


import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
 import torch


@require_torch
@require_optimum
@slow
class  lowerCAmelCase_						(       unittest.TestCase      ):





  """simple docstring"""



  def __a						(					self     :							List[str]						):





       '''simple docstring'''

       __a       =   """hf-internal-testing/tiny-random-t5"""
       __a       =   AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE__						)
       __a       =   AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE__						)

       __a       =   tokenizer("""This is me"""				,							return_tensors="""pt"""						)

       __a       =   model.to_bettertransformer()

       self.assertTrue(any("""BetterTransformer""" in mod.__class__.__name__ for _, mod in model.named_modules()						)						)

       __a       =   model.generate(**SCREAMING_SNAKE_CASE__						)

       __a       =   model.reverse_bettertransformer()

       self.assertFalse(any("""BetterTransformer""" in mod.__class__.__name__ for _, mod in model.named_modules()						)						)

       with tempfile.TemporaryDirectory() as tmpdirname:
            model.save_pretrained(SCREAMING_SNAKE_CASE__						)

            __a       =   AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE__						)

            self.assertFalse(
                any("""BetterTransformer""" in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()						)						)

            __a       =   model_reloaded.generate(**SCREAMING_SNAKE_CASE__						)
            self.assertTrue(torch.allclose(SCREAMING_SNAKE_CASE__				,							SCREAMING_SNAKE_CASE__						)						)


  def __a						(					self     :							Union[str, Any]						):





       '''simple docstring'''

       __a       =   """hf-internal-testing/tiny-random-t5"""
       __a       =   AutoModelForSeqaSeqLM.from_pretrained(SCREAMING_SNAKE_CASE__						)

       __a       =   model.to_bettertransformer()

       with tempfile.TemporaryDirectory() as tmpdirname:
            with self.assertRaises(SCREAMING_SNAKE_CASE__						):
                 model.save_pretrained(SCREAMING_SNAKE_CASE__						)

            __a       =   model.reverse_bettertransformer()
            model.save_pretrained(SCREAMING_SNAKE_CASE__						)










'''simple docstring'''







import enum
import shutil
import sys


SCREAMING_SNAKE_CASE_      ,     SCREAMING_SNAKE_CASE_      =			shutil.get_terminal_size()

SCREAMING_SNAKE_CASE_      =			{'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}


class  lowerCAmelCase_						(       enum.Enum      ):





  """simple docstring"""



  a_       :List[Any]												=0
  a_       :Optional[Any]												=1




def        __lowercase						(      __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE=""		)				->					List[Any]:
     """simple docstring"""




     sys.stdout.write(str(__SCREAMING_SNAKE_CASE		) + end		)
     sys.stdout.flush()




def        __lowercase						(      __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE=""		)				->					Tuple:
     """simple docstring"""




     forceWrite(F'''\u001b[{color}m{content}\u001b[0m'''				,  __SCREAMING_SNAKE_CASE		)




def        __lowercase						(      )				->					Union[str, Any]:
     """simple docstring"""




     forceWrite("""\r"""		)




def        __lowercase						(      __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE		)				->					str:
     """simple docstring"""




     forceWrite(F'''\033[{num_lines}{CURSOR_TO_CHAR[direction.upper()]}'''		)




def        __lowercase						(      )				->					int:
     """simple docstring"""




     forceWrite(""" """ * TERMINAL_WIDTH		)
     reset_cursor()




def        __lowercase						(      )				->					str:
     """simple docstring"""




     reset_cursor()
     forceWrite("""-""" * TERMINAL_WIDTH		)






