code: from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  lowercase__    :       Optional[int]						=			logging.get_logger(__name__)
  
  lowercase__    :       Any						=			{
      """dandelin/vilt-b32-mlm""": """https://huggingface.co/dandelin/vilt-b32-mlm/blob/main/config.json"""
  }
  
  
  
  
  class      lowercase_						(						_a		):
  	UpperCAmelCase_						:      int     =       """vilt"""
  
  
  	def __init__(							self	,    __SCREAMING_SNAKE_CASE=30522	,    __SCREAMING_SNAKE_CASE=2	,    __SCREAMING_SNAKE_CASE=2	,    __SCREAMING_SNAKE_CASE=40	,    __SCREAMING_SNAKE_CASE=768	,    __SCREAMING_SNAKE_CASE=12	,    __SCREAMING_SNAKE_CASE=12	,    __SCREAMING_SNAKE_CASE=3072	,    __SCREAMING_SNAKE_CASE="gelu"	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=0.0	,    __SCREAMING_SNAKE_CASE=0.0_2	,    __SCREAMING_SNAKE_CASE=1e-12	,    __SCREAMING_SNAKE_CASE=384	,    __SCREAMING_SNAKE_CASE=32	,    __SCREAMING_SNAKE_CASE=3	,    __SCREAMING_SNAKE_CASE=True	,    __SCREAMING_SNAKE_CASE=-1	,    __SCREAMING_SNAKE_CASE=False	,    __SCREAMING_SNAKE_CASE=-1	,    **__SCREAMING_SNAKE_CASE	,    )		->Tuple:
  								super().__init__(tie_word_embeddings=lowerCamelCase__	,    **lowerCamelCase__       )
  
  								lowerCAmelCase				=	vocab_size
  								lowerCAmelCase				=	type_vocab_size
  								lowerCAmelCase				=	modality_type_vocab_size
  								lowerCAmelCase				=	max_position_embeddings
  
  								lowerCAmelCase				=	hidden_size
  								lowerCAmelCase				=	num_hidden_layers
  								lowerCAmelCase				=	num_attention_heads
  								lowerCAmelCase				=	intermediate_size
  								lowerCAmelCase				=	hidden_act
  								lowerCAmelCase				=	hidden_dropout_prob
  								lowerCAmelCase				=	attention_probs_dropout_prob
  								lowerCAmelCase				=	initializer_range
  								lowerCAmelCase				=	layer_norm_eps
  
  								lowerCAmelCase				=	image_size
  								lowerCAmelCase				=	patch_size
  								lowerCAmelCase				=	num_channels
  								lowerCAmelCase				=	qkv_bias
  								lowerCAmelCase				=	max_image_length
  								lowerCAmelCase				=	num_images
  
  
  
  
style_context: from dataclasses import dataclass
  from typing import List, Optional, Union
  
  import numpy as np
  import PIL
  
  from ...utils import BaseOutput, is_invisible_watermark_available, is_torch_available, is_transformers_available
  
  
  
  
  @dataclass
  class      lowercase_						(						UpperCamelCase_		):
  
  
  
  	"""simple docstring"""
  
  
  
  
  
  	UpperCAmelCase_						:      Union[List[PIL.Image.Image], np.ndarray]
  
  
  if is_transformers_available() and is_torch_available() and is_invisible_watermark_available():
  	from .pipeline_stable_diffusion_xl import StableDiffusionXLPipeline
  	from .pipeline_stable_diffusion_xl_imgaimg import StableDiffusionXLImgaImgPipeline
  
  
  
  