"""simple docstring"""







import math
from typing import Optional

import numpy as np

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_a  :  str=				logging.get_logger(__name__)

_a  :  Union[str, Any]=				{
    "facebook/encodec_24khz": "https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json",
    "facebook/encodec_48khz": "https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json",
}

class 	UpperCamelCase    (					lowercase		):
    UpperCAmelCase       :   Union[str, Any]					=	"""encodec"""



    def __init__(self       :   Tuple			,						_A       :   str=[1.5, 3.0, 6.0, 12.0, 24.0]			,						_A       :   Any=2_40_00			,						_A       :   Union[str, Any]=1			,						_A       :   Optional[Any]=False			,						_A       :   Tuple=None			,						_A       :   int=None			,						_A       :   int=1_28			,						_A       :   List[str]=32			,						_A       :   Tuple=1			,						_A       :   Any=[8, 5, 4, 2]			,						_A       :   int="weight_norm"			,						_A       :   List[Any]=7			,						_A       :   List[str]=7			,						_A       :   str=3			,						_A       :   Tuple=2			,						_A       :   Dict=True			,						_A       :   Optional[int]="reflect"			,						_A       :   Union[str, Any]=2			,						_A       :   str=2			,						_A       :   List[Any]=1.0			,						_A       :   List[Any]=10_24			,						_A       :   Optional[int]=None			,						_A       :   List[Any]=True			,						**_A       :   Union[str, Any]			,						)					->			Union[str, Any]:
     __snake_case    :							Optional[Any]   	=				target_bandwidths
     __snake_case    :							Tuple   	=				sampling_rate
     __snake_case    :							str   	=				audio_channels
     __snake_case    :							Optional[int]   	=				normalize
     __snake_case    :							Optional[Any]   	=				chunk_length_s
     __snake_case    :							int   	=				overlap
     __snake_case    :							Union[str, Any]   	=				hidden_size
     __snake_case    :							int   	=				num_filters
     __snake_case    :							Union[str, Any]   	=				num_residual_layers
     __snake_case    :							int   	=				upsampling_ratios
     __snake_case    :							Optional[Any]   	=				norm_type
     __snake_case    :							Optional[Any]   	=				kernel_size
     __snake_case    :							Tuple   	=				last_kernel_size
     __snake_case    :							Optional[Any]   	=				residual_kernel_size
     __snake_case    :							List[Any]   	=				dilation_growth_rate
     __snake_case    :							Optional[Any]   	=				use_causal_conv
     __snake_case    :							int   	=				pad_mode
     __snake_case    :							List[str]   	=				compress
     __snake_case    :							Tuple   	=				num_lstm_layers
     __snake_case    :							Dict   	=				trim_right_ratio
     __snake_case    :							Dict   	=				codebook_size
     __snake_case    :							List[str]   	=				codebook_dim if codebook_dim is not None else hidden_size
     __snake_case    :							str   	=				use_conv_shortcut

     if self.norm_type not in ["weight_norm", "time_group_norm"]:
      raise ValueError(
          f"self.norm_type must be one of `\"weight_norm\"`, `\"time_group_norm\"`), got {self.norm_type}")

     super().__init__(**_A)



    @property
    def       _lowercase  (self       :   Any)					->			Optional[int]:
     if self.chunk_length_s is None:
      return None
     else:
      return int(self.chunk_length_s * self.sampling_rate)



    @property
    def       _lowercase  (self       :   List[Any])					->			Optional[int]:
     if self.chunk_length_s is None or self.overlap is None:
      return None
     else:
      return max(1			,						int((1.0 - self.overlap) * self.chunk_length))



    @property
    def       _lowercase  (self       :   str)					->			int:
     __snake_case    :							Dict   	=				np.prod(self.upsampling_ratios)
     return math.ceil(self.sampling_rate / hop_length)






    @property
    def       _lowercase  (self       :   List[Any])					->			int:
     return int(10_00 * self.target_bandwidths[-1] // (self.frame_rate * 10))






"""simple docstring"""







import string

import numpy
def 						__UpperCAmelCase       (					UpperCAmelCase_					:       int    ,							UpperCAmelCase_					:       int						)							->    int:

	'''simple docstring'''





	return b if a == 0 else greatest_common_divisor(b % a    ,							UpperCAmelCase_						)

class 	UpperCamelCase    :
				UpperCAmelCase       :   Any					=	string.ascii_uppercase + string.digits
				# This cipher takes alphanumerics into account
				# i.e. a total of 36 characters

				# take x and return x % len(key_string)
				UpperCAmelCase       :   List[Any]					=	numpy.vectorize(lambda lowercase		: x % 36		)

				UpperCAmelCase       :   Dict					=	numpy.vectorize(lowercase		)



				def __init__(self       :   str			,						_A       :   numpy.ndarray)					->			None:
					__snake_case    :							str   	=				self.modulus(_A)  # mod36 calc's on the encrypt key
					self.check_determinant()  # validate the determinant of the encryption key
					__snake_case    :							Optional[Any]   	=				encrypt_key.shape[0]



				def       _lowercase  (self       :   Any			,						_A       :   str)					->			int:
					return self.key_string.index(_A)



				def       _lowercase  (self       :   Union[str, Any]			,						_A       :   int)					->			str:
					return self.key_string[round(_A)]



				def       _lowercase  (self       :   Optional[int])					->			None:
					__snake_case    :							Any   	=				round(numpy.linalg.det(self.encrypt_key))

					if det < 0:
						__snake_case    :							Any   	=				det % len(self.key_string)

					__snake_case    :							Tuple   	=				len(self.key_string)
					if greatest_common_divisor(_A			,						len(self.key_string)) != 1:
						__snake_case    :							List[str]   	=				(
						    f"determinant modular {req_l} of encryption key({det}) "
						    f"is not co prime w.r.t {req_l}.\nTry another key."
						)
						raise ValueError(_A)



				def       _lowercase  (self       :   Dict			,						_A       :   str)					->			str:
					__snake_case    :							str   	=				[char for char in text.upper() if char in self.key_string]

					__snake_case    :							int   	=				chars[-1]
					while len(_A) % self.break_key != 0:
						chars.append(_A)

					return "".join(_A)



				def       _lowercase  (self       :   Union[str, Any]			,						_A       :   str)					->			str:
					__snake_case    :							Any   	=				self.process_text(text.upper())
					__snake_case    :							Dict   	=				''

					for i in range(0			,						len(_A) - self.break_key + 1			,						self.break_key):
						__snake_case    :							Dict   	=				text[i : i + self.break_key]
						__snake_case    :							List[str]   	=				[self.replace_letters(_A) for char in batch]
						__snake_case    :							str   	=				numpy.array([vec]).T
						__snake_case    :							List[Any]   	=				self.modulus(self.encrypt_key.dot(_A)).T.tolist()[
						    0
						]
						__snake_case    :							str   	=				''.join(
						    self.replace_digits(_A) for num in batch_encrypted)
						encrypted += encrypted_batch

					return encrypted



				def       _lowercase  (self       :   Optional[int])					->			numpy.ndarray:
					__snake_case    :							List[Any]   	=				round(numpy.linalg.det(self.encrypt_key))

					if det < 0:
						__snake_case    :							int   	=				det % len(self.key_string)
					__snake_case    :							Optional[Any]   	=				None
					for i in range(len(self.key_string)):
						if (det * i) % len(self.key_string) == 1:
							__snake_case    :							Dict   	=				i
							break

					__snake_case    :							List[str]   	=				(
					    det_inv
					    * numpy.linalg.det(self.encrypt_key)
					    * numpy.linalg.inv(self.encrypt_key)
					)

					return self.to_int(self.modulus(_A))






				def       _lowercase  (self       :   int			,						_A       :   str)					->			str:
					__snake_case    :							int   	=				self.make_decrypt_key()
					__snake_case    :							List[str]   	=				self.process_text(text.upper())
					__snake_case    :							str   	=				''

					for i in range(0			,						len(_A) - self.break_key + 1			,						self.break_key):
						__snake_case    :							Optional[Any]   	=				text[i : i + self.break_key]
						__snake_case    :							Union[str, Any]   	=				[self.replace_letters(_A) for char in batch]
						__snake_case    :							Tuple   	=				numpy.array([vec]).T
						__snake_case    :							List[str]   	=				self.modulus(decrypt_key.dot(_A)).T.tolist()[0]
						__snake_case    :							str   	=				''.join(
						    self.replace_digits(_A) for num in batch_decrypted)
						decrypted += decrypted_batch

					return decrypted







def 						__UpperCAmelCase       (					)							->    None:

	'''simple docstring'''





	__snake_case    :							List[str]   	=				int(input('Enter the order of the encryption key: '						)						)
	__snake_case    :							str   	=				[]

	print('Enter each row of the encryption key with space separated integers'						)
	for _ in range(UpperCAmelCase_						):
		__snake_case    :							Union[str, Any]   	=				[int(UpperCAmelCase_						) for x in input().split()]
		hill_matrix.append(UpperCAmelCase_						)

	__snake_case    :							Dict   	=				HillCipher(numpy.array(UpperCAmelCase_						)						)

	print('Would you like to encrypt or decrypt some text? (1 or 2)'						)
	__snake_case    :							Optional[Any]   	=				input('\n1. Encrypt\n2. Decrypt\n'						)
	if option == "1":
		__snake_case    :							int   	=				input('What text would you like to encrypt?: '						)
		print('Your encrypted text is:'						)
		print(hc.encrypt(UpperCAmelCase_						)						)
	elif option == "2":
		__snake_case    :							Tuple   	=				input('What text would you like to decrypt?: '						)
		print('Your decrypted text is:'						)
		print(hc.decrypt(UpperCAmelCase_						)						)


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	main()





