
'''simple docstring'''



import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch

import numpy as np
import pytest
from absl.testing import parameterized

import datasets
from datasets import load_metric

from .utils import for_all_test_methods, local, slow


# mark all tests as integration
UpperCamelCase__      :		List[Any]       							=  pytest.mark.integration


UpperCamelCase__      :		Optional[Any]       							=  {"comet"}
UpperCamelCase__      :		Any       							=  importlib.util.find_spec("fairseq") is not None

UpperCamelCase__      :		Optional[Any]       							=  {"code_eval"}
UpperCamelCase__      :		List[str]       							=  os.name == "nt"

UpperCamelCase__      :		Union[str, Any]       							=  {"bertscore", "frugalscore", "perplexity"}
UpperCamelCase__      :		int       							=  importlib.util.find_spec("transformers") is not None
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     Optional[Any]:




   """simple docstring"""
   @wraps(SCREAMING_SNAKE_CASE_						)
   def wrapper(self    ,      SCREAMING_SNAKE_CASE_						):
      if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
         self.skipTest("""\"test requires Fairseq\""""						)
      else:
         test_case(self    ,      SCREAMING_SNAKE_CASE_						)

   return wrapper
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     Tuple:




   """simple docstring"""
   @wraps(SCREAMING_SNAKE_CASE_						)
   def wrapper(self    ,      SCREAMING_SNAKE_CASE_						):
      if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
         self.skipTest("""\"test requires transformers\""""						)
      else:
         test_case(self    ,      SCREAMING_SNAKE_CASE_						)

   return wrapper
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     Optional[Any]:




   """simple docstring"""
   @wraps(SCREAMING_SNAKE_CASE_						)
   def wrapper(self    ,      SCREAMING_SNAKE_CASE_						):
      if _on_windows and metric_name in UNSUPPORTED_ON_WINDOWS:
         self.skipTest("""\"test not supported on Windows\""""						)
      else:
         test_case(self    ,      SCREAMING_SNAKE_CASE_						)

   return wrapper
def    lowerCAmelCase_	(				)     ->     List[Any]:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE      =				[metric_dir.split(os.sep						)[-2] for metric_dir in glob.glob("""./metrics/*/"""						)]
   return [{"testcase_name": x, "metric_name": x} for x in metrics if x != "gleu"]  # gleu is unfinished

@parameterized.named_parameters(get_local_metric_names())
@for_all_test_methods(
    _lowerCamelCase  ,					_lowerCamelCase  ,					_lowerCamelCase)
@local
class    _a				(parameterized.TestCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE      =  {}
       SCREAMING_SNAKE_CASE      =  None






       @pytest.mark.filterwarnings("""ignore:metric_module_factory is deprecated:FutureWarning"""      )
       @pytest.mark.filterwarnings("""ignore:load_metric is deprecated:FutureWarning"""      )
       def        UpperCamelCase				(							self       ,							A__      )    ->			Dict:
          _SCREAMING_SNAKE_CASE      =				"""[...]"""
          _SCREAMING_SNAKE_CASE      =				importlib.import_module(
              datasets.load.metric_module_factory(os.path.join("""metrics"""       ,							A__      )      ).module_path      )
          _SCREAMING_SNAKE_CASE      =				datasets.load.import_main_class(metric_module.__name__       ,							dataset=A__      )
          # check parameters
          _SCREAMING_SNAKE_CASE      =				inspect.signature(metric._compute      ).parameters
          self.assertTrue(all(p.kind != p.VAR_KEYWORD for p in parameters.values()      )      )  # no **kwargs
          # run doctest
          with self.patch_intensive_calls(A__       ,							metric_module.__name__      ):
             with self.use_local_metrics():
                try:
                   _SCREAMING_SNAKE_CASE      =				doctest.testmod(A__       ,							verbose=A__       ,							raise_on_error=A__      )
                except doctest.UnexpectedException as e:
                   raise e.exc_info[1]  # raise the exception that doctest caught
          self.assertEqual(results.failed       ,							0      )
          self.assertGreater(results.attempted       ,							1      )






       @slow
       def        UpperCamelCase				(							self       ,							A__      )    ->			str:
          _SCREAMING_SNAKE_CASE      =				"""[...]"""
          _SCREAMING_SNAKE_CASE      =				importlib.import_module(
              datasets.load.metric_module_factory(os.path.join("""metrics"""       ,							A__      )      ).module_path      )
          # run doctest
          with self.use_local_metrics():
             _SCREAMING_SNAKE_CASE      =				doctest.testmod(A__       ,							verbose=A__       ,							raise_on_error=A__      )
          self.assertEqual(results.failed       ,							0      )
          self.assertGreater(results.attempted       ,							1      )






       @contextmanager
       def        UpperCamelCase				(							self       ,							A__       ,							A__      )    ->			Dict:
          if metric_name in self.INTENSIVE_CALLS_PATCHER:
             with self.INTENSIVE_CALLS_PATCHER[metric_name](A__      ):
                yield
          else:
             yield






       @contextmanager
       def        UpperCamelCase				(							self      )    ->			Any:
          def load_local_metric(A__       ,							*A__       ,							**A__      ):
             return load_metric(os.path.join("""metrics"""       ,							A__      )       ,							*A__       ,							**A__      )

          with patch("""datasets.load_metric"""      ) as mock_load_metric:
             _SCREAMING_SNAKE_CASE      =				load_local_metric
             yield






       @classmethod
       def        UpperCamelCase				(							cls       ,							A__      )    ->			List[Any]:
          def wrapper(A__      ):
             _SCREAMING_SNAKE_CASE      =				contextmanager(A__      )
             _SCREAMING_SNAKE_CASE      =				patcher
             return patcher

          return wrapper






@LocalMetricTest.register_intensive_calls_patcher("""bleurt"""						)
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     List[str]:




   """simple docstring"""
   import tensorflow.compat.va as tf
   from bleurt.score import Predictor

   tf.flags.DEFINE_string("""sv"""    ,      """"""    ,      """"""						)  # handle pytest cli flags

   class    _a				(_lowerCamelCase):





          """simple docstring"""




          def        UpperCamelCase				(							self       ,							A__      )    ->			List[str]:
             assert len(input_dict["""input_ids"""]      ) == 2
             return np.array([1.03, 1.04]      )

    # mock predict_fn which is supposed to do a forward pass with a bleurt model
   with patch("""bleurt.score._create_predictor"""						) as mock_create_predictor:
      _SCREAMING_SNAKE_CASE      =				MockedPredictor()
      yield
@LocalMetricTest.register_intensive_calls_patcher("""bertscore"""						)
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     Optional[Any]:




   """simple docstring"""
   import torch

   def bert_cos_score_idf(SCREAMING_SNAKE_CASE_    ,      SCREAMING_SNAKE_CASE_    ,      *SCREAMING_SNAKE_CASE_    ,      **SCREAMING_SNAKE_CASE_						):
      return torch.tensor([[1.0, 1.0, 1.0]] * len(SCREAMING_SNAKE_CASE_						)						)

   # mock get_model which is supposed to do download a bert model
   # mock bert_cos_score_idf which is supposed to do a forward pass with a bert model
   with patch("""bert_score.scorer.get_model"""						), patch(
       """bert_score.scorer.bert_cos_score_idf"""						) as mock_bert_cos_score_idf:
      _SCREAMING_SNAKE_CASE      =				bert_cos_score_idf
      yield
@LocalMetricTest.register_intensive_calls_patcher("""comet"""						)
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     Union[str, Any]:




   """simple docstring"""
   def load_from_checkpoint(SCREAMING_SNAKE_CASE_						):

      class    _a				:





             """simple docstring"""




             def        UpperCamelCase				(							self       ,							A__       ,							*A__       ,							**A__      )    ->			Optional[int]:
                assert len(A__      ) == 2
                _SCREAMING_SNAKE_CASE      =				[0.19, 0.92]
                return scores, sum(A__      ) / len(A__      )






      return Model()

   # mock load_from_checkpoint which is supposed to do download a bert model
   # mock load_from_checkpoint which is supposed to do download a bert model
   with patch("""comet.download_model"""						) as mock_download_model:
      _SCREAMING_SNAKE_CASE      =				None
      with patch("""comet.load_from_checkpoint"""						) as mock_load_from_checkpoint:
         _SCREAMING_SNAKE_CASE      =				load_from_checkpoint
         yield







def    lowerCAmelCase_	(				)     ->     Any:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE      =				load_metric(os.path.join("""metrics"""    ,      """seqeval"""						)						)
   _SCREAMING_SNAKE_CASE      =				"""ERROR"""
   _SCREAMING_SNAKE_CASE      =				F"Scheme should be one of [IOB1, IOB2, IOE1, IOE2, IOBES, BILOU], got {wrong_scheme}"
   with pytest.raises(SCREAMING_SNAKE_CASE_    ,      match=re.escape(SCREAMING_SNAKE_CASE_						)						):
      metric.compute(predictions=[]    ,      references=[]    ,      scheme=SCREAMING_SNAKE_CASE_						)








'''simple docstring'''



UpperCamelCase__      :		Dict       							=  {
    "a": "AAAAA",
    "b": "AAAAB",
    "c": "AAABA",
    "d": "AAABB",
    "e": "AABAA",
    "f": "AABAB",
    "g": "AABBA",
    "h": "AABBB",
    "i": "ABAAA",
    "j": "BBBAA",
    "k": "ABAAB",
    "l": "ABABA",
    "m": "ABABB",
    "n": "ABBAA",
    "o": "ABBAB",
    "p": "ABBBA",
    "q": "ABBBB",
    "r": "BAAAA",
    "s": "BAAAB",
    "t": "BAABA",
    "u": "BAABB",
    "v": "BBBAB",
    "w": "BABAA",
    "x": "BABAB",
    "y": "BABBA",
    "z": "BABBB",
    " ": " ",
}


UpperCamelCase__      :		str       							=  {value: key for key, value in encode_dict.items()}
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     str:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE      =				""""""
   for letter in word.lower():
      if letter.isalpha() or letter == " ":
         encoded += encode_dict[letter]
      else:
         raise Exception("""encode() accepts only letters of the alphabet and spaces"""						)
   return encoded
def    lowerCAmelCase_	(				SCREAMING_SNAKE_CASE_						)     ->     str:




   """simple docstring"""
   if set(SCREAMING_SNAKE_CASE_						) - {"A", "B", " "} != set():
      raise Exception("""decode() accepts only 'A', 'B' and spaces"""						)
   _SCREAMING_SNAKE_CASE      =				""""""
   for word in coded.split():
      while len(SCREAMING_SNAKE_CASE_						) != 0:
         decoded += decode_dict[word[:5]]
         _SCREAMING_SNAKE_CASE      =				word[5:]
      decoded += " "
   return decoded.strip()


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

     testmod()






