




"""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


UpperCamelCase__						=			logging.get_logger(__name__)

UpperCamelCase__						=			{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

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

UpperCamelCase__						=			{
    '''gpt-neox-20b''': 2_0_4_8,
}




class   a__			(       UpperCamelCase_  ):
						snake_case__             = VOCAB_FILES_NAMES
						snake_case__             = PRETRAINED_VOCAB_FILES_MAP
						snake_case__             = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						snake_case__             = ['''input_ids''', '''attention_mask''']





						def __init__(							self      :	str     ,a__      :	List[str]=None     ,a__      :	Any=None     ,a__      :	Any=None     ,a__      :	List[Any]="<|endoftext|>"     ,a__      :	Optional[Any]="<|endoftext|>"     ,a__      :	List[str]="<|endoftext|>"     ,a__      :	List[str]=False     ,**a__      :	int     ,)						->       Union[str, Any]:




											"""simple docstring"""







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

											_lowerCAmelCase:Optional[Any]									=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
											if pre_tok_state.get('''add_prefix_space'''     ,a__) != add_prefix_space:
																_lowerCAmelCase:Union[str, Any]									=  getattr(a__     ,pre_tok_state.pop('''type'''))
																_lowerCAmelCase:str									=  add_prefix_space
																_lowerCAmelCase:Optional[int]									=  pre_tok_class(**a__)

											_lowerCAmelCase:int									=  add_prefix_space





						def       __UpperCamelCase     (							self      :	List[Any]     ,a__      :	str     ,a__      :	Optional[str] = None)						->       Tuple[str]:




											"""simple docstring"""







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







						def       __UpperCamelCase     (							self      :	int     ,a__      :	"Conversation")						->       List[int]:




											"""simple docstring"""







											_lowerCAmelCase:Dict									=  []
											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:
																_lowerCAmelCase:Optional[Any]									=  input_ids[-self.model_max_length :]
											return input_ids












"""simple docstring"""






from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import torch

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available




@dataclass
class   a__			(       UpperCamelCase_  ):
						snake_case__             = 42


try:
				if not (is_transformers_available() and is_torch_available()):
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
				from .pipeline_text_to_video_synth import TextToVideoSDPipeline
				from .pipeline_text_to_video_synth_imgaimg import VideoToVideoSDPipeline  # noqa: F401
				from .pipeline_text_to_video_zero import TextToVideoZeroPipeline






