
"""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 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_  ,				UpperCamelCase_=1024  ,				UpperCamelCase_=1024  ,				UpperCamelCase_=False  ,				**UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = AutoTokenizer.from_pretrained(UpperCamelCase_				)
		__SCREAMING_SNAKE_CASE            = SeqaSeqDataset(UpperCamelCase_  ,				UpperCamelCase_  ,				UpperCamelCase_  ,				UpperCamelCase_  ,				type_path="""train"""  ,				**UpperCamelCase_				)
		__SCREAMING_SNAKE_CASE            = tok.pad_token_id

		def get_lens(UpperCamelCase_				):
				__SCREAMING_SNAKE_CASE            = tqdm(
				    DataLoader(UpperCamelCase_  ,				batch_size=512  ,				num_workers=8  ,				shuffle=UpperCamelCase_  ,				collate_fn=ds.collate_fn				)  ,				desc=str(ds.len_file				)  ,				)
				__SCREAMING_SNAKE_CASE            = []
				for batch in dl:
						__SCREAMING_SNAKE_CASE            = batch["""input_ids"""].ne(UpperCamelCase_				).sum(1				).tolist()
						__SCREAMING_SNAKE_CASE            = 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

		__SCREAMING_SNAKE_CASE            = get_lens(UpperCamelCase_				)
		__SCREAMING_SNAKE_CASE            = SeqaSeqDataset(UpperCamelCase_  ,				UpperCamelCase_  ,				UpperCamelCase_  ,				UpperCamelCase_  ,				type_path="""val"""  ,				**UpperCamelCase_				)
		__SCREAMING_SNAKE_CASE            = 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)












"""simple docstring"""


import os
import sys
from contextlib import contextmanager


# Windows only
if os.name == "nt":
       import ctypes
       import msvcrt  # noqa


       class 					snake_case		(							ctypes.Structure						):


          '''simple docstring'''

          A_						:	List[str]						 = [("size", ctypes.c_int), ("visible", ctypes.c_byte)]



def 					lowerCAmelCase				(    ):




  """simple docstring"""







  if os.name == "nt":
    __A									= CursorInfo()
    __A									= ctypes.windll.kernelaa.GetStdHandle(-1_1 )
    ctypes.windll.kernelaa.GetConsoleCursorInfo(__UpperCamelCase		,       ctypes.byref(__UpperCamelCase ) )
    __A									= False
    ctypes.windll.kernelaa.SetConsoleCursorInfo(__UpperCamelCase		,       ctypes.byref(__UpperCamelCase ) )
  elif os.name == "posix":
    sys.stdout.write('''\033[?25l''' )
    sys.stdout.flush()



def 					lowerCAmelCase				(    ):




  """simple docstring"""







  if os.name == "nt":
    __A									= CursorInfo()
    __A									= ctypes.windll.kernelaa.GetStdHandle(-1_1 )
    ctypes.windll.kernelaa.GetConsoleCursorInfo(__UpperCamelCase		,       ctypes.byref(__UpperCamelCase ) )
    __A									= True
    ctypes.windll.kernelaa.SetConsoleCursorInfo(__UpperCamelCase		,       ctypes.byref(__UpperCamelCase ) )
  elif os.name == "posix":
    sys.stdout.write('''\033[?25h''' )
    sys.stdout.flush()





@contextmanager
def 					lowerCAmelCase				(    ):




  """simple docstring"""







  try:
    hide_cursor()
    yield
  finally:
    show_cursor()




