code: 
  
  
  import os
  
  from apache_beam.io.filesystems import FileSystems
  from apache_beam.pipeline import Pipeline
  
  from .logging import get_logger
  
  
  __a   				=      2 << 20  # 2mb
  __a   				=      get_logger(__name__)
  
  
  
  
  
  
  
  class 				__SCREAMING_SNAKE_CASE   (			A__   ):
  
  
        def        __lowerCamelCase			(							self		):
              lowercase			:   Optional[int]					   =		self._options.get_all_options().get('''runner'''		)
              return runner in [None, "DirectRunner", "PortableRunner"]
  
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase=False     )    ->List[str]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   str					   =		FileSystems
        if fs.exists(_UpperCamelCase     ):
              if force_upload:
                    logger.info(f"""Remote path already exist: {remote_file_path}. Overwriting it as force_upload=True."""     )
              else:
                    logger.info(f"""Remote path already exist: {remote_file_path}. Skipping it as force_upload=False."""     )
                    return
        with fs.create(_UpperCamelCase     ) as remote_file:
              with open(_UpperCamelCase,    '''rb'''     ) as local_file:
                    lowercase			:   Dict					   =		local_file.read(_UpperCamelCase     )
                    while chunk:
                          remote_file.write(_UpperCamelCase     )
                          lowercase			:   List[str]					   =		local_file.read(_UpperCamelCase     )
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase,    _UpperCamelCase=False     )    ->Optional[int]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   Union[str, Any]					   =		FileSystems
        if os.path.exists(_UpperCamelCase     ):
              if force_download:
                    logger.info(f"""Local path already exist: {remote_file_path}. Overwriting it as force_upload=True."""     )
              else:
                    logger.info(f"""Local path already exist: {remote_file_path}. Skipping it as force_upload=False."""     )
                    return
        with fs.open(_UpperCamelCase     ) as remote_file:
              with open(_UpperCamelCase,    '''wb'''     ) as local_file:
                    lowercase			:   Tuple					   =		remote_file.read(_UpperCamelCase     )
                    while chunk:
                          local_file.write(_UpperCamelCase     )
                          lowercase			:   Union[str, Any]					   =		remote_file.read(_UpperCamelCase     )
  
  
style_context: 
  
  
  import numpy as np
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase     )    ->Dict:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   Optional[Any]					   =		np.array(_UpperCamelCase     )
        lowercase			:   Dict					   =		np.array(_UpperCamelCase     )
  
        lowercase			:   List[Any]					   =		abs(predict - actual     )
        lowercase			:   int					   =		difference.mean()
  
        return score
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase     )    ->List[Any]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   Tuple					   =		np.array(_UpperCamelCase     )
        lowercase			:   str					   =		np.array(_UpperCamelCase     )
  
        lowercase			:   List[str]					   =		predict - actual
        lowercase			:   Tuple					   =		np.square(_UpperCamelCase     )
  
        lowercase			:   Union[str, Any]					   =		square_diff.mean()
        return score
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase     )    ->str:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   Union[str, Any]					   =		np.array(_UpperCamelCase     )
        lowercase			:   Optional[Any]					   =		np.array(_UpperCamelCase     )
  
        lowercase			:   Tuple					   =		predict - actual
        lowercase			:   Dict					   =		np.square(_UpperCamelCase     )
        lowercase			:   Union[str, Any]					   =		square_diff.mean()
        lowercase			:   Union[str, Any]					   =		np.sqrt(_UpperCamelCase     )
        return score
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase     )    ->List[Any]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   List[str]					   =		np.array(_UpperCamelCase     )
        lowercase			:   List[Any]					   =		np.array(_UpperCamelCase     )
  
        lowercase			:   Dict					   =		np.log(predict + 1     )
        lowercase			:   List[str]					   =		np.log(actual + 1     )
  
        lowercase			:   int					   =		log_predict - log_actual
        lowercase			:   Tuple					   =		np.square(_UpperCamelCase     )
        lowercase			:   List[Any]					   =		square_diff.mean()
  
        lowercase			:   int					   =		np.sqrt(_UpperCamelCase     )
  
        return score
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase     )    ->List[str]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        lowercase			:   List[Any]					   =		np.array(_UpperCamelCase     )
        lowercase			:   Optional[int]					   =		np.array(_UpperCamelCase     )
  
        lowercase			:   Optional[int]					   =		predict - actual
        lowercase			:   Optional[int]					   =		np.sum(_UpperCamelCase     ) / len(_UpperCamelCase     )
        lowercase			:   Dict					   =		np.sum(_UpperCamelCase     ) / len(_UpperCamelCase     )
        # print(numerator, denumerator)
        lowercase			:   int					   =		float(_UpperCamelCase     ) / denumerator * 100
  
        return score
  
  
  
  
  def 			__lowercase	(						_UpperCamelCase,    _UpperCamelCase     )    ->List[Any]:
  
  
  
  
  
  
  
        """simple docstring"""
  
        return np.mean(np.array(_UpperCamelCase     ) == np.array(_UpperCamelCase     )     )
  
  