


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     )





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     )     )

