
"""simple docstring"""

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


UpperCamelCase			:       Union[str, Any]									=				logging.get_logger(__name__)

UpperCamelCase			:       str									=				{
    "google/switch-base-8": "https://huggingface.co/google/switch-base-8/blob/main/config.json",
}

class __lowerCAmelCase	(   __SCREAMING_SNAKE_CASE    ):
     lowercase		     =		"switch_transformers"
     lowercase		     =		["past_key_values"]
     lowercase		     =		{"hidden_size": "d_model", "num_attention_heads": "num_heads", "num_hidden_layers": "num_layers"}





     def __init__(			self			,  __UpperCAmelCase=3_2128			,  __UpperCAmelCase=768			,  __UpperCAmelCase=64			,  __UpperCAmelCase=2048			,  __UpperCAmelCase=64			,  __UpperCAmelCase=12			,  __UpperCAmelCase=3			,  __UpperCAmelCase=12			,  __UpperCAmelCase=3			,  __UpperCAmelCase=12			,  __UpperCAmelCase=8			,  __UpperCAmelCase=False			,  __UpperCAmelCase=0.0_1			,  __UpperCAmelCase="float32"			,  __UpperCAmelCase=False			,  __UpperCAmelCase=32			,  __UpperCAmelCase=128			,  __UpperCAmelCase=0.1			,  __UpperCAmelCase=1E-6			,  __UpperCAmelCase=0.0_0_1			,  __UpperCAmelCase=0.0_0_1			,  __UpperCAmelCase=1.0			,  __UpperCAmelCase="relu"			,  __UpperCAmelCase=True			,  __UpperCAmelCase=False			,  __UpperCAmelCase=True			,  __UpperCAmelCase=0			,  __UpperCAmelCase=1			,  **__UpperCAmelCase			,  ):

      '''simple docstring'''




      __UpperCamelCase       						= vocab_size
      __UpperCamelCase       						= d_model
      __UpperCamelCase       						= d_kv
      __UpperCamelCase       						= d_ff

      __UpperCamelCase       						= num_sparse_encoder_layers

      __UpperCamelCase       						= num_layers
      __UpperCamelCase       						= (
          num_decoder_layers if num_decoder_layers is not None else self.num_layers
      )  # default = symmetry
      __UpperCamelCase       						= num_sparse_decoder_layers

      # This tells us, each how many encoder layer we'll have to set a sparse layer.
      if self.num_sparse_encoder_layers > 0:
       __UpperCamelCase       						= self.num_layers // self.num_sparse_encoder_layers
      else:
       __UpperCamelCase       						= self.num_layers  # HACK: this will create 0 sparse layers

      # This tells us, each how many encoder layer we'll have to set a sparse layer.
      if self.num_sparse_decoder_layers > 0:
       __UpperCamelCase       						= self.num_decoder_layers // self.num_sparse_decoder_layers
      else:
       __UpperCamelCase       						= self.num_decoder_layers  # HACK: this will create 0 sparse layers

      __UpperCamelCase       						= num_heads
      __UpperCamelCase       						= num_experts
      __UpperCamelCase       						= expert_capacity
      __UpperCamelCase       						= router_bias
      __UpperCamelCase       						= router_jitter_noise
      if router_dtype not in ["float32", "float16", "bfloat16"]:
       raise ValueError(F'`router_dtype` must be one of \'float32\', \'float16\' or \'bfloat16\', got {router_dtype}'   )
      __UpperCamelCase       						= router_dtype

      __UpperCamelCase       						= router_ignore_padding_tokens
      __UpperCamelCase       						= relative_attention_num_buckets
      __UpperCamelCase       						= relative_attention_max_distance

      __UpperCamelCase       						= dropout_rate
      __UpperCamelCase       						= layer_norm_epsilon
      __UpperCamelCase       						= initializer_factor
      __UpperCamelCase       						= feed_forward_proj
      __UpperCamelCase       						= use_cache
      __UpperCamelCase       						= add_router_probs

      __UpperCamelCase       						= router_z_loss_coef
      __UpperCamelCase       						= router_aux_loss_coef

      __UpperCamelCase       						= self.feed_forward_proj.split('-'   )
      __UpperCamelCase       						= act_info[-1]
      __UpperCamelCase       						= act_info[0] == 'gated'

      if len(__UpperCAmelCase   ) > 1 and act_info[0] != "gated" or len(__UpperCAmelCase   ) > 2:
       raise ValueError(
           F'`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'
           'Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '
           '\'gated-gelu\' or \'relu\''   )

      # for backwards compatibility
      if feed_forward_proj == "gated-gelu":
       __UpperCamelCase       						= 'gelu_new'

      super().__init__(
          pad_token_id=__UpperCAmelCase			,  eos_token_id=__UpperCAmelCase			,  is_encoder_decoder=__UpperCAmelCase			,  **__UpperCAmelCase			,  )





"""simple docstring"""

import string

import numpy






def 							A		(       snake_case   :int       ,      snake_case   :int	)   ->			int:
 return b if a == 0 else greatest_common_divisor(b % a       ,      snake_case	)

class __lowerCAmelCase	:
     lowercase		     =		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)
     lowercase		     =		numpy.vectorize(lambda __SCREAMING_SNAKE_CASE    : x % 36    )

     lowercase		     =		numpy.vectorize(__SCREAMING_SNAKE_CASE    )





     def __init__(			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.modulus(__UpperCAmelCase   )  # mod36 calc's on the encrypt key
      self.check_determinant()  # validate the determinant of the encryption key
      __UpperCamelCase       						= encrypt_key.shape[0]





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      return self.key_string.index(__UpperCAmelCase   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      return self.key_string[round(__UpperCAmelCase   )]





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= round(numpy.linalg.det(self.encrypt_key   )   )

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

      __UpperCamelCase       						= len(self.key_string   )
      if greatest_common_divisor(__UpperCAmelCase			,  len(self.key_string   )   ) != 1:
       __UpperCamelCase       						= (
           F'determinant modular {req_l} of encryption key({det}) '
           F'is not co prime w.r.t {req_l}.\nTry another key.'
       )
       raise ValueError(__UpperCAmelCase   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= [char for char in text.upper() if char in self.key_string]

      __UpperCamelCase       						= chars[-1]
      while len(__UpperCAmelCase   ) % self.break_key != 0:
       chars.append(__UpperCAmelCase   )

      return "".join(__UpperCAmelCase   )





     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.process_text(text.upper()   )
      __UpperCamelCase       						= ''

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

      return encrypted





     def 		UpperCAmelCase      (			self   ):

      '''simple docstring'''




      __UpperCamelCase       						= round(numpy.linalg.det(self.encrypt_key   )   )

      if det < 0:
       __UpperCamelCase       						= det % len(self.key_string   )
      __UpperCamelCase       						= None
      for i in range(len(self.key_string   )   ):
       if (det * i) % len(self.key_string   ) == 1:
        __UpperCamelCase       						= i
        break

      __UpperCamelCase       						= (
          det_inv
          * numpy.linalg.det(self.encrypt_key   )
          * numpy.linalg.inv(self.encrypt_key   )
      )

      return self.to_int(self.modulus(__UpperCAmelCase   )   )







     def 		UpperCAmelCase      (			self			,  __UpperCAmelCase   ):

      '''simple docstring'''




      __UpperCamelCase       						= self.make_decrypt_key()
      __UpperCamelCase       						= self.process_text(text.upper()   )
      __UpperCamelCase       						= ''

      for i in range(0			,  len(__UpperCAmelCase   ) - self.break_key + 1			,  self.break_key   ):
       __UpperCamelCase       						= text[i : i + self.break_key]
       __UpperCamelCase       						= [self.replace_letters(__UpperCAmelCase   ) for char in batch]
       __UpperCamelCase       						= numpy.array([vec]   ).T
       __UpperCamelCase       						= self.modulus(decrypt_key.dot(__UpperCAmelCase   )   ).T.tolist()[0]
       __UpperCamelCase       						= ''.join(
           self.replace_digits(__UpperCAmelCase   ) for num in batch_decrypted   )
       decrypted += decrypted_batch

      return decrypted






def 							A		(       )   ->			None:
 __UpperCamelCase       						= int(input('Enter the order of the encryption key: '	)	)
 __UpperCamelCase       						= []

 print('Enter each row of the encryption key with space separated integers'	)
 for _ in range(snake_case	):
  __UpperCamelCase       						= [int(snake_case	) for x in input().split()]
  hill_matrix.append(snake_case	)

 __UpperCamelCase       						= HillCipher(numpy.array(snake_case	)	)

 print('Would you like to encrypt or decrypt some text? (1 or 2)'	)
 __UpperCamelCase       						= input('\n1. Encrypt\n2. Decrypt\n'	)
 if option == "1":
  __UpperCamelCase       						= input('What text would you like to encrypt?: '	)
  print('Your encrypted text is:'	)
  print(hc.encrypt(snake_case	)	)
 elif option == "2":
  __UpperCamelCase       						= input('What text would you like to decrypt?: '	)
  print('Your decrypted text is:'	)
  print(hc.decrypt(snake_case	)	)


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      main()



