






import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
UpperCamelCase 				=	{
    '''E''': 12.70,
    '''T''': 9.06,
    '''A''': 8.17,
    '''O''': 7.51,
    '''I''': 6.97,
    '''N''': 6.75,
    '''S''': 6.33,
    '''H''': 6.09,
    '''R''': 5.99,
    '''D''': 4.25,
    '''L''': 4.03,
    '''C''': 2.78,
    '''U''': 2.76,
    '''M''': 2.41,
    '''W''': 2.36,
    '''F''': 2.23,
    '''G''': 2.02,
    '''Y''': 1.97,
    '''P''': 1.93,
    '''B''': 1.29,
    '''V''': 0.98,
    '''K''': 0.77,
    '''J''': 0.15,
    '''X''': 0.15,
    '''Q''': 0.10,
    '''Z''': 0.07,
}
UpperCamelCase 				=	'''ETAOINSHRDLCUMWFGYPBVKJXQZ'''
UpperCamelCase 				=	'''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''

def        __lowerCamelCase			(		snake_case__		)							->  List[Any]:






						"""simple docstring"""





						_SCREAMING_SNAKE_CASE	      =  {letter: 0 for letter in string.ascii_uppercase}
						for letter in message.upper():
												if letter in LETTERS:
																		letter_count[letter] += 1

						return letter_count

def        __lowerCamelCase			(		snake_case__		)							->  List[Any]:






						"""simple docstring"""





						return x[0]

def        __lowerCamelCase			(		snake_case__		)							->  Dict:






						"""simple docstring"""





						_SCREAMING_SNAKE_CASE	      =  get_letter_count(A__		)
						_SCREAMING_SNAKE_CASE	      =  {
						    freq: [] for letter, freq in letter_to_freq.items()
						}
						for letter in LETTERS:
												freq_to_letter[letter_to_freq[letter]].append(A__		)

						_SCREAMING_SNAKE_CASE	      =  {}

						for freq in freq_to_letter:
												freq_to_letter[freq].sort(key=ETAOIN.find       ,reverse=A__		)
												_SCREAMING_SNAKE_CASE	      =  "".join(freq_to_letter[freq]		)

						_SCREAMING_SNAKE_CASE	      =  list(freq_to_letter_str.items()		)
						freq_pairs.sort(key=A__       ,reverse=A__		)

						_SCREAMING_SNAKE_CASE	      =  [freq_pair[1] for freq_pair in freq_pairs]

						return "".join(A__		)

def        __lowerCamelCase			(		snake_case__		)							->  Optional[int]:






						"""simple docstring"""





						_SCREAMING_SNAKE_CASE	      =  get_frequency_order(A__		)
						_SCREAMING_SNAKE_CASE	      =  0
						for common_letter in ETAOIN[:6]:
												if common_letter in freq_order[:6]:
																		match_score += 1

						for uncommon_letter in ETAOIN[-6:]:
												if uncommon_letter in freq_order[-6:]:
																		match_score += 1

						return match_score


if __name__ == "__main__":
		import doctest

		doctest.testmod()









"""simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


lowerCamelCase_					=      logging.get_logger(__name__)  # pylint: disable=invalid-name







class 			UpperCamelCase_       (__A     ):





	def __init__(      self					: Optional[int]	,	lowerCAmelCase_					: List[Any]	,	lowerCAmelCase_					: Dict=768						)						->			List[Any]:
				super().__init__(lowerCAmelCase_						)
				UpperCAmelCase_     : Dict			     =					proj_size

				UpperCAmelCase_     : Optional[Any]			     =					CLIPVisionModel(lowerCAmelCase_						)
				UpperCAmelCase_     : Tuple			     =					PaintByExampleMapper(lowerCAmelCase_						)
				UpperCAmelCase_     : str			     =					nn.LayerNorm(config.hidden_size						)
				UpperCAmelCase_     : List[Any]			     =					nn.Linear(config.hidden_size	,	self.proj_size						)

				# uncondition for scaling
				UpperCAmelCase_     : Optional[int]			     =					nn.Parameter(torch.randn((1, 1, self.proj_size)						)						)





	def      _SCREAMING_SNAKE_CASE      (      self					: int	,	lowerCAmelCase_					: int	,	lowerCAmelCase_					: Dict=False						)						->			Union[str, Any]:
				UpperCAmelCase_     : Optional[int]			     =					self.model(pixel_values=lowerCAmelCase_						)
				UpperCAmelCase_     : Optional[Any]			     =					clip_output.pooler_output
				UpperCAmelCase_     : List[Any]			     =					self.mapper(latent_states[:, None]						)
				UpperCAmelCase_     : List[str]			     =					self.final_layer_norm(lowerCAmelCase_						)
				UpperCAmelCase_     : Union[str, Any]			     =					self.proj_out(lowerCAmelCase_						)
				if return_uncond_vector:
							return latent_states, self.uncond_vector

				return latent_states







class 			UpperCamelCase_       (nn.Module     ):





	def __init__(      self					: Dict	,	lowerCAmelCase_					: Union[str, Any]						)						->			Tuple:
				super().__init__()
				UpperCAmelCase_     : List[Any]			     =					(config.num_hidden_layers + 1) // 5
				UpperCAmelCase_     : Optional[Any]			     =					config.hidden_size
				UpperCAmelCase_     : List[str]			     =					1
				UpperCAmelCase_     : Union[str, Any]			     =					nn.ModuleList(
				    [
				        BasicTransformerBlock(lowerCAmelCase_	,	lowerCAmelCase_	,	lowerCAmelCase_	,	activation_fn="gelu"	,	attention_bias=lowerCAmelCase_						)
				        for _ in range(lowerCAmelCase_						)
				    ]						)





	def      _SCREAMING_SNAKE_CASE      (      self					: List[str]	,	lowerCAmelCase_					: List[str]						)						->			str:
				for block in self.blocks:
							UpperCAmelCase_     : int			     =					block(lowerCAmelCase_						)

				return hidden_states



