






import numpy as np

UpperCamelCase								=		[
    ["a", "b", "c", "d", "e"],
    ["f", "g", "h", "i", "k"],
    ["l", "m", "n", "o", "p"],
    ["q", "r", "s", "t", "u"],
    ["v", "w", "x", "y", "z"],
]

class 				lowerCAmelCase_	:


				def __init__(					self      ):
											_lowercase							:   Any 							=   np.array(_lowerCAmelCase      )


				def 						__a					(					self ,						_lowerCAmelCase      ):
											_lowercase							,							_lowercase							:   List[str] 							=   np.where(letter == self.SQUARE      )
											_lowercase							:   Optional[int] 							=   np.concatenate([indexa + 1, indexa + 1]      )
											return indexes


				def 						__a					(					self ,						_lowerCAmelCase ,						_lowerCAmelCase      ):
											_lowercase							:   int 							=   self.SQUARE[indexa - 1, indexa - 1]
											return letter


				def 						__a					(					self ,						_lowerCAmelCase      ):
											_lowercase							:   int 							=   message.lower()
											_lowercase							:   Optional[Any] 							=   message.replace(' ' ,						''      )
											_lowercase							:   Optional[Any] 							=   message.replace('j' ,						'i'      )

											_lowercase							:   Optional[int] 							=   np.empty((2, len(_lowerCAmelCase      ))      )
											for letter_index in range(len(_lowerCAmelCase      )      ):
																		_lowercase							:   Any 							=   self.letter_to_numbers(message[letter_index]      )

																		_lowercase							:   Tuple 							=   numbers[0]
																		_lowercase							:   int 							=   numbers[1]

											_lowercase							:   int 							=   first_step.reshape(2 * len(_lowerCAmelCase      )      )
											_lowercase							:   Tuple 							=   ''
											for numbers_index in range(len(_lowerCAmelCase      )      ):
																		_lowercase							:   int 							=   int(second_step[numbers_index * 2]      )
																		_lowercase							:   List[Any] 							=   int(second_step[(numbers_index * 2) + 1]      )
																		_lowercase							:   Optional[int] 							=   self.numbers_to_letter(_lowerCAmelCase ,						_lowerCAmelCase      )
																		_lowercase							:   List[Any] 							=   encoded_message + letter

											return encoded_message


				def 						__a					(					self ,						_lowerCAmelCase      ):
											_lowercase							:   Tuple 							=   message.lower()
											message.replace(' ' ,						''      )
											_lowercase							:   Optional[Any] 							=   np.empty(2 * len(_lowerCAmelCase      )      )
											for letter_index in range(len(_lowerCAmelCase      )      ):
																		_lowercase							:   List[Any] 							=   self.letter_to_numbers(message[letter_index]      )
																		_lowercase							:   int 							=   numbers[0]
																		_lowercase							:   Union[str, Any] 							=   numbers[1]

											_lowercase							:   Optional[int] 							=   first_step.reshape((2, len(_lowerCAmelCase      ))      )
											_lowercase							:   Tuple 							=   ''
											for numbers_index in range(len(_lowerCAmelCase      )      ):
																		_lowercase							:   Tuple 							=   int(second_step[0, numbers_index]      )
																		_lowercase							:   Dict 							=   int(second_step[1, numbers_index]      )
																		_lowercase							:   List[Any] 							=   self.numbers_to_letter(_lowerCAmelCase ,						_lowerCAmelCase      )
																		_lowercase							:   Dict 							=   decoded_message + letter

											return decoded_message











import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible




class 	UpperCamelCase_							(  unittest.TestCase     ):


							def   _snake_case	(				self     :Tuple		) -> Any:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """safety_checker/pytorch_model.bin""",
									    """safety_checker/model.safetensors""",
									    """vae/diffusion_pytorch_model.bin""",
									    """vae/diffusion_pytorch_model.safetensors""",
									    """text_encoder/pytorch_model.bin""",
									    """text_encoder/model.safetensors""",
									    """unet/diffusion_pytorch_model.bin""",
									    """unet/diffusion_pytorch_model.safetensors""",
									]
									self.assertTrue(is_safetensors_compatible(__A		)		)


							def   _snake_case	(				self     :List[str]		) -> int:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """unet/diffusion_pytorch_model.bin""",
									    """unet/diffusion_pytorch_model.safetensors""",
									]
									self.assertTrue(is_safetensors_compatible(__A		)		)


							def   _snake_case	(				self     :Tuple		) -> Optional[Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """safety_checker/pytorch_model.bin""",
									    """safety_checker/model.safetensors""",
									    """vae/diffusion_pytorch_model.bin""",
									    """vae/diffusion_pytorch_model.safetensors""",
									    """text_encoder/pytorch_model.bin""",
									    """text_encoder/model.safetensors""",
									    """unet/diffusion_pytorch_model.bin""",
									    # Removed: 'unet/diffusion_pytorch_model.safetensors',
									]
									self.assertFalse(is_safetensors_compatible(__A		)		)


							def   _snake_case	(				self     :Union[str, Any]		) -> Union[str, Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """text_encoder/pytorch_model.bin""",
									    """text_encoder/model.safetensors""",
									]
									self.assertTrue(is_safetensors_compatible(__A		)		)


							def   _snake_case	(				self     :Optional[Any]		) -> Any:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """safety_checker/pytorch_model.bin""",
									    """safety_checker/model.safetensors""",
									    """vae/diffusion_pytorch_model.bin""",
									    """vae/diffusion_pytorch_model.safetensors""",
									    """text_encoder/pytorch_model.bin""",
									    # Removed: 'text_encoder/model.safetensors',
									    """unet/diffusion_pytorch_model.bin""",
									    """unet/diffusion_pytorch_model.safetensors""",
									]
									self.assertFalse(is_safetensors_compatible(__A		)		)


							def   _snake_case	(				self     :Tuple		) -> List[Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """safety_checker/pytorch_model.fp16.bin""",
									    """safety_checker/model.fp16.safetensors""",
									    """vae/diffusion_pytorch_model.fp16.bin""",
									    """vae/diffusion_pytorch_model.fp16.safetensors""",
									    """text_encoder/pytorch_model.fp16.bin""",
									    """text_encoder/model.fp16.safetensors""",
									    """unet/diffusion_pytorch_model.fp16.bin""",
									    """unet/diffusion_pytorch_model.fp16.safetensors""",
									]
									SCREAMING_SNAKE_CASE__								=   """fp16"""
									self.assertTrue(is_safetensors_compatible(__A				,					variant=__A		)		)


							def   _snake_case	(				self     :Any		) -> Tuple:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """unet/diffusion_pytorch_model.fp16.bin""",
									    """unet/diffusion_pytorch_model.fp16.safetensors""",
									]
									SCREAMING_SNAKE_CASE__								=   """fp16"""
									self.assertTrue(is_safetensors_compatible(__A				,					variant=__A		)		)


							def   _snake_case	(				self     :str		) -> Tuple:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """unet/diffusion_pytorch_model.bin""",
									    """unet/diffusion_pytorch_model.safetensors""",
									]
									SCREAMING_SNAKE_CASE__								=   """fp16"""
									self.assertTrue(is_safetensors_compatible(__A				,					variant=__A		)		)


							def   _snake_case	(				self     :List[Any]		) -> List[Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """safety_checker/pytorch_model.fp16.bin""",
									    """safety_checker/model.fp16.safetensors""",
									    """vae/diffusion_pytorch_model.fp16.bin""",
									    """vae/diffusion_pytorch_model.fp16.safetensors""",
									    """text_encoder/pytorch_model.fp16.bin""",
									    """text_encoder/model.fp16.safetensors""",
									    """unet/diffusion_pytorch_model.fp16.bin""",
									    # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
									]
									SCREAMING_SNAKE_CASE__								=   """fp16"""
									self.assertFalse(is_safetensors_compatible(__A				,					variant=__A		)		)


							def   _snake_case	(				self     :str		) -> List[str]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """text_encoder/pytorch_model.fp16.bin""",
									    """text_encoder/model.fp16.safetensors""",
									]
									SCREAMING_SNAKE_CASE__								=   """fp16"""
									self.assertTrue(is_safetensors_compatible(__A				,					variant=__A		)		)


							def   _snake_case	(				self     :Optional[int]		) -> Optional[Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """text_encoder/pytorch_model.bin""",
									    """text_encoder/model.safetensors""",
									]
									SCREAMING_SNAKE_CASE__								=   """fp16"""
									self.assertTrue(is_safetensors_compatible(__A				,					variant=__A		)		)


							def   _snake_case	(				self     :Union[str, Any]		) -> Optional[Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [
									    """safety_checker/pytorch_model.fp16.bin""",
									    """safety_checker/model.fp16.safetensors""",
									    """vae/diffusion_pytorch_model.fp16.bin""",
									    """vae/diffusion_pytorch_model.fp16.safetensors""",
									    """text_encoder/pytorch_model.fp16.bin""",
									    # 'text_encoder/model.fp16.safetensors',
									    """unet/diffusion_pytorch_model.fp16.bin""",
									    """unet/diffusion_pytorch_model.fp16.safetensors""",
									]
									SCREAMING_SNAKE_CASE__								=   """fp16"""
									self.assertFalse(is_safetensors_compatible(__A				,					variant=__A		)		)