






"""simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCamelCase_     :   Tuple       			=   0b101100111110110010010000011110111011000110011110
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
lowerCamelCase_     :   Dict       			=   [int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]







class     UpperCamelCase_ :





	def __init__(   self      :				Optional[int]		)		->    int:
				UpperCAmelCase_  :				Union[str, Any]      =      WATERMARK_BITS
				UpperCAmelCase_  :				List[str]      =      WatermarkEncoder()

				self.encoder.set_watermark("bits"			,			self.watermark		)





	def   _SCREAMING_SNAKE_CASE   (   self      :				Any			,			lowerCAmelCase_      :				torch.FloatTensor		)		->    List[Any]:
				# can't encode images that are smaller than 256
				if images.shape[-1] < 256:
							return images

				UpperCAmelCase_  :				Optional[Any]      =      (255 * (images / 2 + 0.5)).cpu().permute(0			,			2			,			3			,			1		).float().numpy()

				UpperCAmelCase_  :				int      =      [self.encoder.encode(lowerCAmelCase_			,			"dwtDct"		) for image in images]

				UpperCAmelCase_  :				Optional[int]      =      torch.from_numpy(np.array(lowerCAmelCase_		)		).permute(0			,			3			,			1			,			2		)

				UpperCAmelCase_  :				List[str]      =      torch.clamp(2 * (images / 255 - 0.5)			,			min=-1.0			,			max=1.0		)
				return images











"""simple docstring"""
lowerCamelCase_       			=   {
    '''a''': '''AAAAA''',
    '''b''': '''AAAAB''',
    '''c''': '''AAABA''',
    '''d''': '''AAABB''',
    '''e''': '''AABAA''',
    '''f''': '''AABAB''',
    '''g''': '''AABBA''',
    '''h''': '''AABBB''',
    '''i''': '''ABAAA''',
    '''j''': '''BBBAA''',
    '''k''': '''ABAAB''',
    '''l''': '''ABABA''',
    '''m''': '''ABABB''',
    '''n''': '''ABBAA''',
    '''o''': '''ABBAB''',
    '''p''': '''ABBBA''',
    '''q''': '''ABBBB''',
    '''r''': '''BAAAA''',
    '''s''': '''BAAAB''',
    '''t''': '''BAABA''',
    '''u''': '''BAABB''',
    '''v''': '''BBBAB''',
    '''w''': '''BABAA''',
    '''x''': '''BABAB''',
    '''y''': '''BABBA''',
    '''z''': '''BABBB''',
    ''' ''': ''' ''',
}


lowerCamelCase_       			=   {value: key for key, value in encode_dict.items()}

def        snake_case   (     A__		):
			UpperCAmelCase_  :				Union[str, Any]      =      ""
			for letter in word.lower():
						if letter.isalpha() or letter == " ":
									encoded += encode_dict[letter]
						else:
									raise Exception("encode() accepts only letters of the alphabet and spaces"		)
			return encoded

def        snake_case   (     A__		):
			if set(A__		) - {"A", "B", " "} != set():
						raise Exception("decode() accepts only 'A', 'B' and spaces"		)
			UpperCAmelCase_  :				Dict      =      ""
			for word in coded.split():
						while len(A__		) != 0:
									decoded += decode_dict[word[:5]]
									UpperCAmelCase_  :				str      =      word[5:]
						decoded += " "
			return decoded.strip()


if __name__ == "__main__":
			from doctest import testmod

			testmod()



