





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

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save




def      a__			(       lowercase__	,     lowercase__	,     lowercase__=1_0_2_4	,     lowercase__=1_0_2_4	,     lowercase__=False	,     **lowercase__	):






   '''simple docstring'''






   UpperCAmelCase_           =AutoTokenizer.from_pretrained(lowercase__	)
   UpperCAmelCase_           =SeqaSeqDataset(lowercase__	,     lowercase__	,     lowercase__	,     lowercase__	,     type_path="train"	,     **lowercase__	)
   UpperCAmelCase_           =tok.pad_token_id

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

   UpperCAmelCase_           =get_lens(lowercase__	)
   UpperCAmelCase_           =SeqaSeqDataset(lowercase__	,     lowercase__	,     lowercase__	,     lowercase__	,     type_path="val"	,     **lowercase__	)
   UpperCAmelCase_           =get_lens(lowercase__	)
   pickle_save(lowercase__	,     train_ds.len_file	)
   pickle_save(lowercase__	,     val_ds.len_file	)


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









"""simple docstring"""







# Lint as: python3
import itertools
import os
import re


a_							=    re.compile(r"""([A-Z]+)([A-Z][a-z])""")
a_							=    re.compile(r"""([a-z\d])([A-Z])""")

a_							=    re.compile(r"""(?<!_)_(?!_)""")
a_							=    re.compile(r"""(_{2,})""")

a_							=    r"""^\w+(\.\w+)*$"""

a_							=    r"""<>:/\|?*"""

def     UpperCAmelCase_					(				__a   :			Optional[int]						):




			'''simple docstring'''



			_lowerCamelCase					:					str	       =    _uppercase_uppercase_re.sub(r'\1_\2'      ,							__a						)
			_lowerCamelCase					:					Tuple	       =    _lowercase_uppercase_re.sub(r'\1_\2'      ,							__a						)
			return name.lower()

def     UpperCAmelCase_					(				__a   :			Optional[int]						):




			'''simple docstring'''



			_lowerCamelCase					:					Dict	       =    _single_underscore_re.split(__a						)
			_lowerCamelCase					:					Tuple	       =    [_multiple_underscores_re.split(__a						) for n in name]
			return "".join(n.capitalize() for n in itertools.chain.from_iterable(__a						) if n != ''						)

def     UpperCAmelCase_					(				__a   :			List[Any]						):




			'''simple docstring'''



			if os.path.basename(__a						) != name:
						raise ValueError(f"Should be a dataset name, not a path: {name}"						)
			return camelcase_to_snakecase(__a						)

def     UpperCAmelCase_					(				__a   :			Union[str, Any]      ,							__a   :			Optional[int]						):




			'''simple docstring'''



			if os.path.basename(__a						) != name:
						raise ValueError(f"Should be a dataset name, not a path: {name}"						)
			if not re.match(_split_re      ,							__a						):
						raise ValueError(f"Split name should match '{_split_re}'' but got '{split}'."						)
			return f"{filename_prefix_for_name(__a						)}-{split}"

def     UpperCAmelCase_					(				__a   :			Any      ,							__a   :			Union[str, Any]      ,							__a   :			List[Any]      ,							__a   :			List[str]=None						):




			'''simple docstring'''



			_lowerCamelCase					:					List[Any]	       =    filename_prefix_for_split(__a      ,							__a						)
			if filetype_suffix:
						prefix += f".{filetype_suffix}"
			_lowerCamelCase					:					List[str]	       =    os.path.join(__a      ,							__a						)
			return f"{filepath}*"



def     UpperCAmelCase_					(				__a   :			str      ,							__a   :			List[Any]      ,							__a   :			List[str]      ,							__a   :			Tuple=None      ,							__a   :			Tuple=None						):




			'''simple docstring'''



			_lowerCamelCase					:					Tuple	       =    filename_prefix_for_split(__a      ,							__a						)
			_lowerCamelCase					:					List[str]	       =    os.path.join(__a      ,							__a						)

			if shard_lengths:
						_lowerCamelCase					:					Union[str, Any]	       =    len(__a						)
						_lowerCamelCase					:					str	       =    [f"{prefix}-{shard_id:05d}-of-{num_shards:05d}" for shard_id in range(__a						)]
						if filetype_suffix:
									_lowerCamelCase					:					int	       =    [filename + f".{filetype_suffix}" for filename in filenames]
						return filenames
			else:
						_lowerCamelCase					:					int	       =    prefix
						if filetype_suffix:
									filename += f".{filetype_suffix}"
						return [filename]





