


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
_lowercase       :      List[Any]	=	pytest.mark.integration


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

_lowercase       :      int	=	{"code_eval"}
_lowercase       :      int	=	os.name == "nt"

_lowercase       :      str	=	{"bertscore", "frugalscore", "perplexity"}
_lowercase       :      Any	=	importlib.util.find_spec("transformers") is not None





def   _lowerCAmelCase				(   UpperCamelCase__:     int						) ->   Optional[Any]:





 """simple docstring"""







 @wraps(UpperCamelCase__						)
 def wrapper(self:     Optional[Any]							,					UpperCamelCase__:     Any						):
  if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
   self.skipTest("""\"test requires Fairseq\""""						)
  else:
   test_case(self							,					UpperCamelCase__						)

 return wrapper





def   _lowerCAmelCase				(   UpperCamelCase__:     int						) ->   Optional[Any]:





 """simple docstring"""







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

 return wrapper





def   _lowerCAmelCase				(   UpperCamelCase__:     List[str]						) ->   int:





 """simple docstring"""







 @wraps(UpperCamelCase__						)
 def wrapper(self:     Optional[Any]							,					UpperCamelCase__:     List[Any]						):
  if _on_windows and metric_name in UNSUPPORTED_ON_WINDOWS:
   self.skipTest("""\"test not supported on Windows\""""						)
  else:
   test_case(self							,					UpperCamelCase__						)

 return wrapper





def   _lowerCAmelCase				(   ) ->   Optional[int]:





 """simple docstring"""







 A								=				[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(
    __snake_case    ,		__snake_case    ,		__snake_case				)
@local
class       _UpperCamelCase    (					parameterized.TestCase				):

    """simple docstring"""







    lowerCAmelCase 		= {}
    lowerCAmelCase 		= None

    @pytest.mark.filterwarnings("""ignore:metric_module_factory is deprecated:FutureWarning"""   )
    @pytest.mark.filterwarnings("""ignore:load_metric is deprecated:FutureWarning"""   )
    def      _UpperCAmelCase					(						self				,   a__   )	->				int:
     A								=				"""[...]"""
     A								=				importlib.import_module(
         datasets.load.metric_module_factory(os.path.join("""metrics"""				,   a__   )   ).module_path   )
     A								=				datasets.load.import_main_class(metric_module.__name__				,   dataset=a__   )
     # check parameters
     A								=				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:
        A								=				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__   )	->				int:
     A								=				"""[...]"""
     A								=				importlib.import_module(
         datasets.load.metric_module_factory(os.path.join("""metrics"""				,   a__   )   ).module_path   )
     # run doctest
     with self.use_local_metrics():
      A								=				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__   )	->				Any:
     if metric_name in self.INTENSIVE_CALLS_PATCHER:
      with self.INTENSIVE_CALLS_PATCHER[metric_name](a__   ):
       yield
     else:
      yield

    @contextmanager
    def      _UpperCAmelCase					(						self   )	->				int:
     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:
      A								=				load_local_metric
      yield

    @classmethod
    def      _UpperCAmelCase					(						cls				,   a__   )	->				Optional[int]:
     def wrapper(a__   ):
      A								=				contextmanager(a__   )
      A								=				patcher
      return patcher

     return wrapper





@LocalMetricTest.register_intensive_calls_patcher("""bleurt"""						)
def   _lowerCAmelCase				(   UpperCamelCase__:     Any						) ->   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       _UpperCamelCase    (					__snake_case				):

     """simple docstring"""







     def      _UpperCAmelCase					(						self				,   a__   )	->				Any:
      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:
  A								=				MockedPredictor()
  yield





@LocalMetricTest.register_intensive_calls_patcher("""bertscore"""						)
def   _lowerCAmelCase				(   UpperCamelCase__:     Dict						) ->   List[Any]:





 """simple docstring"""







 import torch

 def bert_cos_score_idf(UpperCamelCase__:     List[Any]							,					UpperCamelCase__:     Optional[Any]							,					*UpperCamelCase__:     Optional[Any]							,					**UpperCamelCase__:     Tuple						):
  return torch.tensor([[1.0, 1.0, 1.0]] * len(UpperCamelCase__						)						)

 # 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:
  A								=				bert_cos_score_idf
  yield





@LocalMetricTest.register_intensive_calls_patcher("""comet"""						)
def   _lowerCAmelCase				(   UpperCamelCase__:     Any						) ->   Any:





 """simple docstring"""







 def load_from_checkpoint(UpperCamelCase__:     Any						):






  class       _UpperCamelCase    :

      """simple docstring"""







      def      _UpperCAmelCase					(						self				,   a__				,   *a__				,   **a__   )	->				Any:
       assert len(a__   ) == 2
       A								=				[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:
  A								=				None
  with patch("""comet.load_from_checkpoint"""						) as mock_load_from_checkpoint:
   A								=				load_from_checkpoint
   yield





def   _lowerCAmelCase				(   ) ->   Optional[int]:





 """simple docstring"""







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







from __future__ import annotations

import requests





def   _lowerCAmelCase				(   UpperCamelCase__:     str						) ->   dict:





	"""simple docstring"""







	A								=				f'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
	return requests.get(UpperCamelCase__						).json()





def   _lowerCAmelCase				(   UpperCamelCase__:     int = 10						) ->   list[dict]:





	"""simple docstring"""







	A								=				"""https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty"""
	A								=				requests.get(UpperCamelCase__						).json()[:max_stories]
	return [get_hackernews_story(UpperCamelCase__						) for story_id in story_ids]





def   _lowerCAmelCase				(   UpperCamelCase__:     int = 10						) ->   str:





	"""simple docstring"""







	A								=				hackernews_top_stories(UpperCamelCase__						)
	return "\n".join("""* [{title}]({url})""".format(**UpperCamelCase__						) for story in stories						)


if __name__ == "__main__":
				print(hackernews_top_stories_as_markdown())



