docstr: Parameters
  ----------
  *args
      Variable length argument list.
  **kwargs
      Arbitrary keyword arguments.
docstr_tok: ["Parameters","--","--","--","--","--","*","args","Variable","length","argument","list",".","*","*","kwargs","Arbitrary","keyword","arguments","."]
code: def __init__(self, *args, **kwargs) -> None:
      """
      Parameters
      ----------
      *args
          Variable length argument list.
      **kwargs
          Arbitrary keyword arguments.
      """
      super().__init__(*args, **kwargs)
  
file_path: gluonts/src/gluonts/mx/model/gp_forecaster/_network.py
imports: from typing import Tuple, Type
  import mxnet
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.distribution.distribution import softplus
  from gluonts.mx.kernels import KernelOutputDict
  from .gaussian_process import GaussianProcess
label_desc: Use image node_id 1 to create a new GaussianProcessTrainingNetwork object from inherited base classes: GaussianProcessNetworkBase with example: obj = GaussianProcessTrainingNetwork()