


from typing import Dict, List, Optional, Tuple

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


lowerCAmelCase					 =	logging.get_logger(__name__)





class    A					(     A_				):
							UpperCamelCase_     :							Any =['''input_ids''', '''attention_mask''']


							def __init__(self   ,       lowerCAmelCase="[PAD]"   ,       lowerCAmelCase="[BOS]"   ,       lowerCAmelCase="[EOS]"   ,       lowerCAmelCase="[MASK]"   ,       lowerCAmelCase="[CLS]"   ,       lowerCAmelCase="[SEP]"   ,       lowerCAmelCase=2_0_4_8   ,       **lowerCAmelCase   ,       ):
									__lowercase=    AddedToken(lowerCAmelCase   ,       lstrip=lowerCAmelCase   ,       rstrip=lowerCAmelCase      ) if isinstance(lowerCAmelCase   ,       lowerCAmelCase      ) else pad_token
									__lowercase=    AddedToken(lowerCAmelCase   ,       lstrip=lowerCAmelCase   ,       rstrip=lowerCAmelCase      ) if isinstance(lowerCAmelCase   ,       lowerCAmelCase      ) else bos_token
									__lowercase=    AddedToken(lowerCAmelCase   ,       lstrip=lowerCAmelCase   ,       rstrip=lowerCAmelCase      ) if isinstance(lowerCAmelCase   ,       lowerCAmelCase      ) else eos_token
									__lowercase=    AddedToken(lowerCAmelCase   ,       lstrip=lowerCAmelCase   ,       rstrip=lowerCAmelCase      ) if isinstance(lowerCAmelCase   ,       lowerCAmelCase      ) else mask_token
									__lowercase=    AddedToken(lowerCAmelCase   ,       lstrip=lowerCAmelCase   ,       rstrip=lowerCAmelCase      ) if isinstance(lowerCAmelCase   ,       lowerCAmelCase      ) else cls_token
									__lowercase=    AddedToken(lowerCAmelCase   ,       lstrip=lowerCAmelCase   ,       rstrip=lowerCAmelCase      ) if isinstance(lowerCAmelCase   ,       lowerCAmelCase      ) else sep_token

									super().__init__(
									    pad_token=lowerCAmelCase   ,       bos_token=lowerCAmelCase   ,       eos_token=lowerCAmelCase   ,       mask_token=lowerCAmelCase   ,       cls_token=lowerCAmelCase   ,       sep_token=lowerCAmelCase   ,       model_max_length=lowerCAmelCase   ,       **lowerCAmelCase   ,       )

									__lowercase=    2**8  # utf is 8 bits

									# define special tokens dict
									__lowercase=    {
									    self.pad_token: 0,
									    self.bos_token: 1,
									    self.eos_token: 2,
									    self.mask_token: 3,
									    self.cls_token: 4,
									    self.sep_token: 5,
									}
									__lowercase=    len(self.special_tokens_encoder      )
									__lowercase=    {v: k for k, v in self.special_tokens_encoder.items()}


							def     _A (self      ):
									__lowercase=    self.special_tokens_encoder.copy()
									vocab.update(self.added_tokens_encoder      )
									for i in range(self._utf_vocab_size      ):
											__lowercase=    chr(lowerCAmelCase      )
											__lowercase=    i + len(self.special_tokens_encoder      )
									return vocab


							@property
							def     _A (self      ):
									return self._utf_vocab_size + self._num_special_tokens


							def     _A (self   ,       lowerCAmelCase   ,       lowerCAmelCase = None   ,       lowerCAmelCase = False      ):
									if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=lowerCAmelCase   ,       token_ids_a=lowerCAmelCase   ,       already_has_special_tokens=lowerCAmelCase      )

									# normal case: some special tokens
									if token_ids_a is None:
											return [1] + [0] * len(lowerCAmelCase      ) + [1]
									return [1] + ([0] * len(lowerCAmelCase      )) + [1] + ([0] * len(lowerCAmelCase      )) + [1]


							def     _A (self   ,       lowerCAmelCase   ,       lowerCAmelCase = None      ):
									if token_ids_a is None:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
									else:
											return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]


							def     _A (self   ,       lowerCAmelCase      ):
									__lowercase=    [chr(lowerCAmelCase      ) for i in text.encode('utf-8'      )]
									return tokens


							def     _A (self   ,       lowerCAmelCase      ):
									if token in self.special_tokens_encoder:
											__lowercase=    self.special_tokens_encoder[token]
									elif token in self.added_tokens_encoder:
											__lowercase=    self.added_tokens_encoder[token]
									elif len(lowerCAmelCase      ) != 1:
											__lowercase=    self.unk_token_id
									else:
											__lowercase=    ord(lowerCAmelCase      ) + self._num_special_tokens
									return token_id


							def     _A (self   ,       lowerCAmelCase      ):
									if index in self.special_tokens_decoder:
											__lowercase=    self.special_tokens_decoder[index]
									elif index in self.added_tokens_decoder:
											__lowercase=    self.added_tokens_decoder[index]
									else:
											__lowercase=    chr(index - self._num_special_tokens      )
									return token


							def     _A (self   ,       lowerCAmelCase      ):
									__lowercase=    B''
									for token in tokens:
											if token in self.special_tokens_decoder:
													__lowercase=    self.special_tokens_decoder[token].encode('utf-8'      )
											elif token in self.added_tokens_decoder:
													__lowercase=    self.special_tokens_decoder[token].encode('utf-8'      )
											elif token in self.special_tokens_encoder:
													__lowercase=    token.encode('utf-8'      )
											elif token in self.added_tokens_encoder:
													__lowercase=    token.encode('utf-8'      )
											else:
													__lowercase=    bytes([ord(lowerCAmelCase      )]      )
											bstring += tok_string
									__lowercase=    bstring.decode('utf-8'   ,       errors='replace'      )
									return string







							def     _A (self   ,       lowerCAmelCase   ,       lowerCAmelCase = None      ):
									return ()










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

import numpy as np
import PIL
from PIL import Image

from ...utils import BaseOutput, is_torch_available, is_transformers_available





@dataclass
class    A					(     A_				):
							UpperCamelCase_     :							Optional[int] ={
							    '''sld_warmup_steps''': 15,
							    '''sld_guidance_scale''': 20,
							    '''sld_threshold''': 0.0,
							    '''sld_momentum_scale''': 0.0,
							    '''sld_mom_beta''': 0.0,
							}
							UpperCamelCase_     :							Tuple ={
							    '''sld_warmup_steps''': 10,
							    '''sld_guidance_scale''': 1_000,
							    '''sld_threshold''': 0.01,
							    '''sld_momentum_scale''': 0.3,
							    '''sld_mom_beta''': 0.4,
							}
							UpperCamelCase_     :							Union[str, Any] ={
							    '''sld_warmup_steps''': 7,
							    '''sld_guidance_scale''': 2_000,
							    '''sld_threshold''': 0.025,
							    '''sld_momentum_scale''': 0.5,
							    '''sld_mom_beta''': 0.7,
							}
							UpperCamelCase_     :							List[Any] ={
							    '''sld_warmup_steps''': 0,
							    '''sld_guidance_scale''': 5_000,
							    '''sld_threshold''': 1.0,
							    '''sld_momentum_scale''': 0.5,
							    '''sld_mom_beta''': 0.7,
							}





@dataclass
class    A					(     A_				):
							UpperCamelCase_     :							Union[List[PIL.Image.Image], np.ndarray]
							UpperCamelCase_     :							Optional[List[bool]]
							UpperCamelCase_     :							Optional[Union[List[PIL.Image.Image], np.ndarray]]
							UpperCamelCase_     :							Optional[str]


if is_transformers_available() and is_torch_available():
	from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
	from .safety_checker import SafeStableDiffusionSafetyChecker






