


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

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save

def       lowercase_		(		_A			:    Tuple    ,					_A			:    int    ,					_A			:    Tuple=1024    ,					_A			:    Optional[int]=1024    ,					_A			:    Optional[Any]=False    ,					**_A			:    List[Any]						):

      """simple docstring"""




      lowerCamelCase__		:				Tuple    =  AutoTokenizer.from_pretrained(_A						)
      lowerCamelCase__		:				Dict    =  SeqaSeqDataset(_A    ,					_A    ,					_A    ,					_A    ,					type_path="train"    ,					**_A						)
      lowerCamelCase__		:				int    =  tok.pad_token_id

      def get_lens(_A			:    List[str]						):
            lowerCamelCase__		:				Optional[int]    =  tqdm(
                DataLoader(_A    ,					batch_size=512    ,					num_workers=8    ,					shuffle=_A    ,					collate_fn=ds.collate_fn						)    ,					desc=str(ds.len_file						)    ,					)
            lowerCamelCase__		:				Any    =  []
            for batch in dl:
                  lowerCamelCase__		:				Dict    =  batch["input_ids"].ne(_A						).sum(1						).tolist()
                  lowerCamelCase__		:				List[Any]    =  batch["labels"].ne(_A						).sum(1						).tolist()
                  if consider_target:
                        for src, tgt in zip(_A    ,					_A						):
                              max_lens.append(max(_A    ,					_A						)						)
                  else:
                        max_lens.extend(_A						)
            return max_lens

      lowerCamelCase__		:				int    =  get_lens(_A						)
      lowerCamelCase__		:				int    =  SeqaSeqDataset(_A    ,					_A    ,					_A    ,					_A    ,					type_path="val"    ,					**_A						)
      lowerCamelCase__		:				int    =  get_lens(_A						)
      pickle_save(_A    ,					train_ds.len_file						)
      pickle_save(_A    ,					val_ds.len_file						)


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






from collections import defaultdict

def       lowercase_		(		_A			:    int						):

      """simple docstring"""




      lowerCamelCase__		:				Union[str, Any]    =  1
      lowerCamelCase__		:				Dict    =  True
      for v in tree[start]:
            if v not in visited:
                  ret += dfs(_A						)
      if ret % 2 == 0:
            cuts.append(_A						)
      return ret

def       lowercase_		(		):

      """simple docstring"""




      dfs(1						)


if __name__ == "__main__":
    A,  A      :    Tuple		=					10, 9
    A      :    int		=					defaultdict(list)
    A      :    dict[int, bool]		=					{}
    A      :    list[int]		=					[]
    A      :    List[str]		=					0
    A      :    Tuple		=					[(2, 1), (3, 1), (4, 3), (5, 2), (6, 1), (7, 2), (8, 6), (9, 8), (10, 8)]
    for u, v in edges:
        tree[u].append(v)
        tree[v].append(u)
    even_tree()
    print(len(cuts) - 1)


