

import pytest

from datasets import inspect_metric, list_metrics, load_metric




@pytest.fixture
def 					_lowercase     (				a_				:					List[str]				)				->	Optional[int]:




					'''simple docstring'''







					monkeypatch.setattr('datasets.utils.deprecation_utils._emitted_deprecation_warnings'					,set()				)




@pytest.fixture
def 					_lowercase     (				a_				:					str				)				->	Tuple:




					'''simple docstring'''







					class 				__UpperCamelCase				:







						def __init__(   self: Union[str, Any]  , __UpperCamelCase: int      ):

											'''simple docstring'''





											__magic_name__							=    metric_id




					class 				__UpperCamelCase				:
						_lowercase  :   Optional[Any]       				=  [MetricMock(SCREAMING_SNAKE_CASE			) for metric_id in ["accuracy", "mse", "precision", "codeparrot/apps_metric"]]







						def 	_SCREAMING_SNAKE_CASE							(   self: List[str]      ):

											'''simple docstring'''





											return self._metrics




					monkeypatch.setattr('datasets.inspect.huggingface_hub'					,HfhMock()				)




@pytest.mark.parametrize(
    'func, args'					,[(load_metric, ('metrics/mse',)), (list_metrics, ()), (inspect_metric, ('metrics/mse', 'tmp_path'))]				)
def 					_lowercase     (				a_				:					Optional[Any]					,a_				:					Tuple					,a_				:					Tuple					,a_				:					Tuple					,a_				:					str				)				->	int:




					'''simple docstring'''







					if "tmp_path" in args:
										__magic_name__							=    tuple(arg if arg != 'tmp_path' else tmp_path for arg in args				)
					with pytest.warns(a_					,match='https://huggingface.co/docs/evaluate'				):
										func(*a_				)







import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE  ,						unittest.TestCase			):
	_lowercase  :   Tuple       				=  LayoutLMTokenizer
	_lowercase  :   List[str]       				=  LayoutLMTokenizerFast
	_lowercase  :   List[Any]       				=  True
	_lowercase  :   Optional[int]       				=  True







	def 	_SCREAMING_SNAKE_CASE							(   self: Any      ):

						'''simple docstring'''





						super().setUp()

						__magic_name__							=    [
						    '[UNK]',
						    '[CLS]',
						    '[SEP]',
						    'want',
						    '##want',
						    '##ed',
						    'wa',
						    'un',
						    'runn',
						    '##ing',
						    ',',
						    'low',
						    'lowest',
						]
						__magic_name__							=    os.path.join(self.tmpdirname  , VOCAB_FILES_NAMES['vocab_file']      )
						with open(self.vocab_file  , 'w'  , encoding='utf-8'      ) as vocab_writer:
											vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]      )      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Union[str, Any]  , **__UpperCamelCase: Union[str, Any]      ):

						'''simple docstring'''





						return LayoutLMTokenizer.from_pretrained(self.tmpdirname  , **__UpperCamelCase      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Tuple  , __UpperCamelCase: List[str]      ):

						'''simple docstring'''





						__magic_name__							=    'UNwant\u00E9d,running'
						__magic_name__							=    'unwanted, running'
						return input_text, output_text







	def 	_SCREAMING_SNAKE_CASE							(   self: List[Any]      ):

						'''simple docstring'''





						__magic_name__							=    self.tokenizer_class(self.vocab_file      )

						__magic_name__							=    tokenizer.tokenize('UNwant\u00E9d,running'      )
						self.assertListEqual(__UpperCamelCase  , ['un', '##want', '##ed', ',', 'runn', '##ing']      )
						self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase      )  , [7, 4, 5, 10, 8, 9]      )







	def 	_SCREAMING_SNAKE_CASE							(   self: Dict      ):

						'''simple docstring'''





						pass




