"""simple docstring"""





from __future__ import annotations



def   lowerCamelCase_(__SCREAMING_SNAKE_CASE  ,						__SCREAMING_SNAKE_CASE = None  ,						__SCREAMING_SNAKE_CASE = None	)->     Dict:
							if start is None:
														_SCREAMING_SNAKE_CASE		:    str      	=     0

							if end is None:
														_SCREAMING_SNAKE_CASE		:    Optional[int]      	=     len(lowerCAmelCase__	) - 1

							if start >= end:
														return

							_SCREAMING_SNAKE_CASE		:    List[str]      	=     (start + end) // 2

							slowsort(lowerCAmelCase__  ,						lowerCAmelCase__  ,						lowerCAmelCase__	)
							slowsort(lowerCAmelCase__  ,						mid + 1  ,						lowerCAmelCase__	)

							if sequence[end] < sequence[mid]:
														_SCREAMING_SNAKE_CASE	,					_SCREAMING_SNAKE_CASE		:    Union[str, Any]      	=     sequence[mid], sequence[end]

							slowsort(lowerCAmelCase__  ,						lowerCAmelCase__  ,						end - 1	)


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

			testmod()




"""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   ):
							lowerCamelCase_					=  FlaxMTaForConditionalGeneration.from_pretrained('''google/mt5-small'''   )
							lowerCamelCase_					=  AutoTokenizer.from_pretrained('''google/mt5-small'''   )

							lowerCamelCase_					=  tokenizer('''Hello there'''							,						return_tensors='''np'''   ).input_ids
							lowerCamelCase_					=  tokenizer('''Hi I am'''							,						return_tensors='''np'''   ).input_ids

							lowerCamelCase_					=  shift_tokens_right(UpperCAmelCase							,						model.config.pad_token_id							,						model.config.decoder_start_token_id   )

							lowerCamelCase_					=  model(UpperCAmelCase							,						decoder_input_ids=UpperCAmelCase   ).logits
							lowerCamelCase_					=  optax.softmax_cross_entropy(UpperCAmelCase							,						onehot(UpperCAmelCase							,						logits.shape[-1]   )   ).mean()

							lowerCamelCase_					=  -(labels.shape[-1] * loss.item())

							lowerCamelCase_					=  -8_4.9_1_2_7
							self.assertTrue(abs(mtf_score - EXPECTED_SCORE   ) < 1e-4   )



