


import numpy as np


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   Dict      ,						_lowercase    :   Optional[int]="utf-8"      ,						_lowercase    :   List[Any]="surrogatepass" )      ->       List[Any]:




		'''simple docstring'''
		lowercase__				:			int            =		bin(int.from_bytes(text.encode(lowerCAmelCase__      ,						lowerCAmelCase__ )      ,						'big' ) )[2:]
		return bits.zfill(8 * ((len(lowerCAmelCase__ ) + 7) // 8) )


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   Optional[int]      ,						_lowercase    :   List[str]="utf-8"      ,						_lowercase    :   Dict="surrogatepass" )      ->       List[str]:




		'''simple docstring'''
		lowercase__				:			str            =		int(lowerCAmelCase__      ,						2 )
		return n.to_bytes((n.bit_length() + 7) // 8      ,						'big' ).decode(lowerCAmelCase__      ,						lowerCAmelCase__ ) or "\0"


def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   Optional[int]      ,						_lowercase    :   Dict )      ->       Optional[Any]:




		'''simple docstring'''
		if size_par + len(lowerCAmelCase__ ) <= 2**size_par - (len(lowerCAmelCase__ ) - 1):
				raise ValueError('size of parity don\'t match with size of data' )

		lowercase__				:			List[Any]            =		[]
		lowercase__				:			List[str]            =		[]
		lowercase__				:			Any            =		[bin(lowerCAmelCase__ )[2:] for x in range(1      ,						size_par + len(lowerCAmelCase__ ) + 1 )]

		# sorted information data for the size of the output data
		lowercase__				:			Tuple            =		[]
		# data position template + parity
		lowercase__				:			Dict            =		[]
		# parity bit counter
		lowercase__				:			Any            =		0
		# counter position of data bits
		lowercase__				:			Any            =		0

		for x in range(1      ,						size_par + len(lowerCAmelCase__ ) + 1 ):
				# Performs a template of bit positions - who should be given,
				# and who should be parity
				if qtd_bp < size_par:
						if (np.log(lowerCAmelCase__ ) / np.log(2 )).is_integer():
								data_out_gab.append('P' )
								lowercase__				:			Union[str, Any]            =		qtd_bp + 1
						else:
								data_out_gab.append('D' )
				else:
						data_out_gab.append('D' )

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_ord.append(data[cont_data] )
						cont_data += 1
				else:
						data_ord.append(lowerCAmelCase__ )

    # Calculates parity
		lowercase__				:			List[str]            =		0  # parity bit counter
		for bp in range(1      ,						size_par + 1 ):
				# Bit counter one for a given parity
				lowercase__				:			str            =		0
				# counter to control the loop reading
				lowercase__				:			List[str]            =		0
				for x in data_ord:
						if x is not None:
								try:
										lowercase__				:			List[str]            =		(bin_pos[cont_loop])[-1 * (bp)]
								except IndexError:
										lowercase__				:			str            =		'0'
								if aux == "1" and x == "1":
										cont_bo += 1
						cont_loop += 1
				parity.append(cont_bo % 2 )

				qtd_bp += 1

		# Mount the message
		lowercase__				:			Dict            =		0  # parity bit counter
		for x in range(0      ,						size_par + len(lowerCAmelCase__ ) ):
				if data_ord[x] is None:
						data_out.append(str(parity[cont_bp] ) )
						cont_bp += 1
				else:
						data_out.append(data_ord[x] )

		return data_out





def 			SCREAMING_SNAKE_CASE__     (					_lowercase    :   int      ,						_lowercase    :   List[Any] )      ->       List[Any]:




		'''simple docstring'''
		lowercase__				:			str            =		[]
		# Parity bit counter
		lowercase__				:			Any            =		0
		# Counter p data bit reading
		lowercase__				:			Union[str, Any]            =		0
		# list of parity received
		lowercase__				:			Tuple            =		[]
		lowercase__				:			Any            =		[]

		for x in range(1      ,						len(lowerCAmelCase__ ) + 1 ):
				# Performs a template of bit positions - who should be given,
				#  and who should be parity
				if qtd_bp < size_par and (np.log(lowerCAmelCase__ ) / np.log(2 )).is_integer():
						data_out_gab.append('P' )
						lowercase__				:			Any            =		qtd_bp + 1
				else:
						data_out_gab.append('D' )

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_output.append(data[cont_data] )
				else:
						parity_received.append(data[cont_data] )
				cont_data += 1

		# -----------calculates the parity with the data
		lowercase__				:			Optional[Any]            =		[]
		lowercase__				:			Tuple            =		[]
		lowercase__				:			Dict            =		[bin(lowerCAmelCase__ )[2:] for x in range(1      ,						size_par + len(lowerCAmelCase__ ) + 1 )]

		#  sorted information data for the size of the output data
		lowercase__				:			Any            =		[]
		# Data position feedback + parity
		lowercase__				:			Any            =		[]
		# Parity bit counter
		lowercase__				:			Tuple            =		0
		# Counter p data bit reading
		lowercase__				:			Tuple            =		0

		for x in range(1      ,						size_par + len(lowerCAmelCase__ ) + 1 ):
				# Performs a template position of bits - who should be given,
				# and who should be parity
				if qtd_bp < size_par and (np.log(lowerCAmelCase__ ) / np.log(2 )).is_integer():
						data_out_gab.append('P' )
						lowercase__				:			Union[str, Any]            =		qtd_bp + 1
				else:
						data_out_gab.append('D' )

				# Sorts the data to the new output size
				if data_out_gab[-1] == "D":
						data_ord.append(data_output[cont_data] )
						cont_data += 1
				else:
						data_ord.append(lowerCAmelCase__ )

    # Calculates parity
		lowercase__				:			Dict            =		0  # parity bit counter
		for bp in range(1      ,						size_par + 1 ):
				# Bit counter one for a certain parity
				lowercase__				:			Optional[int]            =		0
				# Counter to control loop reading
				lowercase__				:			int            =		0
				for x in data_ord:
						if x is not None:
								try:
										lowercase__				:			Optional[Any]            =		(bin_pos[cont_loop])[-1 * (bp)]
								except IndexError:
										lowercase__				:			int            =		'0'
								if aux == "1" and x == "1":
										cont_bo += 1
						cont_loop += 1
				parity.append(str(cont_bo % 2 ) )

				qtd_bp += 1

		# Mount the message
		lowercase__				:			Dict            =		0  # Parity bit counter
		for x in range(0      ,						size_par + len(lowerCAmelCase__ ) ):
				if data_ord[x] is None:
						data_out.append(str(parity[cont_bp] ) )
						cont_bp += 1
				else:
						data_out.append(data_ord[x] )

		lowercase__				:			List[str]            =		parity_received == parity
		return data_output, ack









from typing import List

import PIL
import torch
from PIL import Image

from ...configuration_utils import ConfigMixin
from ...models.modeling_utils import ModelMixin
from ...utils import PIL_INTERPOLATION


class 			__lowerCAmelCase				(					_UpperCamelCase      ,						_UpperCamelCase			):


	'''simple docstring'''





	def __init__(	self:	Union[str, Any] ):
			super().__init__()

			self.register_buffer('watermark_image',				torch.zeros((62, 62, 4) ) )
			lowercase__				:			int            =		None





	def       snake_case__(	self:	Optional[int],				lowerCamelCase_:	List[PIL.Image.Image],				lowerCamelCase_:	Dict=None ):
			# copied from https://github.com/deep-floyd/IF/blob/b77482e36ca2031cb94dbca1001fc1e6400bf4ab/deepfloyd_if/modules/base.py#L287

			lowercase__				:			str            =		images[0].height
			lowercase__				:			Optional[Any]            =		images[0].width

			lowercase__				:			List[Any]            =		sample_size or h

			lowercase__				:			Any            =		min(h / sample_size,				w / sample_size )
			lowercase__      ,							lowercase__				:			Optional[int]            =		(int(h / coef ), int(w / coef )) if coef < 1 else (h, w)

			lowercase__      ,							lowercase__				:			Any            =		1024**2, img_w * img_h
			lowercase__				:			Union[str, Any]            =		(Sa / Sa) ** 0.5
			lowercase__      ,							lowercase__      ,							lowercase__				:			Optional[int]            =		int(K * 62 ), img_w - int(14 * K ), img_h - int(14 * K )

			if self.watermark_image_as_pil is None:
					lowercase__				:			Tuple            =		self.watermark_image.to(torch.uinta ).cpu().numpy()
					lowercase__				:			str            =		Image.fromarray(lowerCamelCase_,				mode='RGBA' )
					lowercase__				:			Tuple            =		watermark_image

			lowercase__				:			Optional[int]            =		self.watermark_image_as_pil.resize(
			    (wm_size, wm_size),				PIL_INTERPOLATION['bicubic'],				reducing_gap=lowerCamelCase_ )

			for pil_img in images:
					pil_img.paste(lowerCamelCase_,				box=(wm_x - wm_size, wm_y - wm_size, wm_x, wm_y),				mask=wm_img.split()[-1] )

			return images


