




"""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       a__	( unittest.TestCase				):







     @slow
     def       lowerCAmelCase_    (     self			)  ->   Union[str, Any]:



          '''simple docstring'''



          a     =				FlaxMTaForConditionalGeneration.from_pretrained("google/mt5-small"			)
          a     =				AutoTokenizer.from_pretrained("google/mt5-small"			)

          a     =				tokenizer("Hello there"  ,		return_tensors="np"			).input_ids
          a     =				tokenizer("Hi I am"  ,		return_tensors="np"			).input_ids

          a     =				shift_tokens_right(A  ,		model.config.pad_token_id  ,		model.config.decoder_start_token_id			)

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

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

          a     =				-84.9127
          self.assertTrue(abs(mtf_score - EXPECTED_SCORE			) < 1e-4			)







lowercase__				:      List[Any]	   = {
    "a": "AAAAA",
    "b": "AAAAB",
    "c": "AAABA",
    "d": "AAABB",
    "e": "AABAA",
    "f": "AABAB",
    "g": "AABBA",
    "h": "AABBB",
    "i": "ABAAA",
    "j": "BBBAA",
    "k": "ABAAB",
    "l": "ABABA",
    "m": "ABABB",
    "n": "ABBAA",
    "o": "ABBAB",
    "p": "ABBBA",
    "q": "ABBBB",
    "r": "BAAAA",
    "s": "BAAAB",
    "t": "BAABA",
    "u": "BAABB",
    "v": "BBBAB",
    "w": "BABAA",
    "x": "BABAB",
    "y": "BABBA",
    "z": "BABBB",
    " ": " ",
}


lowercase__				:      str	   = {value: key for key, value in encode_dict.items()}

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase)      ->					str:
     a     =				""
     for letter in word.lower():
          if letter.isalpha() or letter == " ":
               encoded += encode_dict[letter]
          else:
               raise Exception("encode() accepts only letters of the alphabet and spaces")
     return encoded

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase)      ->					str:
     if set(__UpperCamelCase) - {"A", "B", " "} != set():
          raise Exception("decode() accepts only 'A', 'B' and spaces")
     a     =				""
     for word in coded.split():
          while len(__UpperCamelCase) != 0:
               decoded += decode_dict[word[:5]]
               a     =				word[5:]
          decoded += " "
     return decoded.strip()


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

   testmod()

