
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_3_3_7	, num_examples=4_2	, dataset_name="my_dataset"    )}    ),
        SplitDict({"train": SplitInfo(name="train"	, num_bytes=1_3_3_7	, num_examples=4_2    )}    ),
        SplitDict({"train": SplitInfo()}    ),
    ]	, )
def 			lowerCamelCase_ (				lowerCamelCase__    ):
				lowerCamelCase_						=			split_dict._to_yaml_list()
				assert len(lowerCamelCase__    ) == len(lowerCamelCase__    )
				lowerCamelCase_						=			SplitDict._from_yaml_list(lowerCamelCase__    )
				for split_name, split_info in split_dict.items():
								# dataset_name field is deprecated, and is therefore not part of the YAML dump
								lowerCamelCase_						=			None
								# the split name of split_dict takes over the name of the split info object
								lowerCamelCase_						=			split_name
				assert split_dict == reloaded





@pytest.mark.parametrize(
    "split_info"	, [SplitInfo(), SplitInfo(dataset_name=lowerCamelCase__    ), SplitInfo(dataset_name="my_dataset"    )]    )
def 			lowerCamelCase_ (				lowerCamelCase__    ):
				# For backward compatibility, we need asdict(split_dict) to return split info dictrionaries with the "dataset_name"
				# field even if it's deprecated. This way old versionso of `datasets` can still reload dataset_infos.json files
				lowerCamelCase_						=			asdict(SplitDict({"train": split_info}    )    )
				assert "dataset_name" in split_dict_asdict["train"]
				assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name




def 			lowerCamelCase_ (				lowerCamelCase__	, lowerCamelCase__    ):
				lowerCamelCase_						=			[0 for i in range(r + 1    )]
				# nc0 = 1
				lowerCamelCase_						=			1
				for i in range(1	, n + 1    ):
								# to compute current row from previous row.
								lowerCamelCase_						=			min(lowerCamelCase__	, lowerCamelCase__    )
								while j > 0:
												c[j] += c[j - 1]
												j -= 1
				return c[r]





print(binomial_coefficient(n=1_0, r=5))


