



import math
import sys

def   _lowerCAmelCase   (						A__	):
      lowercase__     =  ''
      try:
            with open(A__						,  'rb'	) as binary_file:
                  lowercase__     =  binary_file.read()
            for dat in data:
                  lowercase__     =  F'''{dat:08b}'''
                  result += curr_byte
            return result
      except OSError:
            print('File not accessible'	)
            sys.exit()

def   _lowerCAmelCase   (						A__	):
      lowercase__     =  {'0': '0', '1': '1'}
      lowercase__,	lowercase__     =  '', ''
      lowercase__     =  len(A__	)

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

            lowercase__     =  lexicon[curr_string]
            result += last_match_id
            lowercase__     =  last_match_id + '0'

            if math.loga(A__	).is_integer():
                  lowercase__     =  {}
                  for curr_key in list(A__	):
                        lowercase__     =  lexicon.pop(A__	)
                  lowercase__     =  new_lex

            lowercase__     =  last_match_id + '1'
            index += 1
            lowercase__     =  ''
      return result

def   _lowerCAmelCase   (						A__						,  A__	):
      lowercase__     =  8
      try:
            with open(A__						,  'wb'	) as opened_file:
                  lowercase__     =  [
                      to_write[i : i + byte_length]
                      for i in range(0						,  len(A__	)						,  A__	)
                  ]

                  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(A__						,  2	).to_bytes(1						,  byteorder='big'	)	)
      except OSError:
            print('File not accessible'	)
            sys.exit()

def   _lowerCAmelCase   (						A__	):
      lowercase__     =  0
      for letter in data_bits:
            if letter == "1":
                  break
            counter += 1

      lowercase__     =  data_bits[counter:]
      lowercase__     =  data_bits[counter + 1 :]
      return data_bits

def   _lowerCAmelCase   (						A__						,  A__	):
      lowercase__     =  read_file_binary(A__	)
      lowercase__     =  remove_prefix(A__	)
      lowercase__     =  decompress_data(A__	)
      write_file_binary(A__						,  A__	)


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





from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


a__      :				Union[str, Any]   	=			logging.get_logger(__name__)

a__      :				Optional[Any]   	=			{
    "google/umt5-small": "https://huggingface.co/google/umt5-small/resolve/main/config.json",
    # See all umt5 models at https://huggingface.co/models?filter=umt5
}



class       UpperCAmelCase__(							lowerCamelCase	):

   '''simple docstring'''




   A    :  Union[str, Any]       				=    "umt5"
   A    :  List[str]       				=    ["past_key_values"]


   def __init__(						self  :			List[Any]			,				lowerCAmelCase  :			Optional[int]=25_01_12			,				lowerCAmelCase  :			str=5_12			,				lowerCAmelCase  :			List[Any]=64			,				lowerCAmelCase  :			Optional[int]=10_24			,				lowerCAmelCase  :			Union[str, Any]=8			,				lowerCAmelCase  :			Tuple=None			,				lowerCAmelCase  :			Optional[Any]=6			,				lowerCAmelCase  :			int=32			,				lowerCAmelCase  :			int=1_28			,				lowerCAmelCase  :			List[str]=0.1			,				lowerCAmelCase  :			List[str]=1E-6			,				lowerCAmelCase  :			Optional[int]=1.0			,				lowerCAmelCase  :			Optional[Any]="gated-gelu"			,				lowerCAmelCase  :			List[Any]=True			,				lowerCAmelCase  :			List[str]=True			,				lowerCAmelCase  :			List[Any]="T5Tokenizer"			,				lowerCAmelCase  :			str=True			,				lowerCAmelCase  :			Optional[int]=0			,				lowerCAmelCase  :			Tuple=1			,				lowerCAmelCase  :			Any=0			,				**lowerCAmelCase  :			int			,				)	->				str:




         """simple docstring"""

         super().__init__(
             is_encoder_decoder=lowerCAmelCase			,				tokenizer_class=lowerCAmelCase			,				tie_word_embeddings=lowerCAmelCase			,				pad_token_id=lowerCAmelCase			,				eos_token_id=lowerCAmelCase			,				decoder_start_token_id=lowerCAmelCase			,				**lowerCAmelCase			,				)
         lowercase__     =  vocab_size
         lowercase__     =  d_model
         lowercase__     =  d_kv
         lowercase__     =  d_ff
         lowercase__     =  num_layers
         lowercase__     =  (
             num_decoder_layers if num_decoder_layers is not None else self.num_layers
         )  # default = symmetry
         lowercase__     =  num_heads
         lowercase__     =  relative_attention_num_buckets
         lowercase__     =  relative_attention_max_distance
         lowercase__     =  dropout_rate
         lowercase__     =  layer_norm_epsilon
         lowercase__     =  initializer_factor
         lowercase__     =  feed_forward_proj
         lowercase__     =  use_cache

         lowercase__     =  self.feed_forward_proj.split('-')
         lowercase__     =  act_info[-1]
         lowercase__     =  act_info[0] == 'gated'

         if len(lowerCAmelCase) > 1 and act_info[0] != "gated" or len(lowerCAmelCase) > 2:
               raise ValueError(
                   f'''`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer.'''
                   'Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. '
                   '\'gated-gelu\' or \'relu\'')

         if feed_forward_proj == "gated-gelu":
               lowercase__     =  'gelu_new'


   @property
   def 			UpperCAmelCase		(						self  :			Union[str, Any])	->				Dict:




         """simple docstring"""

         return self.d_model


   @property
   def 			UpperCAmelCase		(						self  :			List[str])	->				Union[str, Any]:




         """simple docstring"""

         return self.num_heads



   @property
   def 			UpperCAmelCase		(						self  :			Optional[int])	->				Optional[Any]:




         """simple docstring"""

         return self.num_layers



class       UpperCAmelCase__(							lowerCamelCase	):

   '''simple docstring'''




   @property
   # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
   def 			UpperCAmelCase		(						self  :			Optional[int])	->				Mapping[str, Mapping[int, str]]:




         """simple docstring"""

         lowercase__     =  {
             'input_ids': {0: 'batch', 1: 'encoder_sequence'},
             'attention_mask': {0: 'batch', 1: 'encoder_sequence'},
         }
         if self.use_past:
               lowercase__     =  'past_encoder_sequence + sequence'
               lowercase__     =  {0: 'batch'}
               lowercase__     =  {0: 'batch', 1: 'past_decoder_sequence + sequence'}
         else:
               lowercase__     =  {0: 'batch', 1: 'decoder_sequence'}
               lowercase__     =  {0: 'batch', 1: 'decoder_sequence'}

         if self.use_past:
               self.fill_with_past_key_values_(lowerCAmelCase			,				direction='inputs')

         return common_inputs


   @property
   # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
   def 			UpperCAmelCase		(						self  :			int)	->				int:




         """simple docstring"""

         return 13



   @property
   def 			UpperCAmelCase		(						self  :			Optional[Any])	->				float:




         """simple docstring"""

         return 5E-4
