


import math
import sys





def   _UpperCAmelCase       (     UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      Union[str, Any]       						=						""""""
      try:
            with open(UpperCAmelCase						,	"""rb"""      ) as binary_file:
                  __lowerCamelCase     :      int       						=						binary_file.read()
            for dat in data:
                  __lowerCamelCase     :      Optional[Any]       						=						f"""{dat:08b}"""
                  result += curr_byte
            return result
      except OSError:
            print("""File not accessible"""      )
            sys.exit()





def   _UpperCAmelCase       (     UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      Tuple       						=						{"""0""": """0""", """1""": """1"""}
      __lowerCamelCase     :      Dict       						=						"""""", """"""
      __lowerCamelCase     :      Optional[Any]       						=						len(UpperCAmelCase      )

      for i in range(len(UpperCAmelCase      )      ):
            curr_string += data_bits[i]
            if curr_string not in lexicon:
                  continue

            __lowerCamelCase     :      Optional[int]       						=						lexicon[curr_string]
            result += last_match_id
            __lowerCamelCase     :      Dict       						=						last_match_id + """0"""

            if math.loga(UpperCAmelCase      ).is_integer():
                  __lowerCamelCase     :      Dict       						=						{}
                  for curr_key in list(UpperCAmelCase      ):
                        __lowerCamelCase     :      Any       						=						lexicon.pop(UpperCAmelCase      )
                  __lowerCamelCase     :      int       						=						new_lex

            __lowerCamelCase     :      Optional[Any]       						=						last_match_id + """1"""
            index += 1
            __lowerCamelCase     :      int       						=						""""""
      return result





def   _UpperCAmelCase       (     UpperCAmelCase      :			str						,	UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      str       						=						8
      try:
            with open(UpperCAmelCase						,	"""wb"""      ) as opened_file:
                  __lowerCamelCase     :      Tuple       						=						[
                      to_write[i : i + byte_length]
                      for i in range(0						,	len(UpperCAmelCase      )						,	UpperCAmelCase      )
                  ]

                  if len(result_byte_array[-1]      ) % byte_length == 0:
                        result_byte_array.append("""10000000"""      )
                  else:
                        result_byte_array[-1] += "1" + "0" * (
                            byte_length - len(result_byte_array[-1]      ) - 1
                        )

                  for elem in result_byte_array[:-1]:
                        opened_file.write(int(UpperCAmelCase						,	2      ).to_bytes(1						,	byteorder="""big"""      )      )
      except OSError:
            print("""File not accessible"""      )
            sys.exit()





def   _UpperCAmelCase       (     UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      Dict       						=						0
      for letter in data_bits:
            if letter == "1":
                  break
            counter += 1

      __lowerCamelCase     :      Tuple       						=						data_bits[counter:]
      __lowerCamelCase     :      Optional[Any]       						=						data_bits[counter + 1 :]
      return data_bits





def   _UpperCAmelCase       (     UpperCAmelCase      :			str						,	UpperCAmelCase      :			str      ):
      """simple docstring"""




      __lowerCamelCase     :      Optional[Any]       						=						read_file_binary(UpperCAmelCase      )
      __lowerCamelCase     :      int       						=						remove_prefix(UpperCAmelCase      )
      __lowerCamelCase     :      List[Any]       						=						decompress_data(UpperCAmelCase      )
      write_file_binary(UpperCAmelCase						,	UpperCAmelCase      )


if __name__ == "__main__":
    compress(sys.argv[1], sys.argv[2])







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


__UpperCamelCase    :						Tuple     =							logging.get_logger(__name__)

__UpperCamelCase    :						Any     =							{
    'facebook/nllb-moe-54B': 'https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json',
}



class 							_UpperCamelCase (						A						):

   '''simple docstring'''







   a_				:							int    = "nllb-moe"
   a_				:							Optional[int]    = ["past_key_values"]
   a_				:							Optional[Any]    = {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}

   def __init__(  self  : int       ,  _lowerCamelCase  : Union[str, Any]=1_2_8_1_1_2       ,  _lowerCamelCase  : List[str]=1_0_2_4       ,  _lowerCamelCase  : Optional[int]=1_2       ,  _lowerCamelCase  : int=4_0_9_6       ,  _lowerCamelCase  : Union[str, Any]=1_6       ,  _lowerCamelCase  : int=1_2       ,  _lowerCamelCase  : Optional[int]=4_0_9_6       ,  _lowerCamelCase  : Any=1_6       ,  _lowerCamelCase  : Any=0.05       ,  _lowerCamelCase  : List[Any]=0.05       ,  _lowerCamelCase  : Tuple=True       ,  _lowerCamelCase  : Any=True       ,  _lowerCamelCase  : Optional[int]="relu"       ,  _lowerCamelCase  : Dict=1_0_2_4       ,  _lowerCamelCase  : Optional[int]=0.1       ,  _lowerCamelCase  : Optional[int]=0.1       ,  _lowerCamelCase  : Optional[int]=0.0       ,  _lowerCamelCase  : List[Any]=0.02       ,  _lowerCamelCase  : List[str]=2       ,  _lowerCamelCase  : List[str]=True       ,  _lowerCamelCase  : Union[str, Any]=False       ,  _lowerCamelCase  : Optional[Any]="float32"       ,  _lowerCamelCase  : Union[str, Any]=False       ,  _lowerCamelCase  : Tuple=1_2_8       ,  _lowerCamelCase  : Dict=6_4       ,  _lowerCamelCase  : Any=4       ,  _lowerCamelCase  : List[Any]=4       ,  _lowerCamelCase  : str=0.001       ,  _lowerCamelCase  : Dict=0.001       ,  _lowerCamelCase  : Any="all"       ,  _lowerCamelCase  : Optional[Any]=False       ,  _lowerCamelCase  : List[Any]=False       ,  _lowerCamelCase  : Optional[Any]=1.0       ,  _lowerCamelCase  : List[str]=0.2       ,  _lowerCamelCase  : List[Any]=1       ,  _lowerCamelCase  : str=0       ,  _lowerCamelCase  : int=2       ,  _lowerCamelCase  : int=False       ,  **_lowerCamelCase  : List[str]       ,  ):






         '''simple docstring'''



         __lowerCamelCase     :      Optional[Any]       						=						vocab_size
         __lowerCamelCase     :      str       						=						max_position_embeddings
         __lowerCamelCase     :      int       						=						d_model
         __lowerCamelCase     :      Optional[Any]       						=						encoder_ffn_dim
         __lowerCamelCase     :      str       						=						encoder_layers
         __lowerCamelCase     :      Tuple       						=						encoder_attention_heads
         __lowerCamelCase     :      Union[str, Any]       						=						decoder_ffn_dim
         __lowerCamelCase     :      Dict       						=						decoder_layers
         __lowerCamelCase     :      Any       						=						decoder_attention_heads
         __lowerCamelCase     :      Union[str, Any]       						=						dropout
         __lowerCamelCase     :      Dict       						=						attention_dropout
         __lowerCamelCase     :      int       						=						activation_dropout
         __lowerCamelCase     :      Union[str, Any]       						=						activation_function
         __lowerCamelCase     :      Optional[int]       						=						init_std
         __lowerCamelCase     :      Union[str, Any]       						=						encoder_layerdrop
         __lowerCamelCase     :      Dict       						=						decoder_layerdrop
         __lowerCamelCase     :      List[str]       						=						use_cache
         __lowerCamelCase     :      Any       						=						encoder_layers
         __lowerCamelCase     :      List[Any]       						=						scale_embedding  # scale factor will be sqrt(d_model) if True
         __lowerCamelCase     :      Optional[Any]       						=						router_z_loss_coef
         __lowerCamelCase     :      Union[str, Any]       						=						router_aux_loss_coef
         __lowerCamelCase     :      Dict       						=						decoder_sparse_step
         __lowerCamelCase     :      Optional[int]       						=						encoder_sparse_step
         __lowerCamelCase     :      Any       						=						num_experts
         __lowerCamelCase     :      int       						=						expert_capacity
         __lowerCamelCase     :      Dict       						=						router_bias
         if router_dtype not in ["float32", "float16", "bfloat16"]:
               raise ValueError(F"""`router_dtype` must be one of 'float32', 'float16' or 'bfloat16', got {router_dtype}"""							)
         __lowerCamelCase     :      Tuple       						=						router_dtype

         __lowerCamelCase     :      Dict       						=						router_ignore_padding_tokens
         __lowerCamelCase     :      str       						=						batch_prioritized_routing
         __lowerCamelCase     :      List[str]       						=						second_expert_policy
         __lowerCamelCase     :      Tuple       						=						normalize_router_prob_before_dropping
         __lowerCamelCase     :      Dict       						=						moe_eval_capacity_token_fraction
         __lowerCamelCase     :      Optional[int]       						=						moe_token_dropout
         __lowerCamelCase     :      Dict       						=						output_router_logits
         super().__init__(
             pad_token_id=_lowerCamelCase       ,  bos_token_id=_lowerCamelCase       ,  eos_token_id=_lowerCamelCase       ,  is_encoder_decoder=_lowerCamelCase       ,  decoder_start_token_id=_lowerCamelCase       ,  **_lowerCamelCase       ,  )



