



"""simple docstring"""
import argparse
import hashlib  # hashlib is only used inside the Test class
import struct



class  SCREAMING_SNAKE_CASE__    :

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





    '''simple docstring'''




    UpperCAmelCase      :   str      =      data
    UpperCAmelCase      :   List[str]      =      [0x6_7_4_5_2_3_0_1, 0xE_F_C_D_A_B_8_9, 0x9_8_B_A_D_C_F_E, 0x1_0_3_2_5_4_7_6, 0xC_3_D_2_E_1_F_0]

   @staticmethod
   def       SCREAMING_SNAKE_CASE	(  _SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE		)    -> List[Any]:





    '''simple docstring'''




    return ((n << b) | (n >> (32 - b))) & 0xF_F_F_F_F_F_F_F

   def       SCREAMING_SNAKE_CASE	(  self		)    -> Tuple:





    '''simple docstring'''




    UpperCAmelCase      :   Dict      =      B"\x80" + B"\x00" * (63 - (len(self.data		) + 8) % 64)
    UpperCAmelCase      :   Dict      =      self.data + padding + struct.pack(""">Q""" ,	8 * len(self.data		)		)
    return padded_data

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





    '''simple docstring'''




    return [
        self.padded_data[i : i + 64] for i in range(0 ,	len(self.padded_data		) ,	64		)
    ]

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





    '''simple docstring'''




    UpperCAmelCase      :   Union[str, Any]      =      list(struct.unpack(""">16L""" ,	snake_case__		)		) + [0] * 64
    for i in range(16 ,	80		):
     UpperCAmelCase      :   Union[str, Any]      =      self.rotate((w[i - 3] ^ w[i - 8] ^ w[i - 14] ^ w[i - 16]) ,	1		)
    return w




   def       SCREAMING_SNAKE_CASE	(  self		)    -> str:





    '''simple docstring'''




    UpperCAmelCase      :   str      =      self.padding()
    UpperCAmelCase      :   Union[str, Any]      =      self.split_blocks()
    for block in self.blocks:
     UpperCAmelCase      :   str      =      self.expand_block(snake_case__		)
     UpperCAmelCase      :   str      =      self.h
     for i in range(0 ,	80		):
      if 0 <= i < 20:
       UpperCAmelCase      :   List[Any]      =      (b & c) | ((~b) & d)
       UpperCAmelCase      :   Tuple      =      0x5_A_8_2_7_9_9_9
      elif 20 <= i < 40:
       UpperCAmelCase      :   Optional[int]      =      b ^ c ^ d
       UpperCAmelCase      :   Optional[Any]      =      0x6_E_D_9_E_B_A_1
      elif 40 <= i < 60:
       UpperCAmelCase      :   Optional[int]      =      (b & c) | (b & d) | (c & d)
       UpperCAmelCase      :   Union[str, Any]      =      0x8_F_1_B_B_C_D_C
      elif 60 <= i < 80:
       UpperCAmelCase      :   Optional[Any]      =      b ^ c ^ d
       UpperCAmelCase      :   Tuple      =      0xC_A_6_2_C_1_D_6
      UpperCAmelCase      :   Tuple      =      (
          self.rotate(snake_case__ ,	5		) + f + e + k + expanded_block[i] & 0xF_F_F_F_F_F_F_F,
          a,
          self.rotate(snake_case__ ,	30		),
          c,
          d,
      )
     UpperCAmelCase      :   Any      =      (
         self.h[0] + a & 0xF_F_F_F_F_F_F_F,
         self.h[1] + b & 0xF_F_F_F_F_F_F_F,
         self.h[2] + c & 0xF_F_F_F_F_F_F_F,
         self.h[3] + d & 0xF_F_F_F_F_F_F_F,
         self.h[4] + e & 0xF_F_F_F_F_F_F_F,
     )
    return ("{:08x}" * 5).format(*self.h		)

def  _snake_case		(		):
 UpperCAmelCase      :   List[Any]      =      b"Test String"
 assert SHAaHash(lowercase__		).final_hash() == hashlib.shaa(lowercase__		).hexdigest()  # noqa: S324

def  _snake_case		(		):
 UpperCAmelCase      :   Any      =      argparse.ArgumentParser(description="""Process some strings or files"""		)
 parser.add_argument(
     """--string"""     ,						dest="""input_string"""     ,						default="""Hello World!! Welcome to Cryptography"""     ,						help="""Hash the string"""     ,						)
 parser.add_argument("""--file"""     ,						dest="""input_file"""     ,						help="""Hash contents of a file"""		)
 UpperCAmelCase      :   Optional[int]      =      parser.parse_args()
 UpperCAmelCase      :   Union[str, Any]      =      args.input_string
 # In any case hash input should be a bytestring
 if args.input_file:
  with open(args.input_file     ,						"""rb"""		) as f:
   UpperCAmelCase      :   Dict      =      f.read()
 else:
  UpperCAmelCase      :   int      =      bytes(lowercase__     ,						"""utf-8"""		)
 print(SHAaHash(lowercase__		).final_hash()		)


if __name__ == "__main__":
      main()
      import doctest

      doctest.testmod()


'''simple docstring'''





import functools
import operator

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


SCREAMING_SNAKE_CASE     =       logging.get_logger(__name__)

SCREAMING_SNAKE_CASE     =       {
    """microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
    # See all WavLM models at https://huggingface.co/models?filter=wavlm
}






class 							UpperCAmelCase_							(    A				):

 '''simple docstring'''
 lowercase_					:    List[str]				=							"wavlm"







 def __init__(					self		:  Optional[int]			,				snake_case__		:  Dict=32			,				snake_case__		:  Optional[Any]=7_68			,				snake_case__		:  Tuple=12			,				snake_case__		:  List[Any]=12			,				snake_case__		:  List[str]=30_72			,				snake_case__		:  Tuple="gelu"			,				snake_case__		:  Optional[Any]=0.1			,				snake_case__		:  List[str]=0.1			,				snake_case__		:  Any=0.1			,				snake_case__		:  List[Any]=0.0			,				snake_case__		:  Dict=0.1			,				snake_case__		:  List[Any]=0.1			,				snake_case__		:  Union[str, Any]=0.02			,				snake_case__		:  int=1e-5			,				snake_case__		:  Dict="group"			,				snake_case__		:  Any="gelu"			,				snake_case__		:  List[Any]=(5_12, 5_12, 5_12, 5_12, 5_12, 5_12, 5_12)			,				snake_case__		:  int=(5, 2, 2, 2, 2, 2, 2)			,				snake_case__		:  Dict=(10, 3, 3, 3, 3, 2, 2)			,				snake_case__		:  Tuple=False			,				snake_case__		:  int=1_28			,				snake_case__		:  Dict=16			,				snake_case__		:  int=3_20			,				snake_case__		:  Dict=8_00			,				snake_case__		:  List[str]=False			,				snake_case__		:  Union[str, Any]=True			,				snake_case__		:  str=0.05			,				snake_case__		:  List[Any]=10			,				snake_case__		:  Tuple=2			,				snake_case__		:  Optional[int]=0.0			,				snake_case__		:  int=10			,				snake_case__		:  Any=3_20			,				snake_case__		:  Dict=2			,				snake_case__		:  Optional[int]=0.1			,				snake_case__		:  Union[str, Any]=1_00			,				snake_case__		:  Dict=2_56			,				snake_case__		:  List[Any]=2_56			,				snake_case__		:  List[str]=0.1			,				snake_case__		:  List[Any]="mean"			,				snake_case__		:  int=False			,				snake_case__		:  Any=False			,				snake_case__		:  Any=2_56			,				snake_case__		:  Union[str, Any]=(5_12, 5_12, 5_12, 5_12, 15_00)			,				snake_case__		:  Union[str, Any]=(5, 3, 3, 1, 1)			,				snake_case__		:  Optional[Any]=(1, 2, 3, 1, 1)			,				snake_case__		:  List[Any]=5_12			,				snake_case__		:  str=80			,				snake_case__		:  Any=0			,				snake_case__		:  str=1			,				snake_case__		:  Union[str, Any]=2			,				snake_case__		:  int=False			,				snake_case__		:  Union[str, Any]=3			,				snake_case__		:  Union[str, Any]=2			,				snake_case__		:  List[str]=3			,				snake_case__		:  List[Any]=None			,				**snake_case__		:  int			,				):



   '''simple docstring'''




   super().__init__(**snake_case__			,				pad_token_id=snake_case__			,				bos_token_id=snake_case__			,				eos_token_id=snake_case__ )
   UpperCAmelCase__      :					Union[str, Any]				       =							hidden_size
   UpperCAmelCase__      :					List[str]				       =							feat_extract_norm
   UpperCAmelCase__      :					int				       =							feat_extract_activation
   UpperCAmelCase__      :					Optional[int]				       =							list(snake_case__ )
   UpperCAmelCase__      :					Tuple				       =							list(snake_case__ )
   UpperCAmelCase__      :					Tuple				       =							list(snake_case__ )
   UpperCAmelCase__      :					Tuple				       =							conv_bias
   UpperCAmelCase__      :					List[Any]				       =							num_buckets
   UpperCAmelCase__      :					Union[str, Any]				       =							max_bucket_distance
   UpperCAmelCase__      :					Tuple				       =							num_conv_pos_embeddings
   UpperCAmelCase__      :					Union[str, Any]				       =							num_conv_pos_embedding_groups
   UpperCAmelCase__      :					Optional[Any]				       =							len(self.conv_dim )
   UpperCAmelCase__      :					Optional[int]				       =							num_hidden_layers
   UpperCAmelCase__      :					Tuple				       =							intermediate_size
   UpperCAmelCase__      :					List[str]				       =							hidden_act
   UpperCAmelCase__      :					List[str]				       =							num_attention_heads
   UpperCAmelCase__      :					Any				       =							hidden_dropout
   UpperCAmelCase__      :					List[Any]				       =							attention_dropout
   UpperCAmelCase__      :					Optional[int]				       =							activation_dropout
   UpperCAmelCase__      :					Optional[Any]				       =							feat_proj_dropout
   UpperCAmelCase__      :					List[str]				       =							final_dropout
   UpperCAmelCase__      :					int				       =							layerdrop
   UpperCAmelCase__      :					int				       =							layer_norm_eps
   UpperCAmelCase__      :					Tuple				       =							initializer_range
   UpperCAmelCase__      :					Union[str, Any]				       =							num_ctc_classes
   UpperCAmelCase__      :					Any				       =							vocab_size
   UpperCAmelCase__      :					Dict				       =							do_stable_layer_norm
   UpperCAmelCase__      :					List[Any]				       =							use_weighted_layer_sum
   UpperCAmelCase__      :					Optional[Any]				       =							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
   UpperCAmelCase__      :					List[str]				       =							apply_spec_augment
   UpperCAmelCase__      :					Union[str, Any]				       =							mask_time_prob
   UpperCAmelCase__      :					List[Any]				       =							mask_time_length
   UpperCAmelCase__      :					List[str]				       =							mask_time_min_masks
   UpperCAmelCase__      :					List[str]				       =							mask_feature_prob
   UpperCAmelCase__      :					Dict				       =							mask_feature_length

   # parameters for pretraining with codevector quantized representations
   UpperCAmelCase__      :					Dict				       =							num_codevectors_per_group
   UpperCAmelCase__      :					Union[str, Any]				       =							num_codevector_groups
   UpperCAmelCase__      :					int				       =							contrastive_logits_temperature
   UpperCAmelCase__      :					List[str]				       =							num_negatives
   UpperCAmelCase__      :					List[str]				       =							codevector_dim
   UpperCAmelCase__      :					List[Any]				       =							proj_codevector_dim
   UpperCAmelCase__      :					List[Any]				       =							diversity_loss_weight

   # ctc loss
   UpperCAmelCase__      :					Tuple				       =							ctc_loss_reduction
   UpperCAmelCase__      :					Any				       =							ctc_zero_infinity

   # adapter
   UpperCAmelCase__      :					int				       =							add_adapter
   UpperCAmelCase__      :					List[Any]				       =							adapter_kernel_size
   UpperCAmelCase__      :					Dict				       =							adapter_stride
   UpperCAmelCase__      :					Dict				       =							num_adapter_layers
   UpperCAmelCase__      :					Union[str, Any]				       =							output_hidden_size or hidden_size

   # SequenceClassification-specific parameter. Feel free to ignore for other classes.
   UpperCAmelCase__      :					str				       =							classifier_proj_size

   # XVector-specific parameters. Feel free to ignore for other classes.
   UpperCAmelCase__      :					Any				       =							list(snake_case__ )
   UpperCAmelCase__      :					List[Any]				       =							list(snake_case__ )
   UpperCAmelCase__      :					List[str]				       =							list(snake_case__ )
   UpperCAmelCase__      :					Dict				       =							xvector_output_dim







 @property
 def 							UpperCamelCase  (					self		:  int ):



   '''simple docstring'''




   return functools.reduce(operator.mul			,				self.conv_stride			,				1 )



