"""simple docstring"""






import fire
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save


def     UpperCAmelCase__ (       lowerCAmelCase__  :Dict      ,	lowerCAmelCase__  :Any      ,	lowerCAmelCase__  :List[Any]=1_0_2_4      ,	lowerCAmelCase__  :Any=1_0_2_4      ,	lowerCAmelCase__  :Union[str, Any]=False      ,	**lowerCAmelCase__  :Any	)				->					Union[str, Any]:
      '''simple docstring'''


      lowercase														=			AutoTokenizer.from_pretrained(lowerCAmelCase__	)
      lowercase														=			SeqaSeqDataset(lowerCAmelCase__      ,	lowerCAmelCase__      ,	lowerCAmelCase__      ,	lowerCAmelCase__      ,	type_path="""train"""      ,	**lowerCAmelCase__	)
      lowercase														=			tok.pad_token_id

      def get_lens(lowerCAmelCase__  :Optional[Any]	):
            lowercase														=			tqdm(
                DataLoader(lowerCAmelCase__      ,	batch_size=5_1_2      ,	num_workers=8      ,	shuffle=lowerCAmelCase__      ,	collate_fn=ds.collate_fn	)      ,	desc=str(ds.len_file	)      ,	)
            lowercase														=			[]
            for batch in dl:
                  lowercase														=			batch["""input_ids"""].ne(lowerCAmelCase__	).sum(1	).tolist()
                  lowercase														=			batch["""labels"""].ne(lowerCAmelCase__	).sum(1	).tolist()
                  if consider_target:
                        for src, tgt in zip(lowerCAmelCase__      ,	lowerCAmelCase__	):
                              max_lens.append(max(lowerCAmelCase__      ,	lowerCAmelCase__	)	)
                  else:
                        max_lens.extend(lowerCAmelCase__	)
            return max_lens

      lowercase														=			get_lens(lowerCAmelCase__	)
      lowercase														=			SeqaSeqDataset(lowerCAmelCase__      ,	lowerCAmelCase__      ,	lowerCAmelCase__      ,	lowerCAmelCase__      ,	type_path="""val"""      ,	**lowerCAmelCase__	)
      lowercase														=			get_lens(lowerCAmelCase__	)
      pickle_save(lowerCAmelCase__      ,	train_ds.len_file	)
      pickle_save(lowerCAmelCase__      ,	val_ds.len_file	)


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




"""simple docstring"""






def     UpperCAmelCase__ (       lowerCAmelCase__  :int	)				->					bool:
      '''simple docstring'''


      lowercase														=			(1 + 2_4 * n) ** 0.5
      return ((1 + root) / 6) % 1 == 0


def     UpperCAmelCase__ (       lowerCAmelCase__  :int = 5_0_0_0	)				->					int:
      '''simple docstring'''


      lowercase														=			[(i * (3 * i - 1)) // 2 for i in range(1      ,	lowerCAmelCase__	)]
      for i, pentagonal_i in enumerate(lowerCAmelCase__	):
            for j in range(lowerCAmelCase__      ,	len(lowerCAmelCase__	)	):
                  lowercase														=			pentagonal_nums[j]
                  lowercase														=			pentagonal_i + pentagonal_j
                  lowercase														=			pentagonal_j - pentagonal_i
                  if is_pentagonal(lowerCAmelCase__	) and is_pentagonal(lowerCAmelCase__	):
                        return b

      return -1


if __name__ == "__main__":
       print(F"""{solution() = }""")



