




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       UpperCAmelCase__(							unittest.TestCase	):

   '''simple docstring'''




   @slow
   def 			UpperCAmelCase		(						self  :			Optional[Any])	->				str:




         """simple docstring"""

         lowercase__     =  FlaxMTaForConditionalGeneration.from_pretrained('google/mt5-small')
         lowercase__     =  AutoTokenizer.from_pretrained('google/mt5-small')

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

         lowercase__     =  shift_tokens_right(lowerCAmelCase			,				model.config.pad_token_id			,				model.config.decoder_start_token_id)

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

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

         lowercase__     =  -84.91_27
         self.assertTrue(abs(mtf_score - EXPECTED_SCORE) < 1E-4)





from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors

def   _lowerCAmelCase   (						A__	):
      lowercase__     =  prime_factors(A__	)
      if is_square_free(A__	):
            return -1 if len(A__	) % 2 else 1
      return 0


if __name__ == "__main__":
       import doctest

       doctest.testmod()
