



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


lowerCamelCase		       =      logging.get_logger(__name__)

lowerCamelCase		       =      {"""tokenizer_file""": """tokenizer.json"""}

lowerCamelCase		       =      {
    """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 				_a						(       SCREAMING_SNAKE_CASE			):





							'''simple docstring'''

							A				:Optional[int] =       VOCAB_FILES_NAMES
							A				:Union[str, Any] =       PRETRAINED_VOCAB_FILES_MAP
							A				:Tuple =       ["input_ids", "attention_mask"]
							A				:int =       None



							def __init__(							self ,					__UpperCAmelCase=None ,					__UpperCAmelCase=None ,					__UpperCAmelCase=None ,					__UpperCAmelCase="<unk>" ,					__UpperCAmelCase="<s>" ,					__UpperCAmelCase="</s>" ,					__UpperCAmelCase="<pad>" ,					__UpperCAmelCase=False ,					__UpperCAmelCase=False ,					**__UpperCAmelCase ,					):







											"""simple docstring"""



											super().__init__(
											    __UpperCAmelCase ,					__UpperCAmelCase ,					tokenizer_file=__UpperCAmelCase ,					unk_token=__UpperCAmelCase ,					bos_token=__UpperCAmelCase ,					eos_token=__UpperCAmelCase ,					pad_token=__UpperCAmelCase ,					add_prefix_space=__UpperCAmelCase ,					clean_up_tokenization_spaces=__UpperCAmelCase ,					**__UpperCAmelCase ,					)
											a__	:							List[str]      						= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()				)
											if pre_tok_state.get("add_prefix_space" ,					__UpperCAmelCase				) != add_prefix_space:
															a__	:							Tuple      						= getattr(__UpperCAmelCase ,					pre_tok_state.pop("type"				)				)
															a__	:							str      						= add_prefix_space
															a__	:							Union[str, Any]      						= pre_tok_class(**__UpperCAmelCase				)

											a__	:							List[str]      						= add_prefix_space



							def 		_A	(							self ,					*__UpperCAmelCase ,					**__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							List[Any]      						= kwargs.get("is_split_into_words" ,					__UpperCAmelCase				)
											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(*__UpperCAmelCase ,					**__UpperCAmelCase				)



							def 		_A	(							self ,					*__UpperCAmelCase ,					**__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							Tuple      						= kwargs.get("is_split_into_words" ,					__UpperCAmelCase				)

											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(*__UpperCAmelCase ,					**__UpperCAmelCase				)



							def 		_A	(							self ,					__UpperCAmelCase ,					__UpperCAmelCase = None				):







											"""simple docstring"""



											a__	:							List[Any]      						= self._tokenizer.model.save(__UpperCAmelCase ,					name=__UpperCAmelCase				)
											return tuple(__UpperCAmelCase				)




							def 		_A	(							self ,					__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							Union[str, Any]      						= []
											for is_user, text in conversation.iter_texts():
															input_ids.extend(self.encode(__UpperCAmelCase ,					add_special_tokens=__UpperCAmelCase				) + [self.eos_token_id]				)

											if len(__UpperCAmelCase				) > self.model_max_length:
															a__	:							Union[str, Any]      						= input_ids[-self.model_max_length :]
											return input_ids







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_speech_available,
    is_torch_available,
)


lowerCamelCase		       =      {
    """configuration_trocr""": ["""TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TrOCRConfig"""],
    """processing_trocr""": ["""TrOCRProcessor"""],
}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase		       =      [
						    """TROCR_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """TrOCRForCausalLM""",
						    """TrOCRPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_trocr import TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP, TrOCRConfig
						from .processing_trocr import TrOCRProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_trocr import TROCR_PRETRAINED_MODEL_ARCHIVE_LIST, TrOCRForCausalLM, TrOCRPreTrainedModel

else:
						import sys

						lowerCamelCase		       =      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


