
'''simple docstring'''






import math
import sys







def 		A_							(						_lowerCAmelCase :     str				):



      """simple docstring"""




      _lowerCamelCase					: Dict		    = ""
      try:
            with open(_lowerCAmelCase					,						"rb"				) as binary_file:
                  _lowerCamelCase					: List[Any]		    = 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 		A_							(						_lowerCAmelCase :     str				):



      """simple docstring"""




      _lowerCamelCase					: Optional[int]		    = {"0": "0", "1": "1"}
      _lowerCamelCase    ,		_lowerCamelCase					: List[str]		    = "", ""
      _lowerCamelCase					: List[Any]		    = len(_lowerCAmelCase				)

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

            _lowerCamelCase					: Optional[Any]		    = lexicon[curr_string]
            result += last_match_id
            _lowerCamelCase					: List[str]		    = last_match_id + "0"

            if math.loga(_lowerCAmelCase				).is_integer():
                  _lowerCamelCase					: Dict		    = {}
                  for curr_key in list(_lowerCAmelCase				):
                        _lowerCamelCase					: Union[str, Any]		    = lexicon.pop(_lowerCAmelCase				)
                  _lowerCamelCase					: List[str]		    = new_lex

            _lowerCamelCase					: Union[str, Any]		    = last_match_id + "1"
            index += 1
            _lowerCamelCase					: Union[str, Any]		    = ""
      return result







def 		A_							(						_lowerCAmelCase :     str					,						_lowerCAmelCase :     str				):



      """simple docstring"""




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

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







def 		A_							(						_lowerCAmelCase :     str				):



      """simple docstring"""




      _lowerCamelCase					: Optional[Any]		    = 0
      for letter in data_bits:
            if letter == "1":
                  break
            counter += 1

      _lowerCamelCase					: Tuple		    = data_bits[counter:]
      _lowerCamelCase					: int		    = data_bits[counter + 1 :]
      return data_bits







def 		A_							(						_lowerCAmelCase :     str					,						_lowerCAmelCase :     str				):



      """simple docstring"""




      _lowerCamelCase					: Dict		    = read_file_binary(_lowerCAmelCase				)
      _lowerCamelCase					: List[str]		    = remove_prefix(_lowerCAmelCase				)
      _lowerCamelCase					: List[Any]		    = decompress_data(_lowerCAmelCase				)
      write_file_binary(_lowerCAmelCase					,						_lowerCAmelCase				)


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







import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


if TYPE_CHECKING:
 from ... import PreTrainedTokenizerBase, TensorType

snake_case__   :						List[str]													=   logging.get_logger(__name__)


class     _a							(	UpperCAmelCase__     ):






  """simple docstring"""





  A_						       = """vision-encoder-decoder"""
  A_						       = True




  def __init__(  self		,		**_UpperCAmelCase			)      ->			Dict:
     super().__init__(**_UpperCAmelCase			)
     if "encoder" not in kwargs or "decoder" not in kwargs:
        raise ValueError(
            f"""A configuraton of type {self.model_type} cannot be instantiated because """
            f"""not both `encoder` and `decoder` sub-configurations are passed, but only {kwargs}"""			)

     UpperCamelCase_						=  kwargs.pop('encoder'			)
     UpperCamelCase_						=  encoder_config.pop('model_type'			)
     UpperCamelCase_						=  kwargs.pop('decoder'			)
     UpperCamelCase_						=  decoder_config.pop('model_type'			)

     UpperCamelCase_						=  AutoConfig.for_model(_UpperCAmelCase		,		**_UpperCAmelCase			)
     UpperCamelCase_						=  AutoConfig.for_model(_UpperCAmelCase		,		**_UpperCAmelCase			)
     UpperCamelCase_						=  True




  @classmethod
  def  _UpperCAmelCase  (  cls		,		_UpperCAmelCase		,		_UpperCAmelCase		,		**_UpperCAmelCase			)      ->			PretrainedConfig:
     logger.info('Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'			)
     UpperCamelCase_						=  True
     UpperCamelCase_						=  True

     return cls(encoder=encoder_config.to_dict()		,		decoder=decoder_config.to_dict()		,		**_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self			)      ->			int:
     UpperCamelCase_						=  copy.deepcopy(self.__dict__			)
     UpperCamelCase_						=  self.encoder.to_dict()
     UpperCamelCase_						=  self.decoder.to_dict()
     UpperCamelCase_						=  self.__class__.model_type
     return output




class     _a							(	UpperCAmelCase__     ):






  """simple docstring"""





  A_						       = version.parse("""1.11"""     )




  @property
  def  _UpperCAmelCase  (  self			)      ->			Mapping[str, Mapping[int, str]]:
     return OrderedDict(
         [
             ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
         ]			)




  @property
  def  _UpperCAmelCase  (  self			)      ->			float:
     return 1e-4




  @property
  def  _UpperCAmelCase  (  self			)      ->			Mapping[str, Mapping[int, str]]:
     return OrderedDict({'last_hidden_state': {0: 'batch', 1: 'encoder_sequence'}}			)




class     _a							(	UpperCAmelCase__     ):






  """simple docstring"""





  @property
  def  _UpperCAmelCase  (  self			)      ->			Mapping[str, Mapping[int, str]]:
     UpperCamelCase_						=  OrderedDict()
     UpperCamelCase_						=  {0: 'batch', 1: 'past_decoder_sequence + sequence'}
     UpperCamelCase_						=  {0: 'batch', 1: 'past_decoder_sequence + sequence'}
     UpperCamelCase_						=  {0: 'batch', 1: 'encoder_sequence'}

     return common_inputs




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase = -1		,		_UpperCAmelCase = -1		,		_UpperCAmelCase = False		,		_UpperCAmelCase = None		,		)      ->			Mapping[str, Any]:
     import torch

     UpperCamelCase_						=  OrderedDict()

     UpperCamelCase_						=  super().generate_dummy_inputs(
         _UpperCAmelCase		,		batch_size=_UpperCAmelCase		,		seq_length=_UpperCAmelCase		,		is_pair=_UpperCAmelCase		,		framework=_UpperCAmelCase			)

     UpperCamelCase_		,   UpperCamelCase_						=  dummy_input['input_ids'].shape
     UpperCamelCase_						=  (batch, encoder_sequence, self._config.encoder_hidden_size)
     UpperCamelCase_						=  dummy_input.pop('input_ids'			)
     UpperCamelCase_						=  dummy_input.pop('attention_mask'			)
     UpperCamelCase_						=  torch.zeros(_UpperCAmelCase			)

     return common_inputs




class     _a							(	UpperCAmelCase__     ):






  """simple docstring"""





  @property
  def  _UpperCAmelCase  (  self			)      ->			None:
     pass




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase			)      ->			OnnxConfig:
     return VisionEncoderDecoderEncoderOnnxConfig(_UpperCAmelCase			)




  def  _UpperCAmelCase  (  self		,		_UpperCAmelCase		,		_UpperCAmelCase		,		_UpperCAmelCase = "default"			)      ->			OnnxConfig:
     UpperCamelCase_						=  encoder_config.hidden_size
     return VisionEncoderDecoderDecoderOnnxConfig(_UpperCAmelCase		,		_UpperCAmelCase			)





