

import random
import sys

lowerCAmelCase						:   List[Any]										=    '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''





def 			_lowercase    (      ):
      snake_case__					=   input("""Enter message: """ )
      snake_case__					=   """LFWOAYUISVKMNXPBDCRJTQEGHZ"""
      snake_case__					=   input("""Encrypt/Decrypt [e/d]: """ )

      check_valid_key(__UpperCamelCase )

      if resp.lower().startswith("""e""" ):
            snake_case__					=   """encrypt"""
            snake_case__					=   encrypt_message(__UpperCamelCase   ,       __UpperCamelCase )
      elif resp.lower().startswith("""d""" ):
            snake_case__					=   """decrypt"""
            snake_case__					=   decrypt_message(__UpperCamelCase   ,       __UpperCamelCase )

      print(F'''\n{mode.title()}ion: \n{translated}''' )





def 			_lowercase    (      __UpperCamelCase     :		str ):
      snake_case__					=   list(__UpperCamelCase )
      snake_case__					=   list(__UpperCamelCase )
      key_list.sort()
      letters_list.sort()

      if key_list != letters_list:
            sys.exit("""Error in the key or symbol set.""" )





def 			_lowercase    (      __UpperCamelCase     :		str   ,       __UpperCamelCase     :		str ):
      return translate_message(__UpperCamelCase   ,       __UpperCamelCase   ,       """encrypt""" )





def 			_lowercase    (      __UpperCamelCase     :		str   ,       __UpperCamelCase     :		str ):
      return translate_message(__UpperCamelCase   ,       __UpperCamelCase   ,       """decrypt""" )





def 			_lowercase    (      __UpperCamelCase     :		str   ,       __UpperCamelCase     :		str   ,       __UpperCamelCase     :		str ):
      snake_case__					=   """"""
      snake_case__					=   LETTERS
      snake_case__					=   key

      if mode == "decrypt":
            snake_case__	,			snake_case__					=   chars_b, chars_a

      for symbol in message:
            if symbol.upper() in chars_a:
                  snake_case__					=   chars_a.find(symbol.upper() )
                  if symbol.isupper():
                        translated += chars_b[sym_index].upper()
                  else:
                        translated += chars_b[sym_index].lower()
            else:
                  translated += symbol

      return translated





def 			_lowercase    (      ):
      snake_case__					=   list(__UpperCamelCase )
      random.shuffle(__UpperCamelCase )
      return "".join(__UpperCamelCase )


if __name__ == "__main__":
       main()









import functools
import operator

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


lowerCAmelCase						:   Dict										=    logging.get_logger(__name__)

lowerCAmelCase						:   str										=    {
    '''facebook/hubert-base-ls960''': '''https://huggingface.co/facebook/hubert-base-ls960/resolve/main/config.json''',
    # See all Hubert models at https://huggingface.co/models?filter=hubert
}
class     SCREAMING_SNAKE_CASE__     (						__a		):





       '''simple docstring'''




       UpperCamelCase__ :     Tuple				    =       '''hubert'''

       def __init__(						self       :						Union[str, Any]    ,		lowerCAmelCase__       :						List[Any]=32    ,		lowerCAmelCase__       :						Any=768    ,		lowerCAmelCase__       :						List[Any]=12    ,		lowerCAmelCase__       :						Tuple=12    ,		lowerCAmelCase__       :						Optional[int]=3072    ,		lowerCAmelCase__       :						Dict="gelu"    ,		lowerCAmelCase__       :						List[str]=0.1    ,		lowerCAmelCase__       :						str=0.1    ,		lowerCAmelCase__       :						List[str]=0.1    ,		lowerCAmelCase__       :						int=True    ,		lowerCAmelCase__       :						Tuple=0.0    ,		lowerCAmelCase__       :						Union[str, Any]=0.1    ,		lowerCAmelCase__       :						Dict=0.1    ,		lowerCAmelCase__       :						int=0.02    ,		lowerCAmelCase__       :						Optional[int]=1E-5    ,		lowerCAmelCase__       :						List[str]="group"    ,		lowerCAmelCase__       :						List[str]="gelu"    ,		lowerCAmelCase__       :						Any=(512, 512, 512, 512, 512, 512, 512)    ,		lowerCAmelCase__       :						str=(5, 2, 2, 2, 2, 2, 2)    ,		lowerCAmelCase__       :						Union[str, Any]=(10, 3, 3, 3, 3, 2, 2)    ,		lowerCAmelCase__       :						Optional[Any]=False    ,		lowerCAmelCase__       :						Dict=128    ,		lowerCAmelCase__       :						List[Any]=16    ,		lowerCAmelCase__       :						Optional[Any]=False    ,		lowerCAmelCase__       :						Optional[int]=True    ,		lowerCAmelCase__       :						List[Any]=0.05    ,		lowerCAmelCase__       :						Any=10    ,		lowerCAmelCase__       :						Dict=2    ,		lowerCAmelCase__       :						Dict=0.0    ,		lowerCAmelCase__       :						Tuple=10    ,		lowerCAmelCase__       :						List[str]=0    ,		lowerCAmelCase__       :						int="sum"    ,		lowerCAmelCase__       :						Optional[Any]=False    ,		lowerCAmelCase__       :						List[Any]=False    ,		lowerCAmelCase__       :						int=256    ,		lowerCAmelCase__       :						List[Any]=0    ,		lowerCAmelCase__       :						Union[str, Any]=1    ,		lowerCAmelCase__       :						Tuple=2    ,		**lowerCAmelCase__       :						str    ,		)			->    Union[str, Any]:
             super().__init__(**lowerCAmelCase__    ,		pad_token_id=lowerCAmelCase__    ,		bos_token_id=lowerCAmelCase__    ,		eos_token_id=lowerCAmelCase__							)
             snake_case__					=   hidden_size
             snake_case__					=   feat_extract_norm
             snake_case__					=   feat_extract_activation
             snake_case__					=   list(lowerCAmelCase__							)
             snake_case__					=   list(lowerCAmelCase__							)
             snake_case__					=   list(lowerCAmelCase__							)
             snake_case__					=   conv_bias
             snake_case__					=   num_conv_pos_embeddings
             snake_case__					=   num_conv_pos_embedding_groups
             snake_case__					=   len(self.conv_dim							)
             snake_case__					=   num_hidden_layers
             snake_case__					=   intermediate_size
             snake_case__					=   hidden_act
             snake_case__					=   num_attention_heads
             snake_case__					=   hidden_dropout
             snake_case__					=   attention_dropout
             snake_case__					=   activation_dropout
             snake_case__					=   feat_proj_layer_norm
             snake_case__					=   feat_proj_dropout
             snake_case__					=   final_dropout
             snake_case__					=   layerdrop
             snake_case__					=   layer_norm_eps
             snake_case__					=   initializer_range
             snake_case__					=   vocab_size
             snake_case__					=   do_stable_layer_norm
             snake_case__					=   use_weighted_layer_sum
             snake_case__					=   classifier_proj_size

             if (
                 (len(self.conv_stride							) != self.num_feat_extract_layers)
                 or (len(self.conv_kernel							) != self.num_feat_extract_layers)
                 or (len(self.conv_dim							) != self.num_feat_extract_layers)
             ):
                   raise ValueError(
                       """Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =="""
                       """ `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ="""
                       f''' {len(self.conv_dim							)}`, `len(config.conv_stride) = {len(self.conv_stride							)}`,'''
                       f''' `len(config.conv_kernel) = {len(self.conv_kernel							)}`.'''							)

             # fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
             snake_case__					=   apply_spec_augment
             snake_case__					=   mask_time_prob
             snake_case__					=   mask_time_length
             snake_case__					=   mask_time_min_masks
             snake_case__					=   mask_feature_prob
             snake_case__					=   mask_feature_length
             snake_case__					=   mask_feature_min_masks

             # ctc loss
             snake_case__					=   ctc_loss_reduction
             snake_case__					=   ctc_zero_infinity

       @property
       def UpperCAmelCase_						(						self       :						Union[str, Any]							)			->    Tuple:
             return functools.reduce(operator.mul    ,		self.conv_stride    ,		1							)






