code: 
  
  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     lowerCamelCase_			(  _lowercase  ):
  	_lowercase		:      Optional[int]    				=							{
  	    '''sld_warmup_steps''': 15,
  	    '''sld_guidance_scale''': 20,
  	    '''sld_threshold''': 0.0,
  	    '''sld_momentum_scale''': 0.0,
  	    '''sld_mom_beta''': 0.0,
  	}
  	_lowercase		:      List[Any]    				=							{
  	    '''sld_warmup_steps''': 10,
  	    '''sld_guidance_scale''': 1000,
  	    '''sld_threshold''': 0.01,
  	    '''sld_momentum_scale''': 0.3,
  	    '''sld_mom_beta''': 0.4,
  	}
  	_lowercase		:      List[Any]    				=							{
  	    '''sld_warmup_steps''': 7,
  	    '''sld_guidance_scale''': 2000,
  	    '''sld_threshold''': 0.0_25,
  	    '''sld_momentum_scale''': 0.5,
  	    '''sld_mom_beta''': 0.7,
  	}
  	_lowercase		:      Dict    				=							{
  	    '''sld_warmup_steps''': 0,
  	    '''sld_guidance_scale''': 5000,
  	    '''sld_threshold''': 1.0,
  	    '''sld_momentum_scale''': 0.5,
  	    '''sld_mom_beta''': 0.7,
  	}
  
  
  
  
  
  
  @dataclass
  class     lowerCamelCase_			(  _lowercase  ):
  	_lowercase		:      Union[List[PIL.Image.Image], np.ndarray]
  	_lowercase		:      Optional[List[bool]]
  	_lowercase		:      Optional[Union[List[PIL.Image.Image], np.ndarray]]
  	_lowercase		:      Optional[str]
  
  
  if is_transformers_available() and is_torch_available():
  			from .pipeline_stable_diffusion_safe import StableDiffusionPipelineSafe
  			from .safety_checker import SafeStableDiffusionSafetyChecker
  
  
  
  
  
  
style_context: 
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  UpperCAmelCase_       :				Optional[Any]		   =      logging.get_logger(__name__)
  
  UpperCAmelCase_       :				List[str]		   =      {
      '''uw-madison/nystromformer-512''': '''https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json''',
      # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
  }
  
  
  
  
  
  
  class     lowerCamelCase_			(  _lowercase  ):
  	_lowercase		:      Optional[Any]    				=							'''nystromformer'''
  
  
  
  
  	def __init__(    self	:    Optional[Any]				,			__A	:    Optional[Any]=3_0000				,			__A	:    Optional[int]=768				,			__A	:    List[str]=12				,			__A	:    str=12				,			__A	:    Tuple=3072				,			__A	:    List[Any]="gelu_new"				,			__A	:    Dict=0.1				,			__A	:    Optional[int]=0.1				,			__A	:    int=510				,			__A	:    Union[str, Any]=2				,			__A	:    Optional[int]=64				,			__A	:    str=64				,			__A	:    List[str]=65				,			__A	:    Tuple=False				,			__A	:    List[str]=0.0_2				,			__A	:    Tuple=1e-5				,			__A	:    List[str]=1				,			__A	:    int=0				,			__A	:    Tuple=2				,			**__A	:    Dict				,			):
  		__A   : str								= vocab_size
  		__A   : Union[str, Any]								= max_position_embeddings
  		__A   : Optional[int]								= hidden_size
  		__A   : Optional[int]								= num_hidden_layers
  		__A   : List[Any]								= num_attention_heads
  		__A   : Dict								= intermediate_size
  		__A   : Union[str, Any]								= hidden_act
  		__A   : int								= hidden_dropout_prob
  		__A   : Tuple								= attention_probs_dropout_prob
  		__A   : Optional[Any]								= initializer_range
  		__A   : int								= type_vocab_size
  		__A   : Optional[int]								= segment_means_seq_len
  		__A   : List[str]								= num_landmarks
  		__A   : Dict								= conv_kernel_size
  		__A   : Union[str, Any]								= inv_coeff_init_option
  		__A   : Union[str, Any]								= layer_norm_eps
  		super().__init__(pad_token_id=__A				,			bos_token_id=__A				,			eos_token_id=__A				,			**__A       )
  
  
  
  
  
  