





'''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


lowerCAmelCase					:     Union[str, Any]												=logging.get_logger(__name__)

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

lowerCAmelCase					:     str												={
    '''tokenizer_file''': {
        '''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/tokenizer.json''',
    },
}

lowerCAmelCase					:     List[str]												={
    '''gpt-neox-20b''': 2_048,
}
class       a_   (				_lowerCAmelCase							):
     __A      =			VOCAB_FILES_NAMES
     __A      =			PRETRAINED_VOCAB_FILES_MAP
     __A      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __A      =			["input_ids", "attention_mask"]





     def __init__( self		:					Union[str, Any]	,      lowercase		:					Any=None	,      lowercase		:					List[Any]=None	,      lowercase		:					str=None	,      lowercase		:					List[Any]="<|endoftext|>"	,      lowercase		:					Union[str, Any]="<|endoftext|>"	,      lowercase		:					Tuple="<|endoftext|>"	,      lowercase		:					List[str]=False	,      **lowercase		:					List[Any]	,      ):





        """simple docstring"""




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

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

        lowercase_			:Dict    			= add_prefix_space





     def 							lowercase__      ( self		:					List[str]	,      lowercase		:					str	,      lowercase		:					Optional[str] = None						):





        """simple docstring"""




        lowercase_			:Tuple    			= self._tokenizer.model.save(lowercase	,      name=lowercase						)
        return tuple(lowercase						)







     def 							lowercase__      ( self		:					Union[str, Any]	,      lowercase		:					"Conversation"						):





        """simple docstring"""




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

        if len(lowercase						) > self.model_max_length:
           lowercase_			:int    			= input_ids[-self.model_max_length :]
        return input_ids









'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCAmelCase					:     Optional[Any]												={
    '''configuration_x_clip''': [
        '''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XCLIPConfig''',
        '''XCLIPTextConfig''',
        '''XCLIPVisionConfig''',
    ],
    '''processing_x_clip''': ['''XCLIPProcessor'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase					:     Tuple												=[
     '''XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''XCLIPModel''',
     '''XCLIPPreTrainedModel''',
     '''XCLIPTextModel''',
     '''XCLIPVisionModel''',
 ]

if TYPE_CHECKING:
 from .configuration_x_clip import (
     XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
     XCLIPConfig,
     XCLIPTextConfig,
     XCLIPVisionConfig,
 )
 from .processing_x_clip import XCLIPProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_x_clip import (
      XCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
      XCLIPModel,
      XCLIPPreTrainedModel,
      XCLIPTextModel,
      XCLIPVisionModel,
  )

else:
 import sys

 lowerCAmelCase					:     str												=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


