size
     else:
          __lowerCamelCase						:       int				   =				False
     __lowerCamelCase						:       Dict				   =				is_small_dataset(_lowercase     )
     assert result == expected











'''simple docstring'''

from __future__ import annotations

import typing
from collections.abc import Iterable

import numpy as np

UpperCAmelCase__						:List[str]          =			typing.Union[Iterable[float], Iterable[int], np.ndarray]  # noqa: UP007
UpperCAmelCase__						:Optional[int]          =			typing.Union[np.floataa, int, float]  # noqa: UP007
def     __lowercase  (_lowercase,						_lowercase     )   ->     VectorOut:


     """simple docstring"""
     return np.sqrt(np.sum((np.asarray(_lowercase     ) - np.asarray(_lowercase     )) ** 2     )     )
def     __lowercase  (_lowercase,						_lowercase     )   ->     VectorOut:


     """simple docstring"""
     return sum((va - va) ** 2 for va, va in zip(_lowercase,						_lowercase     )     ) ** (1 / 2)


if __name__ == "__main__":
   def     __lowercase  ()   ->     None:


        """simple docstring"""
        from timeit import timeit

        print("""Without Numpy"""     )
        print(
            timeit(
                """euclidean_distance_no_np([1, 2, 3], [4, 5, 6])""",						number=10_000,						globals=globals(),						)     )
        print("""With Numpy"""     )
        print(
            timeit(
                """euclidean_distance([1, 2, 3], [4, 5, 6])""",						number=10_000,						globals=globals(),						)     )
   benchmark()



