
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowercase__		:List[Any]   =    {
    "configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
    "convert_funnel_original_tf_checkpoint_to_pytorch": [],
    "tokenization_funnel": ["FunnelTokenizer"],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:List[str]   =    ["FunnelTokenizerFast"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Tuple   =    [
							    "FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "FunnelBaseModel",
							    "FunnelForMaskedLM",
							    "FunnelForMultipleChoice",
							    "FunnelForPreTraining",
							    "FunnelForQuestionAnswering",
							    "FunnelForSequenceClassification",
							    "FunnelForTokenClassification",
							    "FunnelModel",
							    "FunnelPreTrainedModel",
							    "load_tf_weights_in_funnel",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase__		:Any   =    [
							    "TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "TFFunnelBaseModel",
							    "TFFunnelForMaskedLM",
							    "TFFunnelForMultipleChoice",
							    "TFFunnelForPreTraining",
							    "TFFunnelForQuestionAnswering",
							    "TFFunnelForSequenceClassification",
							    "TFFunnelForTokenClassification",
							    "TFFunnelModel",
							    "TFFunnelPreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_funnel import FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP, FunnelConfig
							from .tokenization_funnel import FunnelTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_funnel_fast import FunnelTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_funnel import (
														    FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
														    FunnelBaseModel,
														    FunnelForMaskedLM,
														    FunnelForMultipleChoice,
														    FunnelForPreTraining,
														    FunnelForQuestionAnswering,
														    FunnelForSequenceClassification,
														    FunnelForTokenClassification,
														    FunnelModel,
														    FunnelPreTrainedModel,
														    load_tf_weights_in_funnel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_funnel import (
														    TF_FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFFunnelBaseModel,
														    TFFunnelForMaskedLM,
														    TFFunnelForMultipleChoice,
														    TFFunnelForPreTraining,
														    TFFunnelForQuestionAnswering,
														    TFFunnelForSequenceClassification,
														    TFFunnelForTokenClassification,
														    TFFunnelModel,
														    TFFunnelPreTrainedModel,
														)

else:
							import sys

							lowercase__		:Union[str, Any]   =    _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)







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







class 						__magic_name__			:

   '''simple docstring'''




   def __init__(				self,    lowercase_       )							->    List[str]:






     """simple docstring"""






     a__  =data
     a__  =[0X67452301, 0Xefcdab89, 0X98badcfe, 0X10325476, 0Xc3d2e1f0]



   @staticmethod
   def  _UpperCAmelCase (				lowercase_,    lowercase_       )							->    Union[str, Any]:






     """simple docstring"""






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



   def  _UpperCAmelCase (				self       )							->    Optional[int]:






     """simple docstring"""






     a__  =b'''\x80''' + b'''\x00''' * (63 - (len(self.data       ) + 8) % 64)
     a__  =self.data + padding + struct.pack('''>Q''',    8 * len(self.data       )       )
     return padded_data



   def  _UpperCAmelCase (				self       )							->    Any:






     """simple docstring"""






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



   def  _UpperCAmelCase (				self,    lowercase_       )							->    List[Any]:






     """simple docstring"""






     a__  =list(struct.unpack('''>16L''',    lowercase_       )       ) + [0] * 64
     for i in range(16,    80       ):
       a__  =self.rotate((w[i - 3] ^ w[i - 8] ^ w[i - 14] ^ w[i - 16]),    1       )
     return w



   def  _UpperCAmelCase (				self       )							->    Any:






     """simple docstring"""






     a__  =self.padding()
     a__  =self.split_blocks()
     for block in self.blocks:
       a__  =self.expand_block(lowercase_       )
       a__,      a__,      a__,      a__,      a__  =self.h
       for i in range(0,    80       ):
         if 0 <= i < 20:
           a__  =(b & c) | ((~b) & d)
           a__  =0X5a827999
         elif 20 <= i < 40:
           a__  =b ^ c ^ d
           a__  =0X6ed9eba1
         elif 40 <= i < 60:
           a__  =(b & c) | (b & d) | (c & d)
           a__  =0X8f1bbcdc
         elif 60 <= i < 80:
           a__  =b ^ c ^ d
           a__  =0Xca62c1d6
         a__,      a__,      a__,      a__,      a__  =(
             self.rotate(lowercase_,    5       ) + f + e + k + expanded_block[i] & 0Xffffffff,
             a,
             self.rotate(lowercase_,    30       ),
             c,
             d,
         )
       a__  =(
           self.h[0] + a & 0Xffffffff,
           self.h[1] + b & 0Xffffffff,
           self.h[2] + c & 0Xffffffff,
           self.h[3] + d & 0Xffffffff,
           self.h[4] + e & 0Xffffffff,
       )
     return ("{:08x}" * 5).format(*self.h       )





def 			UpperCAmelCase__				(			):





  '''simple docstring'''







  a__  =b'''Test String'''
  assert SHAaHash(_A							).final_hash() == hashlib.shaa(_A							).hexdigest()  # noqa: S324




def 			UpperCAmelCase__				(			):





  '''simple docstring'''







  a__  =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'''							)
  a__  =parser.parse_args()
  a__  =args.input_string
  # In any case hash input should be a bytestring
  if args.input_file:
    with open(args.input_file	,      '''rb'''							) as f:
      a__  =f.read()
  else:
    a__  =bytes(_A	,      '''utf-8'''							)
  print(SHAaHash(_A							).final_hash()							)


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

       doctest.testmod()
