



'''simple docstring'''




def        lowerCAmelCase_     (			_lowerCamelCase:     Union[str, Any] ,   _lowerCamelCase:     Optional[int]      ):
		__SCREAMING_SNAKE_CASE :	List[Any]					 =	""""""
		for i in table:
				res += inp[i - 1]
		return res


def        lowerCAmelCase_     (			_lowerCamelCase:     Dict      ):
		return data[1:] + data[0]


def        lowerCAmelCase_     (			_lowerCamelCase:     int ,   _lowerCamelCase:     Optional[int]      ):
		__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	""""""
		for i in range(len(_lowerCamelCase      )      ):
				if a[i] == b[i]:
						res += "0"
				else:
						res += "1"
		return res


def        lowerCAmelCase_     (			_lowerCamelCase:     List[Any] ,   _lowerCamelCase:     Any      ):
		__SCREAMING_SNAKE_CASE :	Tuple					 =	int("""0b""" + data[0] + data[-1] ,   2      )
		__SCREAMING_SNAKE_CASE :	Optional[int]					 =	int("""0b""" + data[1:3] ,   2      )
		return bin(s[row][col]      )[2:]


def        lowerCAmelCase_     (			_lowerCamelCase:     int ,   _lowerCamelCase:     Optional[int] ,   _lowerCamelCase:     List[str] ,   _lowerCamelCase:     str ,   _lowerCamelCase:     List[Any]      ):
		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	message[:4]
		__SCREAMING_SNAKE_CASE :	str					 =	message[4:]
		__SCREAMING_SNAKE_CASE :	int					 =	apply_table(_lowerCamelCase ,   _lowerCamelCase      )
		__SCREAMING_SNAKE_CASE :	int					 =	xor(_lowerCamelCase ,   _lowerCamelCase      )
		__SCREAMING_SNAKE_CASE :	Optional[int]					 =	apply_sbox(_lowerCamelCase ,   temp[:4]      )  # noqa: E741
		__SCREAMING_SNAKE_CASE :	Tuple					 =	apply_sbox(_lowerCamelCase ,   temp[4:]      )
		__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	"""0""" * (2 - len(_lowerCamelCase      )) + l  # noqa: E741
		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	"""0""" * (2 - len(_lowerCamelCase      )) + r
		__SCREAMING_SNAKE_CASE :	List[Any]					 =	apply_table(l + r ,   _lowerCamelCase      )
		__SCREAMING_SNAKE_CASE :	List[Any]					 =	xor(_lowerCamelCase ,   _lowerCamelCase      )
		return temp + right


if __name__ == "__main__":
						UpperCamelCase__ :			Optional[int]												=				input('''Enter 10 bit key: ''')
						UpperCamelCase__ :			str												=				input('''Enter 8 bit message: ''')

						UpperCamelCase__ :			Optional[Any]												=				[6, 3, 7, 4, 8, 5, 10, 9]
						UpperCamelCase__ :			Any												=				[3, 5, 2, 7, 4, 10, 1, 9, 8, 6]
						UpperCamelCase__ :			List[str]												=				[2, 4, 3, 1]
						UpperCamelCase__ :			Any												=				[2, 6, 3, 1, 4, 8, 5, 7]
						UpperCamelCase__ :			Optional[int]												=				[4, 1, 3, 5, 7, 2, 8, 6]
						UpperCamelCase__ :			str												=				[4, 1, 2, 3, 2, 3, 4, 1]
						UpperCamelCase__ :			List[Any]												=				[[1, 0, 3, 2], [3, 2, 1, 0], [0, 2, 1, 3], [3, 1, 3, 2]]
						UpperCamelCase__ :			int												=				[[0, 1, 2, 3], [2, 0, 1, 3], [3, 0, 1, 0], [2, 1, 0, 3]]

						# key generation
						UpperCamelCase__ :			Any												=				apply_table(key, paa_table)
						UpperCamelCase__ :			str												=				temp[:5]
						UpperCamelCase__ :			Union[str, Any]												=				temp[5:]
						UpperCamelCase__ :			Optional[Any]												=				left_shift(left)
						UpperCamelCase__ :			str												=				left_shift(right)
						UpperCamelCase__ :			Tuple												=				apply_table(left + right, pa_table)
						UpperCamelCase__ :			List[Any]												=				left_shift(left)
						UpperCamelCase__ :			List[Any]												=				left_shift(right)
						UpperCamelCase__ :			int												=				left_shift(left)
						UpperCamelCase__ :			int												=				left_shift(right)
						UpperCamelCase__ :			List[Any]												=				apply_table(left + right, pa_table)

						# encryption
						UpperCamelCase__ :			Optional[int]												=				apply_table(message, IP)
						UpperCamelCase__ :			str												=				function(expansion, sa, sa, keya, temp)
						UpperCamelCase__ :			List[str]												=				temp[4:] + temp[:4]
						UpperCamelCase__ :			List[str]												=				function(expansion, sa, sa, keya, temp)
						UpperCamelCase__ :			Union[str, Any]												=				apply_table(temp, IP_inv)
						print('''Cipher text is:''', CT)

						# decryption
						UpperCamelCase__ :			int												=				apply_table(CT, IP)
						UpperCamelCase__ :			Dict												=				function(expansion, sa, sa, keya, temp)
						UpperCamelCase__ :			List[Any]												=				temp[4:] + temp[:4]
						UpperCamelCase__ :			Optional[Any]												=				function(expansion, sa, sa, keya, temp)
						UpperCamelCase__ :			int												=				apply_table(temp, IP_inv)
						print('''Plain text after decypting is:''', PT)




'''simple docstring'''




import json
import os

import torch

from diffusers import UNetaDModel


os.makedirs('''hub/hopper-medium-v2/unet/hor32''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/unet/hor128''', exist_ok=True)

os.makedirs('''hub/hopper-medium-v2/value_function''', exist_ok=True)


def        lowerCAmelCase_     (			_lowerCamelCase:     int      ):
		if hor == 1_28:
				__SCREAMING_SNAKE_CASE :	Any					 =	("""DownResnetBlock1D""", """DownResnetBlock1D""", """DownResnetBlock1D""")
				__SCREAMING_SNAKE_CASE :	List[Any]					 =	(32, 1_28, 2_56)
				__SCREAMING_SNAKE_CASE :	str					 =	("""UpResnetBlock1D""", """UpResnetBlock1D""")

		elif hor == 32:
				__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	("""DownResnetBlock1D""", """DownResnetBlock1D""", """DownResnetBlock1D""", """DownResnetBlock1D""")
				__SCREAMING_SNAKE_CASE :	str					 =	(32, 64, 1_28, 2_56)
				__SCREAMING_SNAKE_CASE :	Tuple					 =	("""UpResnetBlock1D""", """UpResnetBlock1D""", """UpResnetBlock1D""")
		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	torch.load(F"/Users/bglickenhaus/Documents/diffuser/temporal_unet-hopper-mediumv2-hor{hor}.torch"      )
		__SCREAMING_SNAKE_CASE :	Any					 =	model.state_dict()
		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	{
		    """down_block_types""": down_block_types,
		    """block_out_channels""": block_out_channels,
		    """up_block_types""": up_block_types,
		    """layers_per_block""": 1,
		    """use_timestep_embedding""": True,
		    """out_block_type""": """OutConv1DBlock""",
		    """norm_num_groups""": 8,
		    """downsample_each_block""": False,
		    """in_channels""": 14,
		    """out_channels""": 14,
		    """extra_in_channels""": 0,
		    """time_embedding_type""": """positional""",
		    """flip_sin_to_cos""": False,
		    """freq_shift""": 1,
		    """sample_size""": 6_55_36,
		    """mid_block_type""": """MidResTemporalBlock1D""",
		    """act_fn""": """mish""",
		}
		__SCREAMING_SNAKE_CASE :	int					 =	UNetaDModel(**_lowerCamelCase      )
		print(F"length of state dict: {len(state_dict.keys()      )}"      )
		print(F"length of value function dict: {len(hf_value_function.state_dict().keys()      )}"      )
		__SCREAMING_SNAKE_CASE :	Optional[int]					 =	dict(zip(model.state_dict().keys() ,   hf_value_function.state_dict().keys()      )      )
		for k, v in mapping.items():
				__SCREAMING_SNAKE_CASE :	Union[str, Any]					 =	state_dict.pop(_lowerCamelCase      )
		hf_value_function.load_state_dict(_lowerCamelCase      )

		torch.save(hf_value_function.state_dict() ,   F"hub/hopper-medium-v2/unet/hor{hor}/diffusion_pytorch_model.bin"      )
		with open(F"hub/hopper-medium-v2/unet/hor{hor}/config.json" ,   """w"""      ) as f:
				json.dump(_lowerCamelCase ,   _lowerCamelCase      )


def        lowerCAmelCase_     (			):
		__SCREAMING_SNAKE_CASE :	Dict					 =	{
		    """in_channels""": 14,
		    """down_block_types""": ("""DownResnetBlock1D""", """DownResnetBlock1D""", """DownResnetBlock1D""", """DownResnetBlock1D"""),
		    """up_block_types""": (),
		    """out_block_type""": """ValueFunction""",
		    """mid_block_type""": """ValueFunctionMidBlock1D""",
		    """block_out_channels""": (32, 64, 1_28, 2_56),
		    """layers_per_block""": 1,
		    """downsample_each_block""": True,
		    """sample_size""": 6_55_36,
		    """out_channels""": 14,
		    """extra_in_channels""": 0,
		    """time_embedding_type""": """positional""",
		    """use_timestep_embedding""": True,
		    """flip_sin_to_cos""": False,
		    """freq_shift""": 1,
		    """norm_num_groups""": 8,
		    """act_fn""": """mish""",
		}

		__SCREAMING_SNAKE_CASE :	Optional[int]					 =	torch.load("""/Users/bglickenhaus/Documents/diffuser/value_function-hopper-mediumv2-hor32.torch"""      )
		__SCREAMING_SNAKE_CASE :	Dict					 =	model
		__SCREAMING_SNAKE_CASE :	List[Any]					 =	UNetaDModel(**_lowerCamelCase      )
		print(F"length of state dict: {len(state_dict.keys()      )}"      )
		print(F"length of value function dict: {len(hf_value_function.state_dict().keys()      )}"      )

		__SCREAMING_SNAKE_CASE :	Optional[Any]					 =	dict(zip(state_dict.keys() ,   hf_value_function.state_dict().keys()      )      )
		for k, v in mapping.items():
				__SCREAMING_SNAKE_CASE :	str					 =	state_dict.pop(_lowerCamelCase      )

		hf_value_function.load_state_dict(_lowerCamelCase      )

		torch.save(hf_value_function.state_dict() ,   """hub/hopper-medium-v2/value_function/diffusion_pytorch_model.bin"""      )
		with open("""hub/hopper-medium-v2/value_function/config.json""" ,   """w"""      ) as f:
				json.dump(_lowerCamelCase ,   _lowerCamelCase      )


if __name__ == "__main__":
						unet(32)
						# unet(128)
						value_function()