'''simple docstring'''

import os
import sys

lowerCAmelCase				:int        =      os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


lowerCAmelCase				:List[Any]        =      [
    """torch""",
    """numpy""",
    """tokenizers""",
    """filelock""",
    """requests""",
    """tqdm""",
    """regex""",
    """sentencepiece""",
    """sacremoses""",
    """importlib_metadata""",
    """huggingface_hub""",
]





@add_start_docstrings(AutoConfig.__doc__		)
def lowerCamelCase      (      *lowerCAmelCase    :     Union[str, Any]		,		**lowerCAmelCase    :     int		):





	"""simple docstring"""







	return AutoConfig.from_pretrained(*lowerCAmelCase		,		**lowerCAmelCase		)





@add_start_docstrings(AutoTokenizer.__doc__		)
def lowerCamelCase      (      *lowerCAmelCase    :     List[Any]		,		**lowerCAmelCase    :     Optional[int]		):





	"""simple docstring"""







	return AutoTokenizer.from_pretrained(*lowerCAmelCase		,		**lowerCAmelCase		)





@add_start_docstrings(AutoModel.__doc__		)
def lowerCamelCase      (      *lowerCAmelCase    :     List[str]		,		**lowerCAmelCase    :     List[str]		):





	"""simple docstring"""







	return AutoModel.from_pretrained(*lowerCAmelCase		,		**lowerCAmelCase		)





@add_start_docstrings(AutoModelForCausalLM.__doc__		)
def lowerCamelCase      (      *lowerCAmelCase    :     int		,		**lowerCAmelCase    :     str		):





	"""simple docstring"""







	return AutoModelForCausalLM.from_pretrained(*lowerCAmelCase		,		**lowerCAmelCase		)





@add_start_docstrings(AutoModelForMaskedLM.__doc__		)
def lowerCamelCase      (      *lowerCAmelCase    :     List[str]		,		**lowerCAmelCase    :     Tuple		):





	"""simple docstring"""







	return AutoModelForMaskedLM.from_pretrained(*lowerCAmelCase		,		**lowerCAmelCase		)





@add_start_docstrings(AutoModelForSequenceClassification.__doc__		)
def lowerCamelCase      (      *lowerCAmelCase    :     Optional[int]		,		**lowerCAmelCase    :     Dict		):





	"""simple docstring"""







	return AutoModelForSequenceClassification.from_pretrained(*lowerCAmelCase		,		**lowerCAmelCase		)





@add_start_docstrings(AutoModelForQuestionAnswering.__doc__		)
def lowerCamelCase      (      *lowerCAmelCase    :     Dict		,		**lowerCAmelCase    :     str		):





	"""simple docstring"""







	return AutoModelForQuestionAnswering.from_pretrained(*lowerCAmelCase		,		**lowerCAmelCase		)



'''simple docstring'''

import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _lowerCamelCase	(						lowercase__		,					unittest.TestCase							):



		'''simple docstring'''







		A_     :      Optional[Any]				   =    LxmertTokenizer
		A_     :      List[Any]				   =    LxmertTokenizerFast
		A_     :      int				   =    True
		A_     :      Any				   =    True







		def        __lowerCAmelCase		( self		:						List[str]      )  ->			Tuple:
			super().setUp()

			__magic_name__	:   str					     =					[
			    '[UNK]',
			    '[CLS]',
			    '[SEP]',
			    'want',
			    '##want',
			    '##ed',
			    'wa',
			    'un',
			    'runn',
			    '##ing',
			    ',',
			    'low',
			    'lowest',
			]
			__magic_name__	:   List[str]					     =					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		:						Any  ,					_A		:						str      )  ->			List[Any]:
			__magic_name__	:   Dict					     =					'UNwant\u00E9d,running'
			__magic_name__	:   Dict					     =					'unwanted, running'
			return input_text, output_text







		def        __lowerCAmelCase		( self		:						Tuple      )  ->			Optional[int]:
			__magic_name__	:   Optional[Any]					     =					self.tokenizer_class(self.vocab_file      )

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







		def        __lowerCAmelCase		( self		:						int      )  ->			List[Any]:
			if not self.test_rust_tokenizer:
				return

			__magic_name__	:   Any					     =					self.get_tokenizer()
			__magic_name__	:   Optional[Any]					     =					self.get_rust_tokenizer()

			__magic_name__	:   Union[str, Any]					     =					'I was born in 92000, and this is falsé.'

			__magic_name__	:   List[Any]					     =					tokenizer.tokenize(_A      )
			__magic_name__	:   Dict					     =					rust_tokenizer.tokenize(_A      )
			self.assertListEqual(_A  ,					_A      )

			__magic_name__	:   int					     =					tokenizer.encode(_A  ,					add_special_tokens=_A      )
			__magic_name__	:   Union[str, Any]					     =					rust_tokenizer.encode(_A  ,					add_special_tokens=_A      )
			self.assertListEqual(_A  ,					_A      )

			__magic_name__	:   List[Any]					     =					self.get_rust_tokenizer()
			__magic_name__	:   str					     =					tokenizer.encode(_A      )
			__magic_name__	:   Optional[int]					     =					rust_tokenizer.encode(_A      )
			self.assertListEqual(_A  ,					_A      )