




from collections.abc import Iterable
from typing import Generic, TypeVar

UpperCamelCase__         =      TypeVar("""_T""")
class       a__   ( Generic[_T]				):






						def __init__(       self		,      _A = None      ):




											"""simple docstring"""



											__lowerCAmelCase           =	list(iterable or []      )
											__lowerCAmelCase           =	[]






						def __len__(       self      ):




											"""simple docstring"""



											return len(self._stacka      ) + len(self._stacka      )






						def __repr__(       self      ):




											"""simple docstring"""



											return f"""Queue({tuple(self._stacka[::-1] + self._stacka      )})"""






						def     __SCREAMING_SNAKE_CASE(       self		,      _A      ):




											"""simple docstring"""



											self._stacka.append(_A      )






						def     __SCREAMING_SNAKE_CASE(       self      ):




											"""simple docstring"""



											__lowerCAmelCase           =	self._stacka.pop
											__lowerCAmelCase           =	self._stacka.append

											if not self._stacka:
																while self._stacka:
																					stacka_append(stacka_pop()      )

											if not self._stacka:
																raise IndexError("Queue is empty"      )
											return self._stacka.pop()


if __name__ == "__main__":
					from doctest import testmod

					testmod()










from pathlib import Path

import fire
from tqdm import tqdm







def      _a				(						SCREAMING_SNAKE_CASE_							:    Dict="ro"				,				SCREAMING_SNAKE_CASE_							:    Union[str, Any]="en"				,				SCREAMING_SNAKE_CASE_							:    Optional[Any]="wmt16"				,				SCREAMING_SNAKE_CASE_							:    List[str]=None					):
					try:
										import datasets
					except (ModuleNotFoundError, ImportError):
										raise ImportError("run pip install datasets"					)
					__lowerCAmelCase           =	F"""{src_lang}-{tgt_lang}"""
					print(F"""Converting {dataset}-{pair}"""					)
					__lowerCAmelCase           =	datasets.load_dataset(SCREAMING_SNAKE_CASE_				,				SCREAMING_SNAKE_CASE_					)
					if save_dir is None:
										__lowerCAmelCase           =	F"""{dataset}-{pair}"""
					__lowerCAmelCase           =	Path(SCREAMING_SNAKE_CASE_					)
					save_dir.mkdir(exist_ok=SCREAMING_SNAKE_CASE_					)

					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
										__lowerCAmelCase           =	"val" if split == "validation" else split
										__lowerCAmelCase           =	save_dir.joinpath(F"""{fn}.source"""					)
										__lowerCAmelCase           =	save_dir.joinpath(F"""{fn}.target"""					)
										__lowerCAmelCase           =	src_path.open("w+"					)
										__lowerCAmelCase           =	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]					):
															__lowerCAmelCase           =	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)




