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       UpperCamelCase__       (     self)	->     List[Any]:
        __UpperCamelCase					:Optional[int]        =		'''hf-internal-testing/tiny-random-t5'''
        __UpperCamelCase					:Any        =		AutoTokenizer.from_pretrained(__lowercase)
        __UpperCamelCase					:Union[str, Any]        =		AutoModelForSeqaSeqLM.from_pretrained(__lowercase)

        __UpperCamelCase					:List[Any]        =		tokenizer('''This is me'''			,			return_tensors='''pt''')

        __UpperCamelCase					:Union[str, Any]        =		model.to_bettertransformer()

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

        __UpperCamelCase					:List[Any]        =		model.generate(**__lowercase)

        __UpperCamelCase					:List[Any]        =		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(__lowercase)

            __UpperCamelCase					:Tuple        =		AutoModelForSeqaSeqLM.from_pretrained(__lowercase)

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

            __UpperCamelCase					:int        =		model_reloaded.generate(**__lowercase)
            self.assertTrue(torch.allclose(__lowercase			,			__lowercase))







    def       UpperCamelCase__       (     self)	->     List[Any]:
        __UpperCamelCase					:int        =		'''hf-internal-testing/tiny-random-t5'''
        __UpperCamelCase					:Optional[Any]        =		AutoModelForSeqaSeqLM.from_pretrained(__lowercase)

        __UpperCamelCase					:Dict        =		model.to_bettertransformer()

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

            __UpperCamelCase					:int        =		model.reverse_bettertransformer()
            model.save_pretrained(__lowercase)






def lowerCamelCase  (       SCREAMING_SNAKE_CASE     ):
    '''simple docstring'''







    if not grid or not grid[0]:
        raise TypeError('''The grid does not contain the appropriate information'''     )

    for cell_n in range(1  ,      len(grid[0]     )     ):
        grid[0][cell_n] += grid[0][cell_n - 1]
    __UpperCamelCase					:Union[str, Any]        =		grid[0]

    for row_n in range(1  ,      len(SCREAMING_SNAKE_CASE     )     ):
        __UpperCamelCase					:Optional[int]        =		grid[row_n]
        __UpperCamelCase					:Dict        =		fill_row(SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     )
        __UpperCamelCase					:Any        =		grid[row_n]

    return grid[-1][-1]



def lowerCamelCase  (       SCREAMING_SNAKE_CASE  ,      SCREAMING_SNAKE_CASE     ):
    '''simple docstring'''







    current_row[0] += row_above[0]
    for cell_n in range(1  ,      len(SCREAMING_SNAKE_CASE     )     ):
        current_row[cell_n] += min(current_row[cell_n - 1]  ,      row_above[cell_n]     )

    return current_row


if __name__ == "__main__":
    import doctest

    doctest.testmod()





