




'''simple docstring'''





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

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
		from transformers.pipelines.conversational import Conversation


_SCREAMING_SNAKE_CASE							:   Optional[int]      		= logging.get_logger(__name__)

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

_SCREAMING_SNAKE_CASE							:   Union[str, Any]      		= {
    "tokenizer_file": {
        "EleutherAI/gpt-neox-20b": "https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json",
    },
}

_SCREAMING_SNAKE_CASE							:   int      		= {
    "gpt-neox-20b": 2048,
}




class  _snake_case		(	lowercase_							):
			lowerCAmelCase_     :      str						       =    VOCAB_FILES_NAMES
			lowerCAmelCase_     :      Tuple						       =    PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase_     :      Any						       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase_     :      str						       =    ["input_ids", "attention_mask"]




			def __init__(					self				,							a__=None				,							a__=None				,							a__=None				,							a__="<|endoftext|>"				,							a__="<|endoftext|>"				,							a__="<|endoftext|>"				,							a__=False				,							**a__				,							)				->				Tuple:

										'''simple docstring'''




										super().__init__(
										    a__				,							a__				,							tokenizer_file=a__				,							unk_token=a__				,							bos_token=a__				,							eos_token=a__				,							add_prefix_space=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




			def    lowerCAmelCase__				(					self				,							a__				,							a__ = None							)				->				Tuple[str]:

										'''simple docstring'''




										snake_case_						=      self._tokenizer.model.save(a__				,							name=a__							)
										return tuple(a__							)




			def    lowerCAmelCase__				(					self				,							a__							)				->				List[int]:

										'''simple docstring'''




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

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










import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


__lowerCAmelCase		:				List[Any]       			=		logging.get_logger(__name__)




class     snake_case__							(_UpperCamelCase   ):
				"""simple docstring"""



				def __init__(      self				:     Union[str, Any]					,      *__lowerCamelCase				:     Optional[Any]					,      **__lowerCamelCase				:     Dict							)					->     None:
							warnings.warn(
							    "The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
							    " use DonutImageProcessor instead."					,      __lowerCamelCase					,      )
							super().__init__(*__lowerCamelCase					,      **__lowerCamelCase							)






