


from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional

from packaging import version


if TYPE_CHECKING:
       from ... import PreTrainedTokenizer, TensorType

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import is_torch_available, logging


__UpperCamelCase				:  Any      					=							logging.get_logger(__name__)

__UpperCamelCase				:  Union[str, Any]      					=							{
    'bigscience/bloom': 'https://huggingface.co/bigscience/bloom/resolve/main/config.json',
    'bigscience/bloom-560m': 'https://huggingface.co/bigscience/bloom-560m/blob/main/config.json',
    'bigscience/bloom-1b1': 'https://huggingface.co/bigscience/bloom-1b1/blob/main/config.json',
    'bigscience/bloom-1b7': 'https://huggingface.co/bigscience/bloom-1b7/blob/main/config.json',
    'bigscience/bloom-3b': 'https://huggingface.co/bigscience/bloom-3b/blob/main/config.json',
    'bigscience/bloom-7b1': 'https://huggingface.co/bigscience/bloom-7b1/blob/main/config.json',
}





class  lowerCAmelCase__(    snake_case__						):






    '''simple docstring'''





    A_  :     Any			= 'bloom'
    A_  :     List[Any]			= ['past_key_values']
    A_  :     str			= {
        'num_hidden_layers': 'n_layer',
        'num_attention_heads': 'n_head',
    }





    def __init__(	self				:   str       ,   __snake_case				:   str=250_880       ,   __snake_case				:   Union[str, Any]=64       ,   __snake_case				:   Optional[int]=2       ,   __snake_case				:   List[Any]=8       ,   __snake_case				:   Any=1E-5       ,   __snake_case				:   List[Any]=0.02       ,   __snake_case				:   int=True       ,   __snake_case				:   int=1       ,   __snake_case				:   Optional[Any]=2       ,   __snake_case				:   Optional[Any]=False       ,   __snake_case				:   Optional[Any]=0.0       ,   __snake_case				:   str=0.0       ,   __snake_case				:   Any=1       ,   __snake_case				:   List[Any]=False       ,   **__snake_case				:   List[Any]       ,   ):





       '''simple docstring'''
       UpperCAmelCase_							:      List[str]						=   vocab_size
       # Backward compatibility with n_embed kwarg
       UpperCAmelCase_							:      Tuple						=   kwargs.pop('''n_embed'''       ,   __snake_case	)
       UpperCAmelCase_							:      Any						=   hidden_size if n_embed is None else n_embed
       UpperCAmelCase_							:      List[Any]						=   n_layer
       UpperCAmelCase_							:      Optional[Any]						=   n_head
       UpperCAmelCase_							:      Optional[Any]						=   layer_norm_epsilon
       UpperCAmelCase_							:      Union[str, Any]						=   initializer_range
       UpperCAmelCase_							:      int						=   use_cache
       UpperCAmelCase_							:      str						=   pretraining_tp
       UpperCAmelCase_							:      Union[str, Any]						=   apply_residual_connection_post_layernorm
       UpperCAmelCase_							:      Tuple						=   hidden_dropout
       UpperCAmelCase_							:      int						=   attention_dropout

       UpperCAmelCase_							:      Union[str, Any]						=   bos_token_id
       UpperCAmelCase_							:      List[Any]						=   eos_token_id
       UpperCAmelCase_							:      Tuple						=   slow_but_exact

       super().__init__(bos_token_id=__snake_case       ,   eos_token_id=__snake_case       ,   **__snake_case	)





class  lowerCAmelCase__(    snake_case__						):






    '''simple docstring'''





    A_  :     Optional[Any]			= version.parse('1.12'						)





    def __init__(	self				:   List[str]       ,   __snake_case				:   PretrainedConfig       ,   __snake_case				:   str = "default"       ,   __snake_case				:   List[PatchingSpec] = None       ,   __snake_case				:   bool = False       ,   ):





       '''simple docstring'''
       super().__init__(__snake_case       ,   task=__snake_case       ,   patching_specs=__snake_case       ,   use_past=__snake_case	)
       if not getattr(self._config       ,   '''pad_token_id'''       ,   __snake_case	):
          # TODO: how to do that better?
          UpperCAmelCase_							:      Dict						=   0





    @property
    def 					_lowerCamelCase (	self				:   Tuple	):





       '''simple docstring'''
       UpperCAmelCase_							:      List[str]						=   OrderedDict({'''input_ids''': {0: '''batch''', 1: '''sequence'''}}	)
       if self.use_past:
          # BLOOM stores values on dynamic axis 2. For more details see: https://github.com/huggingface/transformers/pull/18344
          self.fill_with_past_key_values_(__snake_case       ,   direction='''inputs'''       ,   inverted_values_shape=__snake_case	)
          UpperCAmelCase_							:      List[Any]						=   {0: '''batch''', 1: '''past_sequence + sequence'''}
       else:
          UpperCAmelCase_							:      str						=   {0: '''batch''', 1: '''sequence'''}

       return common_inputs





    @property
    def 					_lowerCamelCase (	self				:   Dict	):





       '''simple docstring'''
       return self._config.n_layer





    @property
    def 					_lowerCamelCase (	self				:   List[str]	):





       '''simple docstring'''
       return self._config.n_head





    @property
    def 					_lowerCamelCase (	self				:   Optional[Any]	):





       '''simple docstring'''
       return 1E-3





    def 					_lowerCamelCase (	self				:   Union[str, Any]       ,   __snake_case				:   "PreTrainedTokenizer"       ,   __snake_case				:   int = -1       ,   __snake_case				:   int = -1       ,   __snake_case				:   bool = False       ,   __snake_case				:   Optional["TensorType"] = None       ,   ):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[int]						=   super(__snake_case       ,   self	).generate_dummy_inputs(
           __snake_case       ,   batch_size=__snake_case       ,   seq_length=__snake_case       ,   is_pair=__snake_case       ,   framework=__snake_case	)

       # We need to order the input in the way they appears in the forward()
       UpperCAmelCase_							:      List[Any]						=   OrderedDict({'''input_ids''': common_inputs['''input_ids''']}	)

       # Need to add the past_keys
       if self.use_past:
          if not is_torch_available():
             raise ValueError('''Cannot generate dummy past_keys inputs without PyTorch installed.'''	)
          else:
             import torch

             UpperCAmelCase_		,      UpperCAmelCase_							:      Any						=   common_inputs['''input_ids'''].shape
             # Not using the same length for past_key_values
             UpperCAmelCase_							:      Tuple						=   seqlen + 2
             UpperCAmelCase_							:      Optional[Any]						=   self._config.hidden_size // self.num_attention_heads
             UpperCAmelCase_							:      List[str]						=   (
                 batch * self.num_attention_heads,
                 head_dim,
                 past_key_values_length,
             )
             UpperCAmelCase_							:      Optional[Any]						=   (
                 batch * self.num_attention_heads,
                 past_key_values_length,
                 head_dim,
             )
             UpperCAmelCase_							:      Union[str, Any]						=   [
                 (torch.zeros(__snake_case	), torch.zeros(__snake_case	)) for _ in range(self.num_layers	)
             ]

       UpperCAmelCase_							:      Tuple						=   common_inputs['''attention_mask''']
       if self.use_past:
          UpperCAmelCase_							:      Optional[int]						=   ordered_inputs['''attention_mask'''].dtype
          UpperCAmelCase_							:      Tuple						=   torch.cat(
              [ordered_inputs['''attention_mask'''], torch.ones(__snake_case       ,   __snake_case       ,   dtype=__snake_case	)]       ,   dim=1	)

       return ordered_inputs





    @property
    def 					_lowerCamelCase (	self				:   Optional[Any]	):





       '''simple docstring'''
       return 13



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





class  lowerCAmelCase__:






    '''simple docstring'''





    def __init__(	self				:   List[str]       ,   __snake_case				:   Union[str, Any]	):





       '''simple docstring'''
       UpperCAmelCase_							:      str						=   data
       UpperCAmelCase_							:      List[Any]						=   [0X67_45_23_01, 0Xef_cd_ab_89, 0X98_ba_dc_fe, 0X10_32_54_76, 0Xc3_d2_e1_f0]





    @staticmethod
    def 					_lowerCamelCase (	__snake_case				:   Dict       ,   __snake_case				:   Dict	):





       '''simple docstring'''
       return ((n << b) | (n >> (32 - b))) & 0Xff_ff_ff_ff





    def 					_lowerCamelCase (	self				:   Dict	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[int]						=   B'''\x80''' + B'''\x00''' * (63 - (len(self.data	) + 8) % 64)
       UpperCAmelCase_							:      Union[str, Any]						=   self.data + padding + struct.pack('''>Q'''       ,   8 * len(self.data	)	)
       return padded_data





    def 					_lowerCamelCase (	self				:   Tuple	):





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





    def 					_lowerCamelCase (	self				:   Dict       ,   __snake_case				:   Optional[int]	):





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





    def 					_lowerCamelCase (	self				:   Union[str, Any]	):





       '''simple docstring'''
       UpperCAmelCase_							:      Optional[int]						=   self.padding()
       UpperCAmelCase_							:      str						=   self.split_blocks()
       for block in self.blocks:
          UpperCAmelCase_							:      Any						=   self.expand_block(__snake_case	)
          UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_							:      List[str]						=   self.h
          for i in range(0       ,   80	):
             if 0 <= i < 20:
                UpperCAmelCase_							:      Optional[Any]						=   (b & c) | ((~b) & d)
                UpperCAmelCase_							:      Optional[Any]						=   0X5a_82_79_99
             elif 20 <= i < 40:
                UpperCAmelCase_							:      List[Any]						=   b ^ c ^ d
                UpperCAmelCase_							:      str						=   0X6e_d9_eb_a1
             elif 40 <= i < 60:
                UpperCAmelCase_							:      str						=   (b & c) | (b & d) | (c & d)
                UpperCAmelCase_							:      Optional[int]						=   0X8f_1b_bc_dc
             elif 60 <= i < 80:
                UpperCAmelCase_							:      Union[str, Any]						=   b ^ c ^ d
                UpperCAmelCase_							:      Dict						=   0Xca_62_c1_d6
             UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_		,      UpperCAmelCase_							:      int						=   (
                 self.rotate(__snake_case       ,   5	) + f + e + k + expanded_block[i] & 0Xff_ff_ff_ff,
                 a,
                 self.rotate(__snake_case       ,   30	),
                 c,
                 d,
             )
          UpperCAmelCase_							:      Optional[Any]						=   (
              self.h[0] + a & 0Xff_ff_ff_ff,
              self.h[1] + b & 0Xff_ff_ff_ff,
              self.h[2] + c & 0Xff_ff_ff_ff,
              self.h[3] + d & 0Xff_ff_ff_ff,
              self.h[4] + e & 0Xff_ff_ff_ff,
          )
       return ("{:08x}" * 5).format(*self.h	)





def      snake_case_						( ):
   UpperCAmelCase_							:      Tuple						=   B'''Test String'''
   assert SHAaHash(__lowercase       ).final_hash() == hashlib.shaa(__lowercase       ).hexdigest()  # noqa: S324
def      snake_case_						( ):
   UpperCAmelCase_							:      int						=   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_							:      List[Any]						=   parser.parse_args()
   UpperCAmelCase_							:      Optional[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_							:      List[str]						=   f.read()
   else:
      UpperCAmelCase_							:      Tuple						=   bytes(__lowercase			,       '''utf-8'''       )
   print(SHAaHash(__lowercase       ).final_hash()       )


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

       doctest.testmod()