




'''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
A									=pytest.mark.integration


A									={'comet'}
A									=importlib.util.find_spec('fairseq') is not None

A									={'code_eval'}
A									=os.name == 'nt'

A									={'bertscore', 'frugalscore', 'perplexity'}
A									=importlib.util.find_spec('transformers') is not None





def 		snake_case_							(_a			:							Any  ):
    @wraps(_a  )
    def wrapper(self			:							int					,     _a			:							Tuple  ):
        if not _has_fairseq and metric_name in REQUIRE_FAIRSEQ:
            self.skipTest('''\"test requires Fairseq\"'''  )
        else:
            test_case(self					,     _a  )

    return wrapper





def 		snake_case_							(_a			:							Tuple  ):
    @wraps(_a  )
    def wrapper(self			:							Optional[int]					,     _a			:							List[Any]  ):
        if not _has_transformers and metric_name in REQUIRE_TRANSFORMERS:
            self.skipTest('''\"test requires transformers\"'''  )
        else:
            test_case(self					,     _a  )

    return wrapper





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

    return wrapper





def 		snake_case_							():
    UpperCAmelCase     =	[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(
    lowercase_							,							lowercase_							,							lowercase_				)
@local
class     _a						(			parameterized.TestCase				):
       __a       :  Optional[Any]            =      {}
       __a       :  Optional[int]            =      None
       @pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning'''       )
       @pytest.mark.filterwarnings('''ignore:load_metric is deprecated:FutureWarning'''       )
       def 					A   (			self		:			Union[str, Any]     ,       lowercase		:			Dict       ):



           '''simple docstring'''

           UpperCAmelCase     =	'''[...]'''
           UpperCAmelCase     =	importlib.import_module(
               datasets.load.metric_module_factory(os.path.join('''metrics'''     ,       UpperCamelCase__       )       ).module_path       )
           UpperCAmelCase     =	datasets.load.import_main_class(metric_module.__name__     ,       dataset=UpperCamelCase__       )
           # check parameters
           UpperCAmelCase     =	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(UpperCamelCase__     ,       metric_module.__name__       ):
               with self.use_local_metrics():
                   try:
                       UpperCAmelCase     =	doctest.testmod(UpperCamelCase__     ,       verbose=UpperCamelCase__     ,       raise_on_error=UpperCamelCase__       )
                   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		:			Any     ,       lowercase		:			Dict       ):



           '''simple docstring'''

           UpperCAmelCase     =	'''[...]'''
           UpperCAmelCase     =	importlib.import_module(
               datasets.load.metric_module_factory(os.path.join('''metrics'''     ,       UpperCamelCase__       )       ).module_path       )
           # run doctest
           with self.use_local_metrics():
               UpperCAmelCase     =	doctest.testmod(UpperCamelCase__     ,       verbose=UpperCamelCase__     ,       raise_on_error=UpperCamelCase__       )
           self.assertEqual(results.failed     ,       0       )
           self.assertGreater(results.attempted     ,       1       )
       @contextmanager
       def 					A   (			self		:			int     ,       lowercase		:			int     ,       lowercase		:			List[str]       ):



           '''simple docstring'''

           if metric_name in self.INTENSIVE_CALLS_PATCHER:
               with self.INTENSIVE_CALLS_PATCHER[metric_name](UpperCamelCase__       ):
                   yield
           else:
               yield
       @contextmanager
       def 					A   (			self		:			List[Any]       ):



           '''simple docstring'''

           def load_local_metric(lowercase		:			Optional[Any]     ,       *lowercase		:			Dict     ,       **lowercase		:			Union[str, Any]       ):
               return load_metric(os.path.join('''metrics'''     ,       UpperCamelCase__       )     ,       *UpperCamelCase__     ,       **UpperCamelCase__       )

           with patch('''datasets.load_metric'''       ) as mock_load_metric:
               UpperCAmelCase     =	load_local_metric
               yield







       @classmethod
       def 					A   (			cls		:			Optional[Any]     ,       lowercase		:			Optional[Any]       ):



           '''simple docstring'''

           def wrapper(lowercase		:			Dict       ):
               UpperCAmelCase     =	contextmanager(UpperCamelCase__       )
               UpperCAmelCase     =	patcher
               return patcher

           return wrapper






@LocalMetricTest.register_intensive_calls_patcher('''bleurt'''  )
def 		snake_case_							(_a			:							Dict  ):
    import tensorflow.compat.va as tf
    from bleurt.score import Predictor

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


    class     _a						(			lowercase_				):
           def 					A   (			self		:			Any     ,       lowercase		:			Dict       ):



               '''simple docstring'''

               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:
        UpperCAmelCase     =	MockedPredictor()
        yield





@LocalMetricTest.register_intensive_calls_patcher('''bertscore'''  )
def 		snake_case_							(_a			:							str  ):
    import torch

    def bert_cos_score_idf(_a			:							Optional[Any]					,     _a			:							int					,     *_a			:							Dict					,     **_a			:							Any  ):
        return torch.tensor([[1.0, 1.0, 1.0]] * len(_a  )  )

    # 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     =	bert_cos_score_idf
        yield





@LocalMetricTest.register_intensive_calls_patcher('''comet'''  )
def 		snake_case_							(_a			:							Optional[Any]  ):
    def load_from_checkpoint(_a			:							int  ):


        class     _a						:
               def 					A   (			self		:			Union[str, Any]     ,       lowercase		:			Optional[int]     ,       *lowercase		:			Optional[Any]     ,       **lowercase		:			str       ):



                   '''simple docstring'''

                   assert len(UpperCamelCase__       ) == 2
                   UpperCAmelCase     =	[0.19, 0.92]
                   return scores, sum(UpperCamelCase__       ) / len(UpperCamelCase__       )






        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     =	None
        with patch('''comet.load_from_checkpoint'''  ) as mock_load_from_checkpoint:
            UpperCAmelCase     =	load_from_checkpoint
            yield







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










'''simple docstring'''







import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class     _a						(			__a							,							unittest.TestCase				):
       __a       :  Any            =      MgpstrTokenizer
       __a       :  Optional[Any]            =      False
       __a       :  str            =      {}
       __a       :  Optional[int]            =      False
       def 					A   (			self		:			Dict       ):



           '''simple docstring'''

           super().setUp()

           # fmt: off
           UpperCAmelCase     =	['''[GO]''', '''[s]''', '''0''', '''1''', '''2''', '''3''', '''4''', '''5''', '''6''', '''7''', '''8''', '''9''', '''a''', '''b''', '''c''', '''d''', '''e''', '''f''', '''g''', '''h''', '''i''', '''j''', '''k''', '''l''', '''m''', '''n''', '''o''', '''p''', '''q''', '''r''', '''s''', '''t''', '''u''', '''v''', '''w''', '''x''', '''y''', '''z''']
           # fmt: on
           UpperCAmelCase     =	dict(zip(lowercase     ,       range(len(lowercase       )       )       )       )

           UpperCAmelCase     =	os.path.join(self.tmpdirname     ,       VOCAB_FILES_NAMES['''vocab_file''']       )
           with open(self.vocab_file     ,       '''w'''     ,       encoding='''utf-8'''       ) as fp:
               fp.write(json.dumps(lowercase       ) + '''\n'''       )
       def 					A   (			self		:			int     ,       **lowercase		:			Optional[Any]       ):



           '''simple docstring'''

           return MgpstrTokenizer.from_pretrained(self.tmpdirname     ,       **lowercase       )
       def 					A   (			self		:			int     ,       lowercase		:			str       ):



           '''simple docstring'''

           UpperCAmelCase     =	'''tester'''
           UpperCAmelCase     =	'''tester'''
           return input_text, output_text
       @unittest.skip('''MGP-STR always lower cases letters.'''       )
       def 					A   (			self		:			Optional[int]       ):



           '''simple docstring'''

           pass
       def 					A   (			self		:			int       ):



           '''simple docstring'''

           UpperCAmelCase     =	self.get_tokenizers(do_lower_case=lowercase       )
           for tokenizer in tokenizers:
               with self.subTest(f"{tokenizer.__class__.__name__}"       ):
                   UpperCAmelCase     =	'''[SPECIAL_TOKEN]'''

                   tokenizer.add_special_tokens({'''cls_token''': special_token}       )
                   UpperCAmelCase     =	tokenizer.encode([special_token]     ,       add_special_tokens=lowercase       )
                   self.assertEqual(len(lowercase       )     ,       1       )

                   UpperCAmelCase     =	tokenizer.decode(lowercase     ,       skip_special_tokens=lowercase       )
                   self.assertTrue(special_token not in decoded       )
       def 					A   (			self		:			List[Any]       ):



           '''simple docstring'''

           UpperCAmelCase     =	self.get_tokenizers()
           for tokenizer in tokenizers:
               with self.subTest(f"{tokenizer.__class__.__name__}"       ):
                   UpperCAmelCase ,  UpperCAmelCase     =	self.get_input_output_texts(lowercase       )

                   UpperCAmelCase     =	tokenizer.tokenize(lowercase       )
                   UpperCAmelCase     =	tokenizer.convert_tokens_to_ids(lowercase       )
                   UpperCAmelCase     =	tokenizer.encode(lowercase     ,       add_special_tokens=lowercase       )
                   self.assertListEqual(lowercase     ,       lowercase       )

                   UpperCAmelCase     =	tokenizer.convert_ids_to_tokens(lowercase       )
                   self.assertNotEqual(len(lowercase       )     ,       0       )
                   UpperCAmelCase     =	tokenizer.decode(lowercase       )
                   self.assertIsInstance(lowercase     ,       lowercase       )

                   self.assertEqual(text_a.replace(''' '''     ,       ''''''       )     ,       lowercase       )
       @unittest.skip('''MGP-STR tokenizer only handles one sequence.'''       )
       def 					A   (			self		:			Any       ):



           '''simple docstring'''

           pass







       @unittest.skip('''inputs cannot be pretokenized in MgpstrTokenizer'''       )
       def 					A   (			self		:			str       ):



           '''simple docstring'''

           pass




