






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
A_						:						Union[str, Any]						      =					pytest.mark.integration


A_						:						Any						      =					{'comet'}
A_						:						Tuple						      =					importlib.util.find_spec('fairseq') is not None

A_						:						List[Any]						      =					{'code_eval'}
A_						:						Union[str, Any]						      =					os.name == 'nt'

A_						:						Union[str, Any]						      =					{'bertscore', 'frugalscore', 'perplexity'}
A_						:						List[str]						      =					importlib.util.find_spec('transformers') is not None

def     snake_case   (UpperCAmelCase__    )			->							Tuple:
  @wraps(UpperCAmelCase__    )
  def wrapper(self      ,       UpperCAmelCase__    ):
    if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
      self.skipTest('"test requires Fairseq"'    )
    else:
      test_case(self      ,       UpperCAmelCase__    )

  return wrapper

def     snake_case   (UpperCAmelCase__    )			->							Any:
  @wraps(UpperCAmelCase__    )
  def wrapper(self      ,       UpperCAmelCase__    ):
    if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
      self.skipTest('"test requires transformers"'    )
    else:
      test_case(self      ,       UpperCAmelCase__    )

  return wrapper

def     snake_case   (UpperCAmelCase__    )			->							Optional[int]:
  @wraps(UpperCAmelCase__    )
  def wrapper(self      ,       UpperCAmelCase__    ):
    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     snake_case   ()			->							List[Any]:
  UpperCamelCase_:   Optional[int]        =							[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(
    UpperCAmelCase_				,      UpperCAmelCase_				,      UpperCAmelCase_   )
@local
class 							_lowerCAmelCase(			parameterized.TestCase   ):





       """simple docstring"""







       a							:						Tuple										={}
       a							:						str										=None





       @pytest.mark.filterwarnings('ignore:metric_module_factory is deprecated:FutureWarning'				)
       @pytest.mark.filterwarnings('ignore:load_metric is deprecated:FutureWarning'				)
       def      _a       (   self    ,     _lowerCamelCase				):
         UpperCamelCase_:   Any        =							'[...]'
         UpperCamelCase_:   int        =							importlib.import_module(
             datasets.load.metric_module_factory(os.path.join('metrics'    ,     _lowerCamelCase				)				).module_path				)
         UpperCamelCase_:   List[Any]        =							datasets.load.import_main_class(metric_module.__name__    ,     dataset=_lowerCamelCase				)
         # check parameters
         UpperCamelCase_:   Optional[Any]        =							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(_lowerCamelCase    ,     metric_module.__name__				):
           with self.use_local_metrics():
             try:
               UpperCamelCase_:   Union[str, Any]        =							doctest.testmod(_lowerCamelCase    ,     verbose=_lowerCamelCase    ,     raise_on_error=_lowerCamelCase				)
             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      _a       (   self    ,     _lowerCamelCase				):
         UpperCamelCase_:   Optional[Any]        =							'[...]'
         UpperCamelCase_:   Optional[int]        =							importlib.import_module(
             datasets.load.metric_module_factory(os.path.join('metrics'    ,     _lowerCamelCase				)				).module_path				)
         # run doctest
         with self.use_local_metrics():
           UpperCamelCase_:   Union[str, Any]        =							doctest.testmod(_lowerCamelCase    ,     verbose=_lowerCamelCase    ,     raise_on_error=_lowerCamelCase				)
         self.assertEqual(results.failed    ,     0				)
         self.assertGreater(results.attempted    ,     1				)





       @contextmanager
       def      _a       (   self    ,     _lowerCamelCase    ,     _lowerCamelCase				):
         if metric_name in self.INTENSIVE_CALLS_PATCHER:
           with self.INTENSIVE_CALLS_PATCHER[metric_name](_lowerCamelCase				):
             yield
         else:
           yield





       @contextmanager
       def      _a       (   self				):
         def load_local_metric(_lowerCamelCase    ,     *_lowerCamelCase    ,     **_lowerCamelCase				):
           return load_metric(os.path.join('metrics'    ,     _lowerCamelCase				)    ,     *_lowerCamelCase    ,     **_lowerCamelCase				)

         with patch('datasets.load_metric'				) as mock_load_metric:
           UpperCamelCase_:   List[Any]        =							load_local_metric
           yield





       @classmethod
       def      _a       (   cls    ,     _lowerCamelCase				):
         def wrapper(_lowerCamelCase				):
           UpperCamelCase_:   Optional[Any]        =							contextmanager(_lowerCamelCase				)
           UpperCamelCase_:   int        =							patcher
           return patcher

         return wrapper







@LocalMetricTest.register_intensive_calls_patcher('bleurt'    )
def     snake_case   (UpperCAmelCase__    )			->							Dict:
  import tensorflow.compat.va as tf
  from bleurt.score import Predictor

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




  class 							_lowerCAmelCase(			UpperCAmelCase_   ):





         """simple docstring"""







         def      _a       (   self    ,     _lowerCamelCase				):
           assert len(input_dict['input_ids']				) == 2
           return np.array([1.0_3, 1.0_4]				)

    # 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:
    UpperCamelCase_:   Dict        =							MockedPredictor()
    yield

@LocalMetricTest.register_intensive_calls_patcher('bertscore'    )
def     snake_case   (UpperCAmelCase__    )			->							Optional[Any]:
  import torch

  def bert_cos_score_idf(UpperCAmelCase__      ,       UpperCAmelCase__      ,       *UpperCAmelCase__      ,       **UpperCAmelCase__    ):
    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:
    UpperCamelCase_:   Dict        =							bert_cos_score_idf
    yield

@LocalMetricTest.register_intensive_calls_patcher('comet'    )
def     snake_case   (UpperCAmelCase__    )			->							List[str]:
  def load_from_checkpoint(UpperCAmelCase__    ):




    class 							_lowerCAmelCase:





           """simple docstring"""







           def      _a       (   self    ,     _lowerCamelCase    ,     *_lowerCamelCase    ,     **_lowerCamelCase				):
             assert len(_lowerCamelCase				) == 2
             UpperCamelCase_:   List[Any]        =							[0.1_9, 0.9_2]
             return scores, sum(_lowerCamelCase				) / len(_lowerCamelCase				)







    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:
    UpperCamelCase_:   Union[str, Any]        =							None
    with patch('comet.load_from_checkpoint'    ) as mock_load_from_checkpoint:
      UpperCamelCase_:   int        =							load_from_checkpoint
      yield

def     snake_case   ()			->							str:
  UpperCamelCase_:   Union[str, Any]        =							load_metric(os.path.join('metrics'      ,       'seqeval'    )    )
  UpperCamelCase_:   Any        =							'ERROR'
  UpperCamelCase_:   List[Any]        =							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

from typing import TypedDict





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 lowercase_							       =       42
 lowercase_							       =       42


def    UpperCAmelCase_				( __UpperCAmelCase		:      str				)   ->					list[str]:
      if not isinstance(__UpperCAmelCase     ,     __UpperCAmelCase				):
            raise TypeError('The parameter s type must be str.'				)

      return [s[i:] + s[:i] for i in range(len(__UpperCAmelCase				)				)]

def    UpperCAmelCase_				( __UpperCAmelCase		:      str				)   ->					BWTTransformDict:
      if not isinstance(__UpperCAmelCase     ,     __UpperCAmelCase				):
            raise TypeError('The parameter s type must be str.'				)
      if not s:
            raise ValueError('The parameter s must not be empty.'				)

      SCREAMING_SNAKE_CASE_      		=     all_rotations(__UpperCAmelCase				)
      rotations.sort()  # sort the list of rotations in alphabetically order
      # make a string composed of the last char of each rotation
      SCREAMING_SNAKE_CASE_      		=     {
          "bwt_string": "".join([word[-1] for word in rotations]				),
          "idx_original_string": rotations.index(__UpperCAmelCase				),
      }
      return response

def    UpperCAmelCase_				( __UpperCAmelCase		:      str     ,     __UpperCAmelCase		:      int				)   ->					str:
      if not isinstance(__UpperCAmelCase     ,     __UpperCAmelCase				):
            raise TypeError('The parameter bwt_string type must be str.'				)
      if not bwt_string:
            raise ValueError('The parameter bwt_string must not be empty.'				)
      try:
            SCREAMING_SNAKE_CASE_      		=     int(__UpperCAmelCase				)
      except ValueError:
            raise TypeError(
                'The parameter idx_original_string type must be int or passive'
                ' of cast to int.'				)
      if idx_original_string < 0:
            raise ValueError('The parameter idx_original_string must not be lower than 0.'				)
      if idx_original_string >= len(__UpperCAmelCase				):
            raise ValueError(
                'The parameter idx_original_string must be lower than' ' len(bwt_string).'				)

      SCREAMING_SNAKE_CASE_      		=     [''] * len(__UpperCAmelCase				)
      for _ in range(len(__UpperCAmelCase				)				):
            for i in range(len(__UpperCAmelCase				)				):
                  SCREAMING_SNAKE_CASE_      		=     bwt_string[i] + ordered_rotations[i]
            ordered_rotations.sort()
      return ordered_rotations[idx_original_string]


if __name__ == "__main__":
   lowerCamelCase__					:  Optional[int]      							=				'Provide a string that I will generate its BWT transform: '
   lowerCamelCase__					:  List[str]      							=				input(entry_msg).strip()
   lowerCamelCase__					:  int      							=				bwt_transform(s)
   print(
       f'''Burrows Wheeler transform for string \'{s}\' results '''
       f'''in \'{result['bwt_string']}\''''
   )
   lowerCamelCase__					:  Dict      							=				reverse_bwt(result['bwt_string'], result['idx_original_string'])
   print(
       f'''Reversing Burrows Wheeler transform for entry \'{result['bwt_string']}\' '''
       f'''we get original string \'{original_string}\''''
   )