
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_bart import BartTokenizer


lowerCamelCase_						: int         =  logging.get_logger(__name__)


lowerCamelCase_						: List[Any]         =  {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

# See all BART models at https://huggingface.co/models?filter=bart
lowerCamelCase_						: Optional[int]         =  {
    """vocab_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/vocab.json""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/vocab.json""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/merges.txt""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/merges.txt""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """facebook/bart-base""": """https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json""",
        """facebook/bart-large""": """https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json""",
        """facebook/bart-large-mnli""": """https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json""",
        """facebook/bart-large-cnn""": """https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json""",
        """facebook/bart-large-xsum""": """https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json""",
        """yjernite/bart_eli5""": """https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json""",
    },
}

lowerCamelCase_						: Dict         =  {
    """facebook/bart-base""": 10_24,
    """facebook/bart-large""": 10_24,
    """facebook/bart-large-mnli""": 10_24,
    """facebook/bart-large-cnn""": 10_24,
    """facebook/bart-large-xsum""": 10_24,
    """yjernite/bart_eli5""": 10_24,
}

class        _UpperCamelCase				(					_A  ):






			'''simple docstring'''

			__UpperCamelCase      :						Dict					      = VOCAB_FILES_NAMES
			__UpperCamelCase      :						Optional[Any]					      = PRETRAINED_VOCAB_FILES_MAP
			__UpperCamelCase      :						Dict					      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			__UpperCamelCase      :						Optional[int]					      = ["input_ids", "attention_mask"]
			__UpperCamelCase      :						Any					      = BartTokenizer

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

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

							UpperCamelCase_:							int	=						add_prefix_space

							# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
							UpperCamelCase_:							Dict	=						"""post_processor"""
							UpperCamelCase_:							Any	=						getattr(self.backend_tokenizer						,	UpperCamelCase__						,	UpperCamelCase__      )
							if tokenizer_component_instance:
											UpperCamelCase_:							Optional[int]	=						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:
															UpperCamelCase_:							str	=						tuple(state["""sep"""]      )
											if "cls" in state:
															UpperCamelCase_:							List[Any]	=						tuple(state["""cls"""]      )

											UpperCamelCase_:							List[Any]	=						False

											if state.get("""add_prefix_space"""						,	UpperCamelCase__      ) != add_prefix_space:
															UpperCamelCase_:							Dict	=						add_prefix_space
															UpperCamelCase_:							Tuple	=						True

											if state.get("""trim_offsets"""						,	UpperCamelCase__      ) != trim_offsets:
															UpperCamelCase_:							Optional[int]	=						trim_offsets
															UpperCamelCase_:							str	=						True

											if changes_to_apply:
															UpperCamelCase_:							str	=						getattr(UpperCamelCase__						,	state.pop("""type"""      )      )
															UpperCamelCase_:							List[str]	=						component_class(**UpperCamelCase__      )
															setattr(self.backend_tokenizer						,	UpperCamelCase__						,	UpperCamelCase__      )

			@property
			def       lowerCAmelCase__	(       self :       Optional[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       lowerCAmelCase__	(       self :       Any						,	snake_case_ :       Optional[Any]      ):
							UpperCamelCase_:							List[Any]	=						AddedToken(UpperCamelCase__						,	lstrip=UpperCamelCase__						,	rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__						,	UpperCamelCase__      ) else value
							UpperCamelCase_:							Optional[int]	=						value

			def       lowerCAmelCase__	(       self :       Tuple						,	*snake_case_ :       Tuple						,	**snake_case_ :       Dict      ):
							UpperCamelCase_:							List[str]	=						kwargs.get("""is_split_into_words"""						,	UpperCamelCase__      )

							if is_split_into_words and not self.add_prefix_space:
											raise ValueError(
											    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
											    """to use it with pretokenized inputs."""      )

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

			def       lowerCAmelCase__	(       self :       Optional[int]						,	*snake_case_ :       List[Any]						,	**snake_case_ :       List[Any]      ):
							UpperCamelCase_:							List[str]	=						kwargs.get("""is_split_into_words"""						,	UpperCamelCase__      )

							if is_split_into_words and not self.add_prefix_space:
											raise ValueError(
											    f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
											    """to use it with pretokenized inputs."""      )

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

			def       lowerCAmelCase__	(       self :       Optional[Any]						,	snake_case_ :       Tuple						,	snake_case_ :       Union[str, Any] = None      ):
							UpperCamelCase_:							Optional[int]	=						self._tokenizer.model.save(UpperCamelCase__						,	name=UpperCamelCase__      )
							return tuple(UpperCamelCase__      )

			def       lowerCAmelCase__	(       self :       Any						,	snake_case_ :       Any						,	snake_case_ :       List[str]=None      ):
							UpperCamelCase_:							Optional[int]	=						[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       lowerCAmelCase__	(       self :       Tuple						,	snake_case_ :       str						,	snake_case_ :       Optional[int] = None      ):
							UpperCamelCase_:							List[Any]	=						[self.sep_token_id]
							UpperCamelCase_:							str	=						[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 warnings

from ..trainer import Trainer
from ..utils import logging


lowerCamelCase_						: Dict         =  logging.get_logger(__name__)

class        _UpperCamelCase				(					_A  ):






			'''simple docstring'''

			def __init__(       self :       List[str]						,	snake_case_ :       Tuple=None						,	**snake_case_ :       List[str]      ):
							warnings.warn(
							    """`SageMakerTrainer` is deprecated and will be removed in v5 of Transformers. You can use `Trainer` """
							    """instead."""						,	snake_case_						,	)
							super().__init__(args=snake_case_						,	**snake_case_      )






