




def 		lowerCAmelCase_ (						lowerCamelCase ):
				if not numbers:
								return 0

				if not isinstance(lowerCamelCase						,  (list, tuple) ) or not all(
				    isinstance(lowerCamelCase						,  lowerCamelCase ) for number in numbers ):
								raise ValueError("""numbers must be an iterable of integers""" )

				__magic_name__						:						List[Any]										=numbers[0]

				for i in range(1						,  len(lowerCamelCase ) ):
								# update the maximum and minimum subarray products
								__magic_name__						:						Dict										=numbers[i]
								if number < 0:
												__magic_name__					,			__magic_name__						:						str										=min_till_now, max_till_now
								__magic_name__						:						Union[str, Any]										=max(lowerCamelCase						,  max_till_now * number )
								__magic_name__						:						Optional[Any]										=min(lowerCamelCase						,  min_till_now * number )

								# update the maximum product found till now
								__magic_name__						:						Union[str, Any]										=max(lowerCamelCase						,  lowerCamelCase )

				return max_prod










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)




