


import numpy as np
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:int   ,    lowercase__	:str="utf-8"   ,    lowercase__	:int="surrogatepass"					)							->	str:
						__magic_name__					:				Any				=   bin(int.from_bytes(text.encode(lowercase__   ,    lowercase__					)   ,    'big'					)					)[2:]
						return bits.zfill(8 * ((len(lowercase__					) + 7) // 8)					)
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:Union[str, Any]   ,    lowercase__	:Union[str, Any]="utf-8"   ,    lowercase__	:List[str]="surrogatepass"					)							->	List[Any]:
						__magic_name__					:				Tuple				=   int(lowercase__   ,    2					)
						return n.to_bytes((n.bit_length() + 7) // 8   ,    'big'					).decode(lowercase__   ,    lowercase__					) or "\0"
def 			__SCREAMING_SNAKE_CASE							(					lowercase__	:Union[str, Any]   ,    lowercase__	:Optional[Any]					)							->	List[str]:







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

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

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

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

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

												qtd_bp += 1

						# Mount the message
						__magic_name__					:				Tuple				=   0  # parity bit counter
						for x in range(0   ,    size_par + len(lowercase__					)					):
												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__	:List[str]   ,    lowercase__	:Any					)							->	Optional[int]:
						__magic_name__					:				int				=   []
						# Parity bit counter
						__magic_name__					:				Dict				=   0
						# Counter p data bit reading
						__magic_name__					:				Dict				=   0
						# list of parity received
						__magic_name__					:				int				=   []
						__magic_name__					:				Tuple				=   []

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

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

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

    # Calculates parity
						__magic_name__					:				Optional[Any]				=   0  # parity bit counter
						for bp in range(1   ,    size_par + 1					):
												# Bit counter one for a certain parity
												__magic_name__					:				Any				=   0
												# Counter to control loop reading
												__magic_name__					:				List[Any]				=   0
												for x in data_ord:
																		if x is not None:
																								try:
																														__magic_name__					:				Optional[Any]				=   (bin_pos[cont_loop])[-1 * (bp)]
																								except IndexError:
																														__magic_name__					:				Union[str, Any]				=   '''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
						__magic_name__					:				Optional[Any]				=   0  # Parity bit counter
						for x in range(0   ,    size_par + len(lowercase__					)					):
												if data_ord[x] is None:
																		data_out.append(str(parity[cont_bp]					)					)
																		cont_bp += 1
												else:
																		data_out.append(data_ord[x]					)

						__magic_name__					:				str				=   parity_received == parity
						return data_output, ack





"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A									=						{
    """configuration_imagegpt""": ["""IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ImageGPTConfig""", """ImageGPTOnnxConfig"""]
}

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 A									=						["""ImageGPTFeatureExtractor"""]
 A									=						["""ImageGPTImageProcessor"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 A									=						[
     """IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """ImageGPTForCausalImageModeling""",
     """ImageGPTForImageClassification""",
     """ImageGPTModel""",
     """ImageGPTPreTrainedModel""",
     """load_tf_weights_in_imagegpt""",
 ]


if TYPE_CHECKING:
 from .configuration_imagegpt import IMAGEGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, ImageGPTConfig, ImageGPTOnnxConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_imagegpt import ImageGPTFeatureExtractor
  from .image_processing_imagegpt import ImageGPTImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_imagegpt import (
      IMAGEGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
      ImageGPTForCausalImageModeling,
      ImageGPTForImageClassification,
      ImageGPTModel,
      ImageGPTPreTrainedModel,
      load_tf_weights_in_imagegpt,
  )

else:
 import sys

 A									=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
