





__lowerCamelCase	:					Optional[int]			  =					"""Tobias Carryer"""

from time import time



class  A__       :





      def __init__(			self	,							A_	,							A_	,							A_	,							A_=int(time()       )       ):  # noqa: B008
       '''simple docstring'''




       UpperCamelCase     : int	     =       multiplier
       UpperCamelCase     : Tuple	     =       increment
       UpperCamelCase     : List[str]	     =       modulo
       UpperCamelCase     : Tuple	     =       seed





      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : Tuple	     =       (self.multiplier * self.seed + self.increment) % self.modulo
       return self.seed


if __name__ == "__main__":
    # Show the LCG in action.
    __lowerCamelCase	:					List[str]			  =					LinearCongruentialGenerator(166_4525, 10_1390_4223, 2 << 31)
    while True:
        print(lcg.next_number())







from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
    import tensorflow as tf

    from transformers import AutoTokenizer, TFAutoModelForSeqaSeqLM



@require_tf
@require_sentencepiece
@require_tokenizers
class  A__       (	unittest.TestCase      ):





      @slow
      def 	__UpperCamelCase(			self       ):
       '''simple docstring'''




       UpperCamelCase     : List[str]	     =       TFAutoModelForSeqaSeqLM.from_pretrained("google/mt5-small"       )
       UpperCamelCase     : Tuple	     =       AutoTokenizer.from_pretrained("google/mt5-small"       )

       UpperCamelCase     : Dict	     =       tokenizer("Hello there"	,							return_tensors="tf"       ).input_ids
       UpperCamelCase     : int	     =       tokenizer("Hi I am"	,							return_tensors="tf"       ).input_ids

       UpperCamelCase     : Union[str, Any]	     =       model(A_	,							labels=A_       ).loss
       UpperCamelCase     : List[str]	     =       -tf.math.reduce_mean(A_       ).numpy()

       UpperCamelCase     : Union[str, Any]	     =       -21.22_81_68
       self.assertTrue(abs(mtf_score - EXPECTED_SCORE       ) < 2e-4       )
