class_docstr: Module mix-in for the parametric function classes.
      
docstr: Get parameters.
  Args:
      grad_only (bool, optional): Return parameters with `need_grad` option as `True`. 
      If you set this option as `False`, All parameters are returned. Default is `True`.
  Returns:
      dict: The dictionary of parameter name (`str`) to Variable (:obj:`~nnabla.Variable`).
code: def get_parameters(self, grad_only=True):
      """Get parameters.
      Args:
          grad_only (bool, optional): Return parameters with `need_grad` option as `True`.
          If you set this option as `False`, All parameters are returned. Default is `True`.
      Returns:
          dict: The dictionary of parameter name (`str`) to Variable (:obj:`~nnabla.Variable`).
      """
      params = OrderedDict()
  
      for v in self.get_modules():
          if not isinstance(v, tuple):
              continue
          prefix, module = v
          for k, v in module.__dict__.items():
              if not isinstance(v, nn.Variable):
                  continue
              pname = k
              name = "{}/{}".format(prefix, pname)
              if grad_only and v.need_grad == False:
                  continue
              params[name] = v
      return params
  
file_path: nnabla/python/src/nnabla/experimental/parametric_function_class/module.py
imports: from collections import OrderedDict
  import nnabla
label_desc: Use image node_id 2 for calling the Module obj's underlying member method code with example usage: obj.get_parameters(grad_only) and returns: params