





"""simple docstring"""






def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE							)		->       int:






       """simple docstring"""




       assert column_title.isupper()
       _UpperCAmelCase     =     0
       _UpperCAmelCase     =     len(SCREAMING_SNAKE_CASE							) - 1
       _UpperCAmelCase     =     0

       while index >= 0:
              _UpperCAmelCase     =     (ord(column_title[index]							) - 64) * pow(26,SCREAMING_SNAKE_CASE							)
              answer += value
              power += 1
              index -= 1

       return answer


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 							__A (   self     ):
              _UpperCAmelCase     =     FlaxMTaForConditionalGeneration.from_pretrained('google/mt5-small'     )
              _UpperCAmelCase     =     AutoTokenizer.from_pretrained('google/mt5-small'     )

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

              _UpperCAmelCase     =     shift_tokens_right(a__    ,  model.config.pad_token_id    ,  model.config.decoder_start_token_id     )

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

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

              _UpperCAmelCase     =     -84.9_127
              self.assertTrue(abs(mtf_score - EXPECTED_SCORE     ) < 1E-4     )






