




import operator




def 		lowerCAmelCase_ (						lowerCamelCase						,  lowerCamelCase = False						,  lowerCamelCase = None ):
				__magic_name__						:						Any										=operator.lt if reverse else operator.gt
				__magic_name__						:						Union[str, Any]										=solution or []

				if not arr:
								return solution

				__magic_name__						:						Optional[Any]										=[arr.pop(0 )]
				for i, item in enumerate(lowerCamelCase ):
								if _operator(lowerCamelCase						,  sublist[-1] ):
												sublist.append(lowerCamelCase )
												arr.pop(lowerCamelCase )

    #  merging sublist into solution list
				if not solution:
								solution.extend(lowerCamelCase )
				else:
								while sublist:
												__magic_name__						:						List[Any]										=sublist.pop(0 )
												for i, xx in enumerate(lowerCamelCase ):
																if not _operator(lowerCamelCase						,  lowerCamelCase ):
																				solution.insert(lowerCamelCase						,  lowerCamelCase )
																				break
												else:
																solution.append(lowerCamelCase )

				strand_sort(lowerCamelCase						,  lowerCamelCase						,  lowerCamelCase )
				return solution


if __name__ == "__main__":
							assert strand_sort([4, 3, 5, 1, 2]) == [1, 2, 3, 4, 5]
							assert strand_sort([4, 3, 5, 1, 2], reverse=True) == [5, 4, 3, 2, 1]










from pathlib import Path

import fire
from tqdm import tqdm




def 		lowerCAmelCase_ (						lowerCamelCase="ro"						,  lowerCamelCase="en"						,  lowerCamelCase="wmt16"						,  lowerCamelCase=None ):
				try:
								import datasets
				except (ModuleNotFoundError, ImportError):
								raise ImportError("""run pip install datasets""" )
				__magic_name__						:						Dict										=F"{src_lang}-{tgt_lang}"
				print(F"Converting {dataset}-{pair}" )
				__magic_name__						:						Dict										=datasets.load_dataset(lowerCamelCase						,  lowerCamelCase )
				if save_dir is None:
								__magic_name__						:						Optional[int]										=F"{dataset}-{pair}"
				__magic_name__						:						int										=Path(lowerCamelCase )
				save_dir.mkdir(exist_ok=lowerCamelCase )

				for split in ds.keys():
								print(F"Splitting {split} with {ds[split].num_rows} records" )

								# to save to val.source, val.target like summary datasets
								__magic_name__						:						Dict										="""val""" if split == """validation""" else split
								__magic_name__						:						List[Any]										=save_dir.joinpath(F"{fn}.source" )
								__magic_name__						:						Optional[int]										=save_dir.joinpath(F"{fn}.target" )
								__magic_name__						:						Optional[Any]										=src_path.open("""w+""" )
								__magic_name__						:						List[Any]										=tgt_path.open("""w+""" )

								# reader is the bottleneck so writing one record at a time doesn't slow things down
								for x in tqdm(ds[split] ):
												__magic_name__						:						str										=x["""translation"""]
												src_fp.write(ex[src_lang] + """\n""" )
												tgt_fp.write(ex[tgt_lang] + """\n""" )

				print(F"Saved {dataset} dataset to {save_dir}" )


if __name__ == "__main__":
							fire.Fire(download_wmt_dataset)




