code: 
  '''simple docstring'''
  
  import os
  
  from apache_beam.io.filesystems import FileSystems
  from apache_beam.pipeline import Pipeline
  
  from .logging import get_logger
  
  
  _UpperCAmelCase   :      List[Any] 						=  2 << 20  # 2mb
  _UpperCAmelCase   :      Tuple 						=  get_logger(__name__)
  
  class 			UpperCAmelCase				(					a_ ):
  
  
  
  
  
  		"""simple docstring"""
  
  
  
  
  
  		def _lowercase  (    self     )				->    Any:
  				_UpperCamelCase       : List[str]    =      self._options.get_all_options().get('''runner'''     )
  				return runner in [None, "DirectRunner", "PortableRunner"]
  
  
  
  
  
  
  
  def 						snake_case__	(      UpperCamelCase			,UpperCamelCase			,UpperCamelCase=False	) ->      Optional[Any]:
  		_UpperCamelCase       : Any    =      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:
  						_UpperCamelCase       : Any    =      local_file.read(UpperCamelCase	)
  						while chunk:
  								remote_file.write(UpperCamelCase	)
  								_UpperCamelCase       : Dict    =      local_file.read(UpperCamelCase	)
  
  
  
  
  
  
  
  def 						snake_case__	(      UpperCamelCase			,UpperCamelCase			,UpperCamelCase=False	) ->      Union[str, Any]:
  		_UpperCamelCase       : str    =      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:
  						_UpperCamelCase       : Any    =      remote_file.read(UpperCamelCase	)
  						while chunk:
  								local_file.write(UpperCamelCase	)
  								_UpperCamelCase       : Optional[Any]    =      remote_file.read(UpperCamelCase	)
  
  
  
  
  
  
style_context: 
  '''simple docstring'''
  
  from typing import TYPE_CHECKING
  
  from ...utils import (
      OptionalDependencyNotAvailable,
      _LazyModule,
      is_flax_available,
      is_tf_available,
      is_torch_available,
  )
  
  
  _UpperCAmelCase   :      int 						=  {
      """configuration_gptsan_japanese""": ["""GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTSanJapaneseConfig"""],
      """tokenization_gptsan_japanese""": ["""GPTSanJapaneseTokenizer"""],
  }
  
  try:
  	if not is_torch_available():
  		raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
  	pass
  else:
  	_UpperCAmelCase   :      int 						=  [
  	    """GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST""",
  	    """GPTSanJapaneseForConditionalGeneration""",
  	    """GPTSanJapaneseModel""",
  	    """GPTSanJapanesePreTrainedModel""",
  	]
  	_UpperCAmelCase   :      str 						=  [
  	    """GPTSanJapaneseTokenizer""",
  	]
  
  
  if TYPE_CHECKING:
  	from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
  	from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer
  
  	try:
  		if not is_torch_available():
  			raise OptionalDependencyNotAvailable()
  	except OptionalDependencyNotAvailable:
  		pass
  	else:
  		from .modeling_gptsan_japanese import (
  		    GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
  		    GPTSanJapaneseForConditionalGeneration,
  		    GPTSanJapaneseModel,
  		    GPTSanJapanesePreTrainedModel,
  		)
  		from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer
  
  
  else:
  	import sys
  
  	_UpperCAmelCase   :      List[str] 						=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
  
  
  
  