

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







@require_torch
class        a__       (   unittest.TestCase       ):







  """simple docstring"""




  def  _lowercase      (			self    : Optional[int]				,				UpperCAmelCase__    : Any		)					->List[Any]:
        """simple docstring"""







        return FSMTTokenizer.from_pretrained(_lowercase		)


  def  _lowercase      (			self    : Tuple				,				UpperCAmelCase__    : Optional[Any]		)					->str:
        """simple docstring"""







        SCREAMING_SNAKE_CASE :      int       =   FSMTForConditionalGeneration.from_pretrained(_lowercase		).to(_lowercase		)
        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  _lowercase      (			self    : Any				,				UpperCAmelCase__    : List[Any]				,				UpperCAmelCase__    : Dict		)					->Dict:
        """simple docstring"""







        SCREAMING_SNAKE_CASE :      List[Any]       =   f"facebook/wmt19-{pair}"
        SCREAMING_SNAKE_CASE :      Optional[Any]       =   self.get_tokenizer(_lowercase		)
        SCREAMING_SNAKE_CASE :      int       =   self.get_model(_lowercase		)

        SCREAMING_SNAKE_CASE :      Optional[int]       =   bleu_data[pair]["""src"""]
        SCREAMING_SNAKE_CASE :      Optional[Any]       =   bleu_data[pair]["""tgt"""]

        SCREAMING_SNAKE_CASE :      Dict       =   tokenizer(_lowercase				,				return_tensors="""pt"""				,				truncation=_lowercase				,				padding="""longest"""		).to(_lowercase		)
        SCREAMING_SNAKE_CASE :      List[str]       =   model.generate(
            input_ids=batch.input_ids				,				num_beams=8				,				)
        SCREAMING_SNAKE_CASE :      Optional[Any]       =   tokenizer.batch_decode(
            _lowercase				,				skip_special_tokens=_lowercase				,				clean_up_tokenization_spaces=_lowercase		)
        SCREAMING_SNAKE_CASE :      Optional[int]       =   calculate_bleu(_lowercase				,				_lowercase		)
        print(_lowercase		)
        self.assertGreaterEqual(scores["""bleu"""]				,				_lowercase		)







def 					__lowercase      (     _A			)     ->						list[int]:
      SCREAMING_SNAKE_CASE :      int       =   [0 for i in range(len(_A			)			)]

      # initialize interval's left pointer and right pointer
      SCREAMING_SNAKE_CASE     ,	SCREAMING_SNAKE_CASE :      Dict       =   0, 0

      for i in range(1						,    len(_A			)			):
            # case when current index is inside the interval
            if i <= right_pointer:
                  SCREAMING_SNAKE_CASE :      Any       =   min(right_pointer - i + 1						,    z_result[i - left_pointer]			)
                  SCREAMING_SNAKE_CASE :      Optional[Any]       =   min_edge

            while go_next(_A						,    _A						,    _A			):
                  z_result[i] += 1

            # if new index's result gives us more right interval,
            # we've to update left_pointer and right_pointer
            if i + z_result[i] - 1 > right_pointer:
                  SCREAMING_SNAKE_CASE     ,	SCREAMING_SNAKE_CASE :      List[Any]       =   i, i + z_result[i] - 1

      return z_result






def 					__lowercase      (     _A						,    _A						,    _A			)     ->						bool:
      return i + z_result[i] < len(_A			) and s[z_result[i]] == s[i + z_result[i]]






def 					__lowercase      (     _A						,    _A			)     ->						int:
      SCREAMING_SNAKE_CASE :      Any       =   0
      # concatenate 'pattern' and 'input_str' and call z_function
      # with concatenated string
      SCREAMING_SNAKE_CASE :      List[Any]       =   z_function(pattern + input_str			)

      for val in z_result:
            # if value is greater then length of the pattern string
            # that means this index is starting position of substring
            # which is equal to pattern string
            if val >= len(_A			):
                  answer += 1

      return answer


if __name__ == "__main__":
  import doctest

  doctest.testmod()




