






import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict






@pytest.mark.parametrize(
    'split_dict'     ,     [
        SplitDict(),
        SplitDict({'train': SplitInfo(name='train'     ,     num_bytes=1_337     ,     num_examples=42     ,     dataset_name='my_dataset'				)}				),
        SplitDict({'train': SplitInfo(name='train'     ,     num_bytes=1_337     ,     num_examples=42				)}				),
        SplitDict({'train': SplitInfo()}				),
    ]     ,     )
def    __magic_name__    (	SCREAMING_SNAKE_CASE				)     ->    Optional[int]:
							_lowercase							:   List[Any] 							=   split_dict._to_yaml_list()
							assert len(SCREAMING_SNAKE_CASE				) == len(SCREAMING_SNAKE_CASE				)
							_lowercase							:   Union[str, Any] 							=   SplitDict._from_yaml_list(SCREAMING_SNAKE_CASE				)
							for split_name, split_info in split_dict.items():
														# dataset_name field is deprecated, and is therefore not part of the YAML dump
														_lowercase							:   str 							=   None
														# the split name of split_dict takes over the name of the split info object
														_lowercase							:   int 							=   split_name
							assert split_dict == reloaded






@pytest.mark.parametrize(
    'split_info'     ,     [SplitInfo(), SplitInfo(dataset_name=SCREAMING_SNAKE_CASE				), SplitInfo(dataset_name='my_dataset'				)]				)
def    __magic_name__    (	SCREAMING_SNAKE_CASE				)     ->    Any:
							_lowercase							:   Tuple 							=   asdict(SplitDict({'train': split_info}				)				)
							assert "dataset_name" in split_dict_asdict["train"]
							assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name






from PIL import Image


def    a      ( a	)     ->Image:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE						,							SCREAMING_SNAKE_CASE     						= image.size
			SCREAMING_SNAKE_CASE     						= 0
			SCREAMING_SNAKE_CASE     						= image.load()
			for i in range(a	):
						for j in range(a	):
									SCREAMING_SNAKE_CASE     						= pixels[j, i]
									mean += pixel
			mean //= width * height

			for j in range(a	):
						for i in range(a	):
									SCREAMING_SNAKE_CASE     						= 255 if pixels[i, j] > mean else 0
			return image


if __name__ == "__main__":
							__lowerCAmelCase					   =       mean_threshold(Image.open('path_to_image').convert('L'))
							image.save('output_image_path')