


'''simple docstring'''

def __snake_case      (   UpperCAmelCase_		:		int = 10      ,       UpperCAmelCase_		:		int = 1000      ,       UpperCAmelCase_		:		bool = True	):
 assert (
     isinstance(UpperCAmelCase_      ,       UpperCAmelCase_	)
     and isinstance(UpperCAmelCase_      ,       UpperCAmelCase_	)
     and isinstance(UpperCAmelCase_      ,       UpperCAmelCase_	)
 ), "Invalid type of value(s) specified to function!"

 if min_val > max_val:
  raise ValueError("Invalid value for min_val or max_val (min_value < max_value)"	)
 return min_val if option else max_val





def __snake_case      (   UpperCAmelCase_		:		int      ,       UpperCAmelCase_		:		int	):
 return int((number_a + number_a) / 2	)





def __snake_case      (   UpperCAmelCase_		:		int      ,       UpperCAmelCase_		:		int      ,       UpperCAmelCase_		:		int	):
 assert (
     isinstance(UpperCAmelCase_      ,       UpperCAmelCase_	) and isinstance(UpperCAmelCase_      ,       UpperCAmelCase_	) and isinstance(UpperCAmelCase_      ,       UpperCAmelCase_	)
 ), 'argument values must be type of "int"'

 if lower > higher:
  raise ValueError("argument value for lower and higher must be(lower > higher)"	)

 if not lower < to_guess < higher:
  raise ValueError(
      "guess value must be within the range of lower and higher value"	)

 def answer(UpperCAmelCase_		:		int	) -> str:
  if number > to_guess:
   return "high"
  elif number < to_guess:
   return "low"
  else:
   return "same"

 print("started..."	)

 lowerCamelCase_  				=						lower
 lowerCamelCase_  				=						higher

 lowerCamelCase_  				=						[]

 while True:
  lowerCamelCase_  				=						get_avg(UpperCAmelCase_      ,       UpperCAmelCase_	)
  last_numbers.append(UpperCAmelCase_	)

  if answer(UpperCAmelCase_	) == "low":
   lowerCamelCase_  				=						number
  elif answer(UpperCAmelCase_	) == "high":
   lowerCamelCase_  				=						number
  else:
   break

 print(F'''guess the number : {last_numbers[-1]}'''	)
 print(F'''details : {last_numbers!s}'''	)





def __snake_case      (   ):
 lowerCamelCase_  				=						int(input("Enter lower value : "	).strip()	)
 lowerCamelCase_  				=						int(input("Enter high value : "	).strip()	)
 lowerCamelCase_  				=						int(input("Enter value to guess : "	).strip()	)
 guess_the_number(UpperCAmelCase_      ,       UpperCAmelCase_      ,       UpperCAmelCase_	)


if __name__ == "__main__":
     main()







'''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 __snake_case      (   UpperCAmelCase_		:		List[str]      ,       UpperCAmelCase_		:		Optional[int]      ,       UpperCAmelCase_		:		Optional[int]=1024      ,       UpperCAmelCase_		:		int=1024      ,       UpperCAmelCase_		:		Optional[Any]=False      ,       **UpperCAmelCase_		:		Optional[Any]	):
 lowerCamelCase_  				=						AutoTokenizer.from_pretrained(UpperCAmelCase_	)
 lowerCamelCase_  				=						SeqaSeqDataset(UpperCAmelCase_      ,       UpperCAmelCase_      ,       UpperCAmelCase_      ,       UpperCAmelCase_      ,       type_path="train"      ,       **UpperCAmelCase_	)
 lowerCamelCase_  				=						tok.pad_token_id

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

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


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



