




import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


SCREAMING_SNAKE_CASE__			: List[str]    =  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__			: Any    =  {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

SCREAMING_SNAKE_CASE__			: List[Any]    =  {
    'vocab_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/vocab.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/vocab.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/vocab.json',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/merges.txt',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/merges.txt',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/merges.txt',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'
        ),
    },
    'tokenizer_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/tokenizer.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/tokenizer.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json',
        'roberta-base-openai-detector': (
            'https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json'
        ),
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json'
        ),
    },
}

SCREAMING_SNAKE_CASE__			: int    =  {
    'roberta-base': 512,
    'roberta-large': 512,
    'roberta-large-mnli': 512,
    'distilroberta-base': 512,
    'roberta-base-openai-detector': 512,
    'roberta-large-openai-detector': 512,
}




class 						UpperCamelCase__      (_a	):

    '''simple docstring'''



    lowerCamelCase_ :      Optional[Any]      	= VOCAB_FILES_NAMES
    lowerCamelCase_ :      Optional[Any]      	= PRETRAINED_VOCAB_FILES_MAP
    lowerCamelCase_ :      Any      	= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowerCamelCase_ :      Dict      	= ["""input_ids""", """attention_mask"""]
    lowerCamelCase_ :      List[Any]      	= RobertaTokenizer







    def __init__(       self	,    UpperCamelCase__=None	,    UpperCamelCase__=None	,    UpperCamelCase__=None	,    UpperCamelCase__="replace"	,    UpperCamelCase__="<s>"	,    UpperCamelCase__="</s>"	,    UpperCamelCase__="</s>"	,    UpperCamelCase__="<s>"	,    UpperCamelCase__="<unk>"	,    UpperCamelCase__="<pad>"	,    UpperCamelCase__="<mask>"	,    UpperCamelCase__=False	,    UpperCamelCase__=True	,    **UpperCamelCase__	,    )	-> List[str]:
           super().__init__(
               __lowerCAmelCase	,    __lowerCAmelCase	,    tokenizer_file=__lowerCAmelCase	,    errors=__lowerCAmelCase	,    bos_token=__lowerCAmelCase	,    eos_token=__lowerCAmelCase	,    sep_token=__lowerCAmelCase	,    cls_token=__lowerCAmelCase	,    unk_token=__lowerCAmelCase	,    pad_token=__lowerCAmelCase	,    mask_token=__lowerCAmelCase	,    add_prefix_space=__lowerCAmelCase	,    trim_offsets=__lowerCAmelCase	,    **__lowerCAmelCase	,    )

           lowerCamelCase  : int     					=   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
           if pre_tok_state.get("add_prefix_space"	,    __lowerCAmelCase	) != add_prefix_space:
                  lowerCamelCase  : List[str]     					=   getattr(__lowerCAmelCase	,    pre_tok_state.pop("type"	)	)
                  lowerCamelCase  : List[str]     					=   add_prefix_space
                  lowerCamelCase  : List[Any]     					=   pre_tok_class(**__lowerCAmelCase	)

           lowerCamelCase  : int     					=   add_prefix_space

           lowerCamelCase  : Optional[int]     					=   "post_processor"
           lowerCamelCase  : List[Any]     					=   getattr(self.backend_tokenizer	,    __lowerCAmelCase	,    __lowerCAmelCase	)
           if tokenizer_component_instance:
                  lowerCamelCase  : str     					=   json.loads(tokenizer_component_instance.__getstate__()	)

                  # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
                  if "sep" in state:
                         lowerCamelCase  : Dict     					=   tuple(state["sep"]	)
                  if "cls" in state:
                         lowerCamelCase  : Optional[int]     					=   tuple(state["cls"]	)

                  lowerCamelCase  : str     					=   False

                  if state.get("add_prefix_space"	,    __lowerCAmelCase	) != add_prefix_space:
                         lowerCamelCase  : List[Any]     					=   add_prefix_space
                         lowerCamelCase  : List[Any]     					=   True

                  if state.get("trim_offsets"	,    __lowerCAmelCase	) != trim_offsets:
                         lowerCamelCase  : Union[str, Any]     					=   trim_offsets
                         lowerCamelCase  : str     					=   True

                  if changes_to_apply:
                         lowerCamelCase  : Optional[Any]     					=   getattr(__lowerCAmelCase	,    state.pop("type"	)	)
                         lowerCamelCase  : Optional[int]     					=   component_class(**__lowerCAmelCase	)
                         setattr(self.backend_tokenizer	,    __lowerCAmelCase	,    __lowerCAmelCase	)







    @property
    def        _lowercase	(       self	)	-> Any:
           if self._mask_token is None:
                  if self.verbose:
                         logger.error("Using mask_token, but it is not set yet."	)
                  return None
           return str(self._mask_token	)







    @mask_token.setter
    def        _lowercase	(       self	,    UpperCamelCase__	)	-> int:
           lowerCamelCase  : int     					=   AddedToken(__lowerCAmelCase	,    lstrip=__lowerCAmelCase	,    rstrip=__lowerCAmelCase	) if isinstance(__lowerCAmelCase	,    __lowerCAmelCase	) else value
           lowerCamelCase  : Union[str, Any]     					=   value







    def        _lowercase	(       self	,    *UpperCamelCase__	,    **UpperCamelCase__	)	-> Union[str, Any]:
           lowerCamelCase  : Tuple     					=   kwargs.get("is_split_into_words"	,    __lowerCAmelCase	)
           assert self.add_prefix_space or not is_split_into_words, (
               F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
               "to use it with pretokenized inputs."
           )

           return super()._batch_encode_plus(*__lowerCAmelCase	,    **__lowerCAmelCase	)







    def        _lowercase	(       self	,    *UpperCamelCase__	,    **UpperCamelCase__	)	-> Any:
           lowerCamelCase  : Optional[int]     					=   kwargs.get("is_split_into_words"	,    __lowerCAmelCase	)

           assert self.add_prefix_space or not is_split_into_words, (
               F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
               "to use it with pretokenized inputs."
           )

           return super()._encode_plus(*__lowerCAmelCase	,    **__lowerCAmelCase	)







    def        _lowercase	(       self	,    UpperCamelCase__	,    UpperCamelCase__ = None	)	-> Dict:
           lowerCamelCase  : Union[str, Any]     					=   self._tokenizer.model.save(__lowerCAmelCase	,    name=__lowerCAmelCase	)
           return tuple(__lowerCAmelCase	)







    def        _lowercase	(       self	,    UpperCamelCase__	,    UpperCamelCase__=None	)	-> Optional[Any]:
           lowerCamelCase  : Dict     					=   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
           if token_ids_a is None:
                  return output

           return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]







    def        _lowercase	(       self	,    UpperCamelCase__	,    UpperCamelCase__ = None	)	-> Optional[Any]:
           lowerCamelCase  : Optional[Any]     					=   [self.sep_token_id]
           lowerCamelCase  : Dict     					=   [self.cls_token_id]

           if token_ids_a is None:
                  return len(cls + token_ids_a + sep	) * [0]
           return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]













import os

import pytest

from transformers.dynamic_module_utils import get_imports


UpperCamelCase__           =			"\nimport os\n"

UpperCamelCase__           =			"\ndef foo():\n    import os\n    return False\n"

UpperCamelCase__           =			"\ndef foo():\n    def bar():\n        if True:\n            import os\n        return False\n    return bar()\n"

UpperCamelCase__           =			"\nimport os\n\ntry:\n    import bar\nexcept ImportError:\n    raise ValueError()\n"

UpperCamelCase__           =			"\nimport os\n\ndef foo():\n    try:\n        import bar\n    except ImportError:\n        raise ValueError()\n"

UpperCamelCase__           =			"\nimport os\n\ntry:\n    import bar\nexcept (ImportError, AttributeError):\n    raise ValueError()\n"

UpperCamelCase__           =			"\nimport os\n\ntry:\n    import bar\nexcept ImportError as e:\n    raise ValueError()\n"

UpperCamelCase__           =			"\nimport os\n\ntry:\n    import bar\nexcept:\n    raise ValueError()\n"

UpperCamelCase__           =			"\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    raise ValueError()\n"

UpperCamelCase__           =			"\nimport os\n\ntry:\n    import bar\n    import baz\nexcept ImportError:\n    x = 1\n    raise ValueError()\n"

UpperCamelCase__           =			[
    TOP_LEVEL_IMPORT,
    IMPORT_IN_FUNCTION,
    DEEPLY_NESTED_IMPORT,
    TOP_LEVEL_TRY_IMPORT,
    GENERIC_EXCEPT_IMPORT,
    MULTILINE_TRY_IMPORT,
    MULTILINE_BOTH_IMPORT,
    MULTIPLE_EXCEPTS_IMPORT,
    EXCEPT_AS_IMPORT,
    TRY_IMPORT_IN_FUNCTION,
]





@pytest.mark.parametrize("""case""" ,      a__							)
def      _UpperCamelCase  (a__ :Any ,      a__ :Optional[Any]							):






							"""simple docstring"""





							UpperCamelCase__					  =      os.path.join(a__ ,      """test_file.py"""							)
							with open(a__ ,      """w"""							) as _tmp_file:
														_tmp_file.write(a__							)

							UpperCamelCase__					  =      get_imports(a__							)
							assert parsed_imports == ["os"]




