docstr: Wrapper of converter parameters
  
  Exporter set this parameters to the target converter's argument.
  
  >>> def own_converter(params):
  ...     # params is FunctionConverterParams
  ...     # so enable to get each attributes:
  ...     func_name = params.func.__class__.__name__
  
  Arguments:
      func (~chainer.FunctionNode): Target function.
      opset_version (int): Target opset version.
      input_names (list): List of input names.
      output_names (list): List of ouptut names.
      context (~onnx_chainer.context.Context): Context for Exporting
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code: def __init__(
      self,
      func=None,
      opset_version=None,
      input_names=None,
      output_names=None,
      context=None,
  ):
      """Wrapper of converter parameters
  
      Exporter set this parameters to the target converter's argument.
  
      >>> def own_converter(params):
      ...     # params is FunctionConverterParams
      ...     # so enable to get each attributes:
      ...     func_name = params.func.__class__.__name__
  
      Arguments:
          func (~chainer.FunctionNode): Target function.
          opset_version (int): Target opset version.
          input_names (list): List of input names.
          output_names (list): List of ouptut names.
          context (~onnx_chainer.context.Context): Context for Exporting
      """
  
      self.func = func
      self.opset_version = opset_version
      self.input_names = input_names
      self.output_names = output_names
      self.context = context
  
label_desc: Use image node_id 1 to create a new FunctionConverterParams object from inherited base classes: object with example: obj = FunctionConverterParams(func, opset_version, input_names, output_names, context)