


"""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			=							logging.get_logger(__name__)

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

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

__lowerCAmelCase			=							{
    '''gpt-neox-20b''': 20_48,
}





class   __a      (   __UpperCamelCase				):
 __lowercase			:							Optional[int]       					=			VOCAB_FILES_NAMES
 __lowercase			:							Tuple       					=			PRETRAINED_VOCAB_FILES_MAP
 __lowercase			:							Tuple       					=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowercase			:							Any       					=			['input_ids', 'attention_mask']
 def __init__(       self    ,			lowerCAmelCase__=None    ,			lowerCAmelCase__=None    ,			lowerCAmelCase__=None    ,			lowerCAmelCase__="<|endoftext|>"    ,			lowerCAmelCase__="<|endoftext|>"    ,			lowerCAmelCase__="<|endoftext|>"    ,			lowerCAmelCase__=False    ,			**lowerCAmelCase__    ,			) ->    Optional[int]:




        '''simple docstring'''
        super().__init__(
            lowerCAmelCase__    ,			lowerCAmelCase__    ,			tokenizer_file=lowerCAmelCase__    ,			unk_token=lowerCAmelCase__    ,			bos_token=lowerCAmelCase__    ,			eos_token=lowerCAmelCase__    ,			add_prefix_space=lowerCAmelCase__    ,			**lowerCAmelCase__    ,			)

        lowercase__:       Any        =       json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
        if pre_tok_state.get('add_prefix_space'    ,			lowerCAmelCase__			) != add_prefix_space:
               lowercase__:       int        =       getattr(lowerCAmelCase__    ,			pre_tok_state.pop('type'			)			)
               lowercase__:       Any        =       add_prefix_space
               lowercase__:       int        =       pre_tok_class(**lowerCAmelCase__			)

        lowercase__:       Optional[int]        =       add_prefix_space
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__    ,			lowerCAmelCase__ = None			) ->    Tuple[str]:




        '''simple docstring'''
        lowercase__:       int        =       self._tokenizer.model.save(lowerCAmelCase__    ,			name=lowerCAmelCase__			)
        return tuple(lowerCAmelCase__			)
 def 		SCREAMING_SNAKE_CASE__       (       self    ,			lowerCAmelCase__			) ->    List[int]:




        '''simple docstring'''
        lowercase__:       Any        =       []
        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:
               lowercase__:       int        =       input_ids[-self.model_max_length :]
        return input_ids






import torch

from diffusers import StableDiffusionPipeline


__lowerCAmelCase			=							'''path-to-your-trained-model'''
__lowerCAmelCase			=							StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')

__lowerCAmelCase			=							'''A photo of sks dog in a bucket'''
__lowerCAmelCase			=							pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save('''dog-bucket.png''')


