





import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
   from transformers.pipelines.conversational import Conversation


_a				:	Tuple           =       logging.get_logger(__name__)

_a				:	Union[str, Any]           =       {"""tokenizer_file""": """tokenizer.json"""}

_a				:	str           =       {
    """tokenizer_file""": {
        """bigscience/tokenizer""": """https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json""",
        """bigscience/bloom-560m""": """https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json""",
        """bigscience/bloom-1b1""": """https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json""",
        """bigscience/bloom-1b7""": """https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json""",
        """bigscience/bloom-3b""": """https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json""",
        """bigscience/bloom-7b1""": """https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json""",
        """bigscience/bloom""": """https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json""",
    },
}




class 							UpperCamelCase_							(       _a		):







 """simple docstring"""

 A			 =       VOCAB_FILES_NAMES
 A			 =       PRETRAINED_VOCAB_FILES_MAP
 A			 =       ["input_ids", "attention_mask"]
 A			 =       None


 def __init__(   self  ,				UpperCAmelCase=None  ,				UpperCAmelCase=None  ,				UpperCAmelCase=None  ,				UpperCAmelCase="<unk>"  ,				UpperCAmelCase="<s>"  ,				UpperCAmelCase="</s>"  ,				UpperCAmelCase="<pad>"  ,				UpperCAmelCase=False  ,				UpperCAmelCase=False  ,				**UpperCAmelCase  ,				):
       super().__init__(
           __lowerCamelCase  ,				__lowerCamelCase  ,				tokenizer_file=__lowerCamelCase  ,				unk_token=__lowerCamelCase  ,				bos_token=__lowerCamelCase  ,				eos_token=__lowerCamelCase  ,				pad_token=__lowerCamelCase  ,				add_prefix_space=__lowerCamelCase  ,				clean_up_tokenization_spaces=__lowerCamelCase  ,				**__lowerCamelCase  ,				)
       __lowerCamelCase				   =       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
       if pre_tok_state.get("""add_prefix_space"""  ,				__lowerCamelCase							) != add_prefix_space:
             __lowerCamelCase				   =       getattr(__lowerCamelCase  ,				pre_tok_state.pop("""type"""							)							)
             __lowerCamelCase				   =       add_prefix_space
             __lowerCamelCase				   =       pre_tok_class(**__lowerCamelCase							)

       __lowerCamelCase				   =       add_prefix_space


 def 		lowerCamelCase_ (   self  ,				*UpperCAmelCase  ,				**UpperCAmelCase							):
       __lowerCamelCase				   =       kwargs.get("""is_split_into_words"""  ,				__lowerCamelCase							)
       if not (self.add_prefix_space or not is_split_into_words):
             raise Exception(
                 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 		lowerCamelCase_ (   self  ,				*UpperCAmelCase  ,				**UpperCAmelCase							):
       __lowerCamelCase				   =       kwargs.get("""is_split_into_words"""  ,				__lowerCamelCase							)

       if not (self.add_prefix_space or not is_split_into_words):
             raise Exception(
                 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 		lowerCamelCase_ (   self  ,				UpperCAmelCase  ,				UpperCAmelCase = None							):
       __lowerCamelCase				   =       self._tokenizer.model.save(__lowerCamelCase  ,				name=__lowerCamelCase							)
       return tuple(__lowerCamelCase							)



 def 		lowerCamelCase_ (   self  ,				UpperCAmelCase							):
       __lowerCamelCase				   =       []
       for is_user, text in conversation.iter_texts():
             input_ids.extend(self.encode(__lowerCamelCase  ,				add_special_tokens=__lowerCamelCase							) + [self.eos_token_id]							)

       if len(__lowerCamelCase							) > self.model_max_length:
             __lowerCamelCase				   =       input_ids[-self.model_max_length :]
       return input_ids












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__magic_name__  :  List[str]					=       {
    """configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxConfig"""],
    """tokenization_m2m_100""": ["""M2M100Tokenizer"""],
}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  Union[str, Any]					=       [
          """M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """M2M100ForConditionalGeneration""",
          """M2M100Model""",
          """M2M100PreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
      from .tokenization_mam_aaa import MaMaaaTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mam_aaa import (
                M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
                MaMaaaForConditionalGeneration,
                MaMaaaModel,
                MaMaaaPreTrainedModel,
            )


else:
      import sys

      __magic_name__  :  List[str]					=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

