code: def __init__(
      self,
      prediction_interval_length: float,
      num_parallel_samples: int = 100,
      *args,
      **kwargs,
  ) -> None:
      super().__init__(*args, **kwargs)
      self.num_parallel_samples = num_parallel_samples
      self.prediction_interval_length = prediction_interval_length
  
file_path: gluonts/src/gluonts/mx/model/tpp/deeptpp/_network.py
imports: from typing import List, Optional, Tuple
  import mxnet
  import numpy
  from mxnet import nd
  from gluonts.core.component import validated
  from gluonts.mx.model.tpp import distribution
  from gluonts.mx.model.tpp.distribution.base import TPPDistributionOutput
  from gluonts.mx import Tensor
  from gluonts.mx.distribution import CategoricalOutput
label_desc: Use image node_id 1 to create a new DeepTPPPredictionNetwork object from inherited base classes: DeepTPPNetworkBase with example: obj = DeepTPPPredictionNetwork(prediction_interval_length, num_parallel_samples)