
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_longformer import LongformerTokenizer


_A       =					logging.get_logger(__name__)

_A       =					{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

_A       =					{
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "allenai/longformer-base-4096": (
            "https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
    },
}

_A       =					{
    "allenai/longformer-base-4096": 40_96,
    "allenai/longformer-large-4096": 40_96,
    "allenai/longformer-large-4096-finetuned-triviaqa": 40_96,
    "allenai/longformer-base-4096-extra.pos.embd.only": 40_96,
    "allenai/longformer-large-4096-extra.pos.embd.only": 40_96,
}







class 	lowerCamelCase						(    A_    ):
     UpperCAmelCase__							:				Optional[Any] 	=						VOCAB_FILES_NAMES
     UpperCAmelCase__							:				str 	=						PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__							:				Optional[int] 	=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__							:				int 	=						["input_ids", "attention_mask"]
     UpperCAmelCase__							:				Tuple 	=						LongformerTokenizer





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

         snake_case						=   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()  )
         if pre_tok_state.get("add_prefix_space"							,       _A  ) != add_prefix_space:
             snake_case						=   getattr(_A							,       pre_tok_state.pop("type"  )  )
             snake_case						=   add_prefix_space
             snake_case						=   pre_tok_class(**_A  )

         snake_case						=   add_prefix_space

         snake_case						=   "post_processor"
         snake_case						=   getattr(self.backend_tokenizer							,       _A							,       _A  )
         if tokenizer_component_instance:
             snake_case						=   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:
                 snake_case						=   tuple(state["sep"]  )
             if "cls" in state:
                 snake_case						=   tuple(state["cls"]  )

             snake_case						=   False

             if state.get("add_prefix_space"							,       _A  ) != add_prefix_space:
                 snake_case						=   add_prefix_space
                 snake_case						=   True

             if state.get("trim_offsets"							,       _A  ) != trim_offsets:
                 snake_case						=   trim_offsets
                 snake_case						=   True

             if changes_to_apply:
                 snake_case						=   getattr(_A							,       state.pop("type"  )  )
                 snake_case						=   component_class(**_A  )
                 setattr(self.backend_tokenizer							,       _A							,       _A  )





     @property
     def 						UpperCAmelCase(self :       str  )		->		str:
         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 						UpperCAmelCase(self :       Dict							,       _A :       Optional[Any]  )		->		Union[str, Any]:
         snake_case						=   AddedToken(_A							,       lstrip=_A							,       rstrip=_A  ) if isinstance(_A							,       _A  ) else value
         snake_case						=   value





     def 						UpperCAmelCase(self :       Optional[Any]							,       *_A :       Dict							,       **_A :       Union[str, Any]  )		->		BatchEncoding:
         snake_case						=   kwargs.get("is_split_into_words"							,       _A  )
         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(*_A							,       **_A  )





     def 						UpperCAmelCase(self :       Any							,       *_A :       Any							,       **_A :       Tuple  )		->		BatchEncoding:
         snake_case						=   kwargs.get("is_split_into_words"							,       _A  )

         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(*_A							,       **_A  )





     def 						UpperCAmelCase(self :       Any							,       _A :       str							,       _A :       Optional[str] = None  )		->		Tuple[str]:
         snake_case						=   self._tokenizer.model.save(_A							,       name=_A  )
         return tuple(_A  )





     def 						UpperCAmelCase(self :       List[str]							,       _A :       Tuple							,       _A :       List[str]=None  )		->		int:
         snake_case						=   [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 						UpperCAmelCase(self :       Dict							,       _A :       List[int]							,       _A :       Optional[List[int]] = None  )		->		List[int]:
         snake_case						=   [self.sep_token_id]
         snake_case						=   [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]



from transformers.models.cpm.tokenization_cpm import CpmTokenizer
from transformers.testing_utils import custom_tokenizers

from ..xlnet.test_modeling_xlnet import XLNetModelTest







@custom_tokenizers
class 	lowerCamelCase						(    A_    ):





     def 						UpperCAmelCase(self :       Optional[Any]							,       _A :       Tuple							,       _A :       Tuple							,       _A :       str							,       _A :       Tuple							,       _A :       Any  )		->		Optional[int]:
         return True





     def 						UpperCAmelCase(self :       str  )		->		List[str]:
         snake_case						=   CpmTokenizer.from_pretrained("TsinghuaAI/CPM-Generate"  )
         snake_case						=   "Hugging Face大法好，谁用谁知道。"
         snake_case						=   "Hugging Face大法好,谁用谁知道。<unk>"
         snake_case						=   "▁Hu gg ing ▁ ▂ ▁F ace ▁大法 ▁好 ▁ , ▁谁 ▁用 ▁谁 ▁知 道 ▁ 。".split()

         snake_case						=   tokenizer.tokenize(_A  )
         self.assertListEqual(_A							,       _A  )

         snake_case						=   tokens + [tokenizer.unk_token]

         snake_case						=   [1_3_7_8_9, 1_3_2_8_3, 1_4_2_1, 8, 1_0, 1_1_6_4, 1_3_6_0_8, 1_6_5_2_8, 6_3, 8, 9, 4_4_0, 1_0_8, 4_4_0, 1_2_1, 9_0, 8, 1_2, 0]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_A  )							,       _A  )

         snake_case						=   tokenizer.decode(_A  )
         self.assertEqual(_A							,       _A  )

