

'''simple docstring'''







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    A__ ( unittest.TestCase     ):



    def    snake_case_     (   self    )  -> List[Any]:





           '''simple docstring'''
           A_		   = """hf-internal-testing/tiny-random-t5"""
           A_		   = AutoTokenizer.from_pretrained(UpperCamelCase__    )
           A_		   = AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__    )

           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(**UpperCamelCase__    )

           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(UpperCamelCase__    )

                  A_		   = AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__    )

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

                  A_		   = model_reloaded.generate(**UpperCamelCase__    )
                  self.assertTrue(torch.allclose(UpperCamelCase__						,			UpperCamelCase__    )    )







    def    snake_case_     (   self    )  -> Dict:





           '''simple docstring'''
           A_		   = """hf-internal-testing/tiny-random-t5"""
           A_		   = AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__    )

           A_		   = model.to_bettertransformer()

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

                  A_		   = model.reverse_bettertransformer()
                  model.save_pretrained(UpperCamelCase__    )



'''simple docstring'''







from __future__ import annotations

from typing import Any
def  UpperCAmelCase__      ( UpperCAmelCase__			)     ->     int:
       if not postfix_notation:
              return 0

       A_		   = {"""+""", """-""", """*""", """/"""}
       A_		   = []

       for token in postfix_notation:
              if token in operations:
                     A_   ,     A_		   = stack.pop(), stack.pop()
                     if token == "+":
                            stack.append(a + b			)
                     elif token == "-":
                            stack.append(a - b			)
                     elif token == "*":
                            stack.append(a * b			)
                     else:
                            if a * b < 0 and a % b != 0:
                                   stack.append(a // b + 1			)
                            else:
                                   stack.append(a // b			)
              else:
                     stack.append(int(UpperCAmelCase__			)			)

       return stack.pop()


if __name__ == "__main__":
      import doctest

      doctest.testmod()
