code: def __init__(
      self, num_parallel_samples: int, *args, **kwargs
  ) -> None:
      super().__init__(*args, **kwargs)
      self.num_parallel_samples = num_parallel_samples
  
imports: from typing import List, Optional
  import mxnet
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.block.feature import FeatureEmbedder
  from gluonts.mx.block.scaler import MeanScaler, NOPScaler
  from gluonts.mx.distribution.lds import LDS, LDSArgsProj, ParameterBounds
  from gluonts.mx.util import make_nd_diag, weighted_average
  from .issm import ISSM
label_desc: Use image node_id 1 to create a new DeepStatePredictionNetwork object from inherited base classes: DeepStateNetwork with example: obj = DeepStatePredictionNetwork(num_parallel_samples)