





'''simple docstring'''

import unittest

from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow


if is_flax_available():
   import optax
   from flax.training.common_utils import onehot

   from transformers import AutoTokenizer, FlaxMTaForConditionalGeneration
   from transformers.models.ta.modeling_flax_ta import shift_tokens_right





@require_torch
@require_sentencepiece
@require_tokenizers
@require_flax
class lowerCamelCase						(unittest.TestCase					):







  @slow
  def 				UpperCAmelCase_				(		self		)		->						int:






        """simple docstring"""





        _snake_case		:	Tuple					     =     FlaxMTaForConditionalGeneration.from_pretrained('''google/mt5-small'''		)
        _snake_case		:	Any					     =     AutoTokenizer.from_pretrained('''google/mt5-small'''		)

        _snake_case		:	List[str]					     =     tokenizer('''Hello there'''     ,     return_tensors='''np'''		).input_ids
        _snake_case		:	Dict					     =     tokenizer('''Hi I am'''     ,     return_tensors='''np'''		).input_ids

        _snake_case		:	Any					     =     shift_tokens_right(lowercase__     ,     model.config.pad_token_id     ,     model.config.decoder_start_token_id		)

        _snake_case		:	Any					     =     model(lowercase__     ,     decoder_input_ids=lowercase__		).logits
        _snake_case		:	Tuple					     =     optax.softmax_cross_entropy(lowercase__     ,     onehot(lowercase__     ,     logits.shape[-1]		)		).mean()

        _snake_case		:	Tuple					     =     -(labels.shape[-1] * loss.item())

        _snake_case		:	Union[str, Any]					     =     -84.9_127
        self.assertTrue(abs(mtf_score - EXPECTED_SCORE		) < 1E-4		)









'''simple docstring'''

from __future__ import annotations




def    _a    (							lowerCAmelCase_			,      lowerCAmelCase_ = None			,      lowerCAmelCase_ = None	):





      """simple docstring"""



      if start is None:
            _snake_case		:	Optional[Any]					     =     0

      if end is None:
            _snake_case		:	Any					     =     len(lowerCAmelCase_	) - 1

      if start >= end:
            return

      _snake_case		:	Optional[Any]					     =     (start + end) // 2

      slowsort(lowerCAmelCase_			,      lowerCAmelCase_			,      lowerCAmelCase_	)
      slowsort(lowerCAmelCase_			,      mid + 1			,      lowerCAmelCase_	)

      if sequence[end] < sequence[mid]:
            _snake_case     ,							_snake_case		:	int					     =     sequence[mid], sequence[end]

      slowsort(lowerCAmelCase_			,      lowerCAmelCase_			,      end - 1	)


if __name__ == "__main__":
   from doctest import testmod

   testmod()


