


"""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 ):
  lowerCAmelCase__      			=	MgpstrTokenizer
  lowerCAmelCase__      			=	False
  lowerCAmelCase__      			=	{}
  lowerCAmelCase__      			=	False


  def 							_lowercase					(			self:						int    ):







     '''simple docstring'''







     super().setUp()

     # fmt: off
     _lowerCamelCase   :				List[Any]							=     ["[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
     _lowerCamelCase   :				Optional[Any]							=     dict(zip(__lowerCAmelCase							,range(len(__lowerCAmelCase    )    )    )    )

     _lowerCamelCase   :				List[str]							=     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(__lowerCAmelCase    ) + "\n"    )


  def 							_lowercase					(			self:						List[str]							,**__lowerCAmelCase:						Optional[Any]    ):







     '''simple docstring'''







     return MgpstrTokenizer.from_pretrained(self.tmpdirname							,**__lowerCAmelCase    )


  def 							_lowercase					(			self:						List[Any]							,__lowerCAmelCase:						Union[str, Any]    ):







     '''simple docstring'''







     _lowerCamelCase   :				List[Any]							=     "tester"
     _lowerCamelCase   :				Optional[Any]							=     "tester"
     return input_text, output_text


  @unittest.skip("MGP-STR always lower cases letters."    )
  def 							_lowercase					(			self:						Any    ):







     '''simple docstring'''







     pass


  def 							_lowercase					(			self:						Tuple    ):







     '''simple docstring'''







     _lowerCamelCase   :				List[str]							=     self.get_tokenizers(do_lower_case=__lowerCAmelCase    )
     for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""    ):
           _lowerCamelCase   :				Tuple							=     "[SPECIAL_TOKEN]"

           tokenizer.add_special_tokens({"cls_token": special_token}    )
           _lowerCamelCase   :				Optional[Any]							=     tokenizer.encode([special_token]							,add_special_tokens=__lowerCAmelCase    )
           self.assertEqual(len(__lowerCAmelCase    )							,1    )

           _lowerCamelCase   :				int							=     tokenizer.decode(__lowerCAmelCase							,skip_special_tokens=__lowerCAmelCase    )
           self.assertTrue(special_token not in decoded    )


  def 							_lowercase					(			self:						Tuple    ):







     '''simple docstring'''







     _lowerCamelCase   :				List[str]							=     self.get_tokenizers()
     for tokenizer in tokenizers:
        with self.subTest(F"""{tokenizer.__class__.__name__}"""    ):
           _lowerCamelCase,					_lowerCamelCase   :				List[Any]							=     self.get_input_output_texts(__lowerCAmelCase    )

           _lowerCamelCase   :				Optional[Any]							=     tokenizer.tokenize(__lowerCAmelCase    )
           _lowerCamelCase   :				int							=     tokenizer.convert_tokens_to_ids(__lowerCAmelCase    )
           _lowerCamelCase   :				List[Any]							=     tokenizer.encode(__lowerCAmelCase							,add_special_tokens=__lowerCAmelCase    )
           self.assertListEqual(__lowerCAmelCase							,__lowerCAmelCase    )

           _lowerCamelCase   :				Dict							=     tokenizer.convert_ids_to_tokens(__lowerCAmelCase    )
           self.assertNotEqual(len(__lowerCAmelCase    )							,0    )
           _lowerCamelCase   :				Optional[int]							=     tokenizer.decode(__lowerCAmelCase    )
           self.assertIsInstance(__lowerCAmelCase							,__lowerCAmelCase    )

           self.assertEqual(text_a.replace(" "							,""    )							,__lowerCAmelCase    )


  @unittest.skip("MGP-STR tokenizer only handles one sequence."    )
  def 							_lowercase					(			self:						Union[str, Any]    ):







     '''simple docstring'''







     pass






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







     '''simple docstring'''







     pass

import os
import sys

lowercase   =	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,
)


lowercase   =	[
    '''torch''',
    '''numpy''',
    '''tokenizers''',
    '''filelock''',
    '''requests''',
    '''tqdm''',
    '''regex''',
    '''sentencepiece''',
    '''sacremoses''',
    '''importlib_metadata''',
    '''huggingface_hub''',
]



@add_start_docstrings(AutoConfig.__doc__							)
def   __lowerCAmelCase    (				*UpperCAmelCase__					:   List[Any]      ,					**UpperCAmelCase__					:   List[str]							)	->     List[str]:
							return AutoConfig.from_pretrained(*UpperCAmelCase__      ,					**UpperCAmelCase__							)



@add_start_docstrings(AutoTokenizer.__doc__							)
def   __lowerCAmelCase    (				*UpperCAmelCase__					:   List[str]      ,					**UpperCAmelCase__					:   List[Any]							)	->     Any:
							return AutoTokenizer.from_pretrained(*UpperCAmelCase__      ,					**UpperCAmelCase__							)



@add_start_docstrings(AutoModel.__doc__							)
def   __lowerCAmelCase    (				*UpperCAmelCase__					:   Union[str, Any]      ,					**UpperCAmelCase__					:   Dict							)	->     Union[str, Any]:
							return AutoModel.from_pretrained(*UpperCAmelCase__      ,					**UpperCAmelCase__							)



@add_start_docstrings(AutoModelForCausalLM.__doc__							)
def   __lowerCAmelCase    (				*UpperCAmelCase__					:   List[str]      ,					**UpperCAmelCase__					:   List[Any]							)	->     Optional[Any]:
							return AutoModelForCausalLM.from_pretrained(*UpperCAmelCase__      ,					**UpperCAmelCase__							)



@add_start_docstrings(AutoModelForMaskedLM.__doc__							)
def   __lowerCAmelCase    (				*UpperCAmelCase__					:   Union[str, Any]      ,					**UpperCAmelCase__					:   Dict							)	->     int:
							return AutoModelForMaskedLM.from_pretrained(*UpperCAmelCase__      ,					**UpperCAmelCase__							)



@add_start_docstrings(AutoModelForSequenceClassification.__doc__							)
def   __lowerCAmelCase    (				*UpperCAmelCase__					:   List[Any]      ,					**UpperCAmelCase__					:   Dict							)	->     Dict:
							return AutoModelForSequenceClassification.from_pretrained(*UpperCAmelCase__      ,					**UpperCAmelCase__							)



@add_start_docstrings(AutoModelForQuestionAnswering.__doc__							)
def   __lowerCAmelCase    (				*UpperCAmelCase__					:   Any      ,					**UpperCAmelCase__					:   List[str]							)	->     Union[str, Any]:
							return AutoModelForQuestionAnswering.from_pretrained(*UpperCAmelCase__      ,					**UpperCAmelCase__							)





