


"""simple docstring"""
from __future__ import annotations

def 				_snake_case      (   __snake_case							:      list[int]						, __snake_case							:      int						, __snake_case							:      int						, __snake_case							:      int   ):




   """simple docstring"""







   if (direction == 1 and array[indexa] > array[indexa]) or (
       direction == 0 and array[indexa] < array[indexa]
   ):
      _lowerCamelCase   ,    _lowerCamelCase	:					List[Any]   =		array[indexa], array[indexa]

def 				_snake_case      (   __snake_case							:      list[int]						, __snake_case							:      int						, __snake_case							:      int						, __snake_case							:      int   ):




   """simple docstring"""







   if length > 1:
      _lowerCamelCase	:					List[str]   =		int(length / 2   )
      for i in range(__snake_case						, low + middle   ):
         comp_and_swap(__snake_case						, __snake_case						, i + middle						, __snake_case   )
      bitonic_merge(__snake_case						, __snake_case						, __snake_case						, __snake_case   )
      bitonic_merge(__snake_case						, low + middle						, __snake_case						, __snake_case   )

def 				_snake_case      (   __snake_case							:      list[int]						, __snake_case							:      int						, __snake_case							:      int						, __snake_case							:      int   ):




   """simple docstring"""







   if length > 1:
      _lowerCamelCase	:					List[str]   =		int(length / 2   )
      bitonic_sort(__snake_case						, __snake_case						, __snake_case						, 1   )
      bitonic_sort(__snake_case						, low + middle						, __snake_case						, 0   )
      bitonic_merge(__snake_case						, __snake_case						, __snake_case						, __snake_case   )


if __name__ == "__main__":
 UpperCAmelCase				=						input("""Enter numbers separated by a comma:\n""").strip()
 UpperCAmelCase				=						[int(item.strip()) for item in user_input.split(""",""")]

 bitonic_sort(unsorted, 0, len(unsorted), 1)
 print("""\nSorted array in ascending order is: """, end="""""")
 print(*unsorted, sep=""", """)

 bitonic_merge(unsorted, 0, len(unsorted), 0)
 print("""Sorted array in descending order is: """, end="""""")
 print(*unsorted, sep=""", """)









"""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       __a							(		self      :	List[str]							):


        '''simple docstring'''
        UpperCAmelCase__						:    Union[str, Any]							=							FlaxMTaForConditionalGeneration.from_pretrained("google/mt5-small"							)
        UpperCAmelCase__						:    str							=							AutoTokenizer.from_pretrained("google/mt5-small"							)

        UpperCAmelCase__						:    str							=							tokenizer("Hello there"							,			return_tensors="np"							).input_ids
        UpperCAmelCase__						:    Optional[Any]							=							tokenizer("Hi I am"							,			return_tensors="np"							).input_ids

        UpperCAmelCase__						:    Any							=							shift_tokens_right(snake_case__							,			model.config.pad_token_id							,			model.config.decoder_start_token_id							)

        UpperCAmelCase__						:    Any							=							model(snake_case__							,			decoder_input_ids=snake_case__							).logits
        UpperCAmelCase__						:    Any							=							optax.softmax_cross_entropy(snake_case__							,			onehot(snake_case__							,			logits.shape[-1]							)							).mean()

        UpperCAmelCase__						:    List[str]							=							-(labels.shape[-1] * loss.item())

        UpperCAmelCase__						:    Dict							=							-84.9127
        self.assertTrue(abs(mtf_score - EXPECTED_SCORE							) < 1e-4							)


