






'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


a_ 		=       logging.get_logger(__name__)


a_ 		=       {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all BART models at https://huggingface.co/models?filter=bart
a_ 		=       {
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
}

a_ 		=       {
    "facebook/bart-base": 1_0_2_4,
    "facebook/bart-large": 1_0_2_4,
    "facebook/bart-large-mnli": 1_0_2_4,
    "facebook/bart-large-cnn": 1_0_2_4,
    "facebook/bart-large-xsum": 1_0_2_4,
    "yjernite/bart_eli5": 1_0_2_4,
}





@lru_cache()
def        _a(     ):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__   : int													=(
          list(range(ord('''!'''							),		ord('''~'''							) + 1							)							) + list(range(ord('''¡'''							),		ord('''¬'''							) + 1							)							) + list(range(ord('''®'''							),		ord('''ÿ'''							) + 1							)							)
      )
      SCREAMING_SNAKE_CASE__   : str													=bs[:]
      SCREAMING_SNAKE_CASE__   : Dict													=0
      for b in range(2**8							):
            if b not in bs:
                  bs.append(_UpperCamelCase							)
                  cs.append(2**8 + n							)
                  n += 1
      SCREAMING_SNAKE_CASE__   : List[Any]													=[chr(_UpperCamelCase							) for n in cs]
      return dict(zip(_UpperCamelCase,		_UpperCamelCase							)							)





def        _a(     UpperCamelCase__ :  Optional[int]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__   : List[Any]													=set()
      SCREAMING_SNAKE_CASE__   : str													=word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)							)
            SCREAMING_SNAKE_CASE__   : Optional[Any]													=char
      return pairs







class    __SCREAMING_SNAKE_CASE					(	A__ ):
 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    ,					__lowercase		:							Optional[int]    ,					__lowercase		:							Optional[int]    ,					__lowercase		:							List[str]="replace"    ,					__lowercase		:							List[str]="<s>"    ,					__lowercase		:							int="</s>"    ,					__lowercase		:							List[Any]="</s>"    ,					__lowercase		:							Optional[Any]="<s>"    ,					__lowercase		:							Any="<unk>"    ,					__lowercase		:							Optional[int]="<pad>"    ,					__lowercase		:							int="<mask>"    ,					__lowercase		:							List[str]=False    ,					**__lowercase		:							Tuple    ,					)		->  Any:
       SCREAMING_SNAKE_CASE__   : int													=AddedToken(_a    ,					lstrip=_a    ,					rstrip=_a					) if isinstance(_a    ,					_a					) else bos_token
       SCREAMING_SNAKE_CASE__   : List[str]													=AddedToken(_a    ,					lstrip=_a    ,					rstrip=_a					) if isinstance(_a    ,					_a					) else eos_token
       SCREAMING_SNAKE_CASE__   : Union[str, Any]													=AddedToken(_a    ,					lstrip=_a    ,					rstrip=_a					) if isinstance(_a    ,					_a					) else sep_token
       SCREAMING_SNAKE_CASE__   : str													=AddedToken(_a    ,					lstrip=_a    ,					rstrip=_a					) if isinstance(_a    ,					_a					) else cls_token
       SCREAMING_SNAKE_CASE__   : int													=AddedToken(_a    ,					lstrip=_a    ,					rstrip=_a					) if isinstance(_a    ,					_a					) else unk_token
       SCREAMING_SNAKE_CASE__   : int													=AddedToken(_a    ,					lstrip=_a    ,					rstrip=_a					) if isinstance(_a    ,					_a					) else pad_token

       # Mask token behave like a normal word, i.e. include the space before it
       SCREAMING_SNAKE_CASE__   : Union[str, Any]													=AddedToken(_a    ,					lstrip=_a    ,					rstrip=_a					) if isinstance(_a    ,					_a					) else mask_token

       super().__init__(
           errors=_a    ,					bos_token=_a    ,					eos_token=_a    ,					unk_token=_a    ,					sep_token=_a    ,					cls_token=_a    ,					pad_token=_a    ,					mask_token=_a    ,					add_prefix_space=_a    ,					**_a    ,					)

       with open(_a    ,					encoding='''utf-8'''					) as vocab_handle:
             SCREAMING_SNAKE_CASE__   : List[str]													=json.load(_a					)
       SCREAMING_SNAKE_CASE__   : str													={v: k for k, v in self.encoder.items()}
       SCREAMING_SNAKE_CASE__   : Dict													=errors  # how to handle errors in decoding
       SCREAMING_SNAKE_CASE__   : List[str]													=bytes_to_unicode()
       SCREAMING_SNAKE_CASE__   : Tuple													={v: k for k, v in self.byte_encoder.items()}
       with open(_a    ,					encoding='''utf-8'''					) as merges_handle:
             SCREAMING_SNAKE_CASE__   : str													=merges_handle.read().split('''\n'''					)[1:-1]
       SCREAMING_SNAKE_CASE__   : Optional[Any]													=[tuple(merge.split()					) for merge in bpe_merges]
       SCREAMING_SNAKE_CASE__   : List[Any]													=dict(zip(_a    ,					range(len(_a					)					)					)					)
       SCREAMING_SNAKE_CASE__   : int													={}
       SCREAMING_SNAKE_CASE__   : Union[str, Any]													=add_prefix_space

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       SCREAMING_SNAKE_CASE__   : str													=re.compile(r'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''					)




 @property
 def    __magic_name__		(					self		:							Any					)		->  str:
       return len(self.encoder					)




 def    __magic_name__		(					self		:							Optional[Any]					)		->  Union[str, Any]:
       return dict(self.encoder    ,					**self.added_tokens_encoder					)




 def    __magic_name__		(					self		:							Union[str, Any]    ,					__lowercase		:							Tuple					)		->  str:






       if token in self.cache:
             return self.cache[token]
       SCREAMING_SNAKE_CASE__   : str													=tuple(_a					)
       SCREAMING_SNAKE_CASE__   : Tuple													=get_pairs(_a					)

       if not pairs:
             return token

       while True:
             SCREAMING_SNAKE_CASE__   : Any													=min(_a    ,					key=lambda __lowercase					: self.bpe_ranks.get(_a    ,					float('''inf'''					)					)					)
             if bigram not in self.bpe_ranks:
                   break
             SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__   : Optional[Any]													=bigram
             SCREAMING_SNAKE_CASE__   : List[str]													=[]
             SCREAMING_SNAKE_CASE__   : Union[str, Any]													=0
             while i < len(_a					):
                   try:
                         SCREAMING_SNAKE_CASE__   : List[Any]													=word.index(_a    ,					_a					)
                   except ValueError:
                         new_word.extend(word[i:]					)
                         break
                   else:
                         new_word.extend(word[i:j]					)
                         SCREAMING_SNAKE_CASE__   : int													=j

                   if word[i] == first and i < len(_a					) - 1 and word[i + 1] == second:
                         new_word.append(first + second					)
                         i += 2
                   else:
                         new_word.append(word[i]					)
                         i += 1
             SCREAMING_SNAKE_CASE__   : Dict													=tuple(_a					)
             SCREAMING_SNAKE_CASE__   : int													=new_word
             if len(_a					) == 1:
                   break
             else:
                   SCREAMING_SNAKE_CASE__   : Dict													=get_pairs(_a					)
       SCREAMING_SNAKE_CASE__   : List[Any]													=''' '''.join(_a					)
       SCREAMING_SNAKE_CASE__   : str													=word
       return word




 def    __magic_name__		(					self		:							Optional[Any]    ,					__lowercase		:							int					)		->  Tuple:
       SCREAMING_SNAKE_CASE__   : Union[str, Any]													=[]
       for token in re.findall(self.pat    ,					_a					):
             SCREAMING_SNAKE_CASE__   : Union[str, Any]													=''''''.join(
                 self.byte_encoder[b] for b in token.encode('''utf-8'''					)					)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
             bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_a					).split(''' '''					)					)
       return bpe_tokens




 def    __magic_name__		(					self		:							Dict    ,					__lowercase		:							List[str]					)		->  int:
       return self.encoder.get(_a    ,					self.encoder.get(self.unk_token					)					)




 def    __magic_name__		(					self		:							Dict    ,					__lowercase		:							List[str]					)		->  Tuple:
       return self.decoder.get(_a					)




 def    __magic_name__		(					self		:							int    ,					__lowercase		:							Any					)		->  List[str]:
       SCREAMING_SNAKE_CASE__   : Any													=''''''.join(_a					)
       SCREAMING_SNAKE_CASE__   : List[Any]													=bytearray([self.byte_decoder[c] for c in text]					).decode('''utf-8'''    ,					errors=self.errors					)
       return text




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






       if not os.path.isdir(_a					):
             logger.error(F"Vocabulary path ({save_directory}) should be a directory"					)
             return
       SCREAMING_SNAKE_CASE__   : Optional[Any]													=os.path.join(
           _a    ,					(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)
       SCREAMING_SNAKE_CASE__   : List[Any]													=os.path.join(
           _a    ,					(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']					)

       with open(_a    ,					'''w'''    ,					encoding='''utf-8'''					) as f:
             f.write(json.dumps(self.encoder    ,					indent=2    ,					sort_keys=_a    ,					ensure_ascii=_a					) + '''\n'''					)

       SCREAMING_SNAKE_CASE__   : List[Any]													=0
       with open(_a    ,					'''w'''    ,					encoding='''utf-8'''					) as writer:
             writer.write('''#version: 0.2\n'''					)
             for bpe_tokens, token_index in sorted(self.bpe_ranks.items()    ,					key=lambda __lowercase					: kv[1]					):
                   if index != token_index:
                         logger.warning(
                             F"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
                             ''' Please check that the tokenizer is not corrupted!'''					)
                         SCREAMING_SNAKE_CASE__   : str													=token_index
                   writer.write(''' '''.join(_a					) + '''\n'''					)
                   index += 1

       return vocab_file, merge_file




 def    __magic_name__		(					self		:							Tuple    ,					__lowercase		:							List[int]    ,					__lowercase		:							Optional[List[int]] = None					)		->  List[int]:






       if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       SCREAMING_SNAKE_CASE__   : List[Any]													=[self.cls_token_id]
       SCREAMING_SNAKE_CASE__   : Optional[Any]													=[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep




 def    __magic_name__		(					self		:							Optional[int]    ,					__lowercase		:							List[int]    ,					__lowercase		:							Optional[List[int]] = None    ,					__lowercase		:							bool = False					)		->  List[int]:






       if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=_a    ,					token_ids_a=_a    ,					already_has_special_tokens=_a					)

       if token_ids_a is None:
             return [1] + ([0] * len(_a					)) + [1]
       return [1] + ([0] * len(_a					)) + [1, 1] + ([0] * len(_a					)) + [1]




 def    __magic_name__		(					self		:							Any    ,					__lowercase		:							List[int]    ,					__lowercase		:							Optional[List[int]] = None					)		->  List[int]:
       SCREAMING_SNAKE_CASE__   : Tuple													=[self.sep_token_id]
       SCREAMING_SNAKE_CASE__   : Any													=[self.cls_token_id]

       if token_ids_a is None:
             return len(cls + token_ids_a + sep					) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep					) * [0]




 def    __magic_name__		(					self		:							List[Any]    ,					__lowercase		:							Tuple    ,					__lowercase		:							List[Any]=False    ,					**__lowercase		:							Optional[int]					)		->  int:
       SCREAMING_SNAKE_CASE__   : Any													=kwargs.pop('''add_prefix_space'''    ,					self.add_prefix_space					)
       if (is_split_into_words or add_prefix_space) and (len(_a					) > 0 and not text[0].isspace()):
             SCREAMING_SNAKE_CASE__   : List[str]													=''' ''' + text
       return (text, kwargs)


'''simple docstring'''
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device


lowerCamelCase :      Optional[int]					 =     False







class 							A__    (       unittest.TestCase  ):
  pass







@slow
@require_torch_gpu
class 							A__    (       unittest.TestCase  ):





  def 						A  (		self      :	Tuple )	->    Dict:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =VersatileDiffusionImageVariationPipeline.from_pretrained('shi-labs/versatile-diffusion' )
       pipe.to(_a )
       pipe.set_progress_bar_config(disable=_a )

       _SCREAMING_SNAKE_CASE							    =load_image(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg' )
       _SCREAMING_SNAKE_CASE							    =torch.manual_seed(0 )
       _SCREAMING_SNAKE_CASE							    =pipe(
           image=_a							,					generator=_a							,					guidance_scale=7.5							,					num_inference_steps=50							,					output_type='numpy'							,					).images

       _SCREAMING_SNAKE_CASE							    =image[0, 253:256, 253:256, -1]

       assert image.shape == (1, 512, 512, 3)
       _SCREAMING_SNAKE_CASE							    =np.array([0.04_41, 0.04_69, 0.05_07, 0.05_75, 0.06_32, 0.06_50, 0.08_65, 0.09_09, 0.09_45] )

       assert np.abs(image_slice.flatten() - expected_slice ).max() < 1e-2
