






"""simple docstring"""


import io
import json
import unittest

from parameterized import parameterized

from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu


_UpperCamelCase    :   List[Any]   			=						get_tests_dir() + "/test_data/fsmt/fsmt_val_data.json"
with io.open(filename, 'r', encoding='utf-8') as f:
   _UpperCamelCase    :   str   			=						json.load(f)






@require_torch
class 						snake_case  (  unittest.TestCase	):





    def     lowerCamelCase__				(							self     : Optional[int]    ,		A     : Tuple      ):


      '''simple docstring'''




      return FSMTTokenizer.from_pretrained(_a      )





    def     lowerCamelCase__				(							self     : Optional[Any]    ,		A     : List[Any]      ):


      '''simple docstring'''




      a					:      Optional[Any]    =       FSMTForConditionalGeneration.from_pretrained(_a      ).to(_a      )
      if torch_device == "cuda":
        model.half()
      return model





    @parameterized.expand(
        [
            ['en-ru', 26.0],
            ['ru-en', 22.0],
            ['en-de', 22.0],
            ['de-en', 29.0],
        ]      )
    @slow
    def     lowerCamelCase__				(							self     : Dict    ,		A     : Dict    ,		A     : Optional[Any]      ):


      '''simple docstring'''




      a					:      Union[str, Any]    =       F'''facebook/wmt19-{pair}'''
      a					:      Dict    =       self.get_tokenizer(_a      )
      a					:      Any    =       self.get_model(_a      )

      a					:      Tuple    =       bleu_data[pair]["""src"""]
      a					:      Any    =       bleu_data[pair]["""tgt"""]

      a					:      Any    =       tokenizer(_a    ,		return_tensors='pt'    ,		truncation=_a    ,		padding='longest'      ).to(_a      )
      a					:      Union[str, Any]    =       model.generate(
          input_ids=batch.input_ids    ,		num_beams=8    ,		)
      a					:      List[Any]    =       tokenizer.batch_decode(
          _a    ,		skip_special_tokens=_a    ,		clean_up_tokenization_spaces=_a      )
      a					:      Dict    =       calculate_bleu(_a    ,		_a      )
      print(_a      )
      self.assertGreaterEqual(scores['bleu']    ,		_a      )












"""simple docstring"""


_UpperCamelCase    :   List[Any]   			=						8.31_44_62  # Unit - J mol-1 K-1




def       snake_case  (A_				:float     ,      A_				:float     ,      A_				:float				):







  '''simple docstring'''

  if moles < 0 or kelvin < 0 or volume < 0:
    raise ValueError('Invalid inputs. Enter positive value.'				)
  return moles * kelvin * UNIVERSAL_GAS_CONSTANT / volume




def       snake_case  (A_				:float     ,      A_				:float     ,      A_				:float				):







  '''simple docstring'''

  if moles < 0 or kelvin < 0 or pressure < 0:
    raise ValueError('Invalid inputs. Enter positive value.'				)
  return moles * kelvin * UNIVERSAL_GAS_CONSTANT / pressure


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

   testmod()




