

import os
import unittest

from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class        A_		(       SCREAMING_SNAKE_CASE			,							unittest.TestCase				):
							_UpperCAmelCase    :  Dict						      =      FunnelTokenizer
							_UpperCAmelCase    :  List[str]						      =      FunnelTokenizerFast
							_UpperCAmelCase    :  str						      =      True
							_UpperCAmelCase    :  Optional[int]						      =      True
							def     lowerCAmelCase     (		self		:			Any):
								super().setUp()

								__lowerCamelCase				:				Union[str, Any]					       = [
								    '<unk>',
								    '<cls>',
								    '<sep>',
								    'want',
								    '##want',
								    '##ed',
								    'wa',
								    'un',
								    'runn',
								    '##ing',
								    ',',
								    'low',
								    'lowest',
								]
								__lowerCamelCase				:				Optional[Any]					       = 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     lowerCAmelCase     (		self		:			Union[str, Any]   ,**SCREAMING_SNAKE_CASE__		:			List[Any]):
								return FunnelTokenizer.from_pretrained(self.tmpdirname   ,**SCREAMING_SNAKE_CASE__)
							def     lowerCAmelCase     (		self		:			List[Any]   ,**SCREAMING_SNAKE_CASE__		:			List[str]):
								return FunnelTokenizerFast.from_pretrained(self.tmpdirname   ,**SCREAMING_SNAKE_CASE__)
							def     lowerCAmelCase     (		self		:			Optional[int]   ,SCREAMING_SNAKE_CASE__		:			str):
								__lowerCamelCase				:				Dict					       = 'UNwant\u00E9d,running'
								__lowerCamelCase				:				Tuple					       = 'unwanted, running'
								return input_text, output_text
							def     lowerCAmelCase     (		self		:			List[Any]):
								__lowerCamelCase				:				Tuple					       = self.tokenizer_class(self.vocab_file)

								__lowerCamelCase				:				Any					       = tokenizer.tokenize('UNwant\u00E9d,running')
								self.assertListEqual(SCREAMING_SNAKE_CASE__   ,['un', '##want', '##ed', ',', 'runn', '##ing'])
								self.assertListEqual(tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__)   ,[7, 4, 5, 1_0, 8, 9])


							def     lowerCAmelCase     (		self		:			Tuple):
								__lowerCamelCase				:				int					       = self.get_tokenizers(do_lower_case=SCREAMING_SNAKE_CASE__)
								for tokenizer in tokenizers:
									__lowerCamelCase				:				Dict					       = tokenizer('UNwant\u00E9d,running')
									__lowerCamelCase				:				int					       = len(inputs['input_ids']) - 1
									self.assertListEqual(inputs['token_type_ids']   ,[2] + [0] * sentence_len)

									__lowerCamelCase				:				Dict					       = tokenizer('UNwant\u00E9d,running'   ,'UNwant\u00E9d,running')
									self.assertListEqual(inputs['token_type_ids']   ,[2] + [0] * sentence_len + [1] * sentence_len)








import os
import sys
import unittest


lowerCamelCase											=       os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
lowerCamelCase											=       os.path.join(git_repo_path, 'src', 'transformers')

lowerCamelCase											=       '\n{0} = None\n'

lowerCamelCase											=       '\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n'


lowerCamelCase											=       '\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'




class A  (   unittest.TestCase     ):






      def        lowerCamelCase       (					self						:     Tuple )					->						Union[str, Any]:
             """simple docstring"""




             _lowerCamelCase       :		int		=find_backend('    _import_structure["models.albert"].append("AlbertTokenizerFast")' )
             self.assertIsNone(lowercase_ )

             _lowerCamelCase       :		List[str]		=find_backend('    if not is_tokenizers_available():' )
             self.assertEqual(lowercase_			,   'tokenizers' )

             _lowerCamelCase       :		List[Any]		=find_backend('    if not is_tensorflow_text_available():' )
             self.assertEqual(lowercase_			,   'tensorflow_text' )

             _lowerCamelCase       :		int		=find_backend('    if not (is_sentencepiece_available() and is_tokenizers_available()):' )
             self.assertEqual(lowercase_			,   'sentencepiece_and_tokenizers' )

             _lowerCamelCase       :		Dict		=find_backend(
                 '    if not (is_sentencepiece_available() and is_tensorflow_text_available()):' )
             self.assertEqual(lowercase_			,   'sentencepiece_and_tensorflow_text' )

             _lowerCamelCase       :		List[Any]		=find_backend(
                 '    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):' )
             self.assertEqual(lowercase_			,   'sentencepiece_and_tokenizers_and_vision' )






      def        lowerCamelCase       (					self						:     Optional[Any] )					->						List[str]:
             """simple docstring"""




             _lowerCamelCase       :		Union[str, Any]		=read_init()
             # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
             self.assertIn('torch'			,   lowercase_ )
             self.assertIn('tensorflow_text'			,   lowercase_ )
             self.assertIn('sentencepiece_and_tokenizers'			,   lowercase_ )

             # Likewise, we can't assert on the exact content of a key
             self.assertIn('BertModel'			,   objects['torch'] )
             self.assertIn('TFBertModel'			,   objects['tf'] )
             self.assertIn('FlaxBertModel'			,   objects['flax'] )
             self.assertIn('BertModel'			,   objects['torch'] )
             self.assertIn('TFBertTokenizer'			,   objects['tensorflow_text'] )
             self.assertIn('convert_slow_tokenizer'			,   objects['sentencepiece_and_tokenizers'] )






      def        lowerCamelCase       (					self						:     int )					->						Optional[Any]:
             """simple docstring"""




             _lowerCamelCase       :		Optional[Any]		=create_dummy_object('CONSTANT'			,   '\'torch\'' )
             self.assertEqual(lowercase_			,   '\nCONSTANT = None\n' )

             _lowerCamelCase       :		Dict		=create_dummy_object('function'			,   '\'torch\'' )
             self.assertEqual(
                 lowercase_			,   '\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n' )

             _lowerCamelCase       :		Union[str, Any]		='\nclass FakeClass(metaclass=DummyObject):\n    _backends = \'torch\'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, \'torch\')\n'
             _lowerCamelCase       :		Tuple		=create_dummy_object('FakeClass'			,   '\'torch\'' )
             self.assertEqual(lowercase_			,   lowercase_ )






      def        lowerCamelCase       (					self						:     List[Any] )					->						Dict:
             """simple docstring"""




             _lowerCamelCase       :		Dict		='# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, ["torch"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = ["torch"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, ["torch"])\n'
             _lowerCamelCase       :		Optional[int]		=create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']} )
             self.assertEqual(dummy_files['torch']			,   lowercase_ )


