

"""simple docstring"""
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       lowerCamelCase	(       unittest.TestCase   ):


  '''simple docstring'''







  @slow
  def  _a      (self	):


        """simple docstring"""

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

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

        UpperCAmelCase__			:							Dict							=    model(_lowerCamelCase							,       labels=_lowerCamelCase	).loss
        UpperCAmelCase__			:							Dict							=    -tf.math.reduce_mean(_lowerCamelCase	).numpy()

        UpperCAmelCase__			:							Optional[int]							=    -21.228_168
        self.assertTrue(abs(mtf_score - EXPECTED_SCORE	) < 2e-4	)




"""simple docstring"""
import cmath
import math




def 					a__						(						lowerCAmelCase			,	lowerCAmelCase			,	lowerCAmelCase			,	lowerCAmelCase    )	-> complex:
      UpperCAmelCase__			:							str							=    math.radians(lowerCAmelCase    )
      UpperCAmelCase__			:							Optional[int]							=    math.radians(lowerCAmelCase    )

      # Convert voltage and current to rectangular form
      UpperCAmelCase__			:							Union[str, Any]							=    cmath.rect(lowerCAmelCase			,	lowerCAmelCase    )
      UpperCAmelCase__			:							List[str]							=    cmath.rect(lowerCAmelCase			,	lowerCAmelCase    )

      # Calculate apparent power
      return voltage_rect * current_rect


if __name__ == "__main__":
    import doctest

    doctest.testmod()

