code: def __init__(
      self,
      global_model: HybridBlock,
      local_model: HybridBlock,
      embedder: FeatureEmbedder,
      **kwargs,
  ) -> None:
      super().__init__(**kwargs)
  
      self.global_model = global_model
      self.local_model = local_model
      self.embedder = embedder
      with self.name_scope():
          self.loading = nn.Dense(
              units=global_model.num_output, use_bias=False
          )
  
file_path: gluonts/src/gluonts/mx/model/deep_factor/_network.py
imports: from typing import Tuple
  import math
  from mxnet.gluon import HybridBlock, nn
  from gluonts.core.component import validated
  from gluonts.mx import Tensor
  from gluonts.mx.block.feature import FeatureEmbedder
label_desc: Use image node_id 1 to create a new DeepFactorNetworkBase object from inherited base classes: HybridBlock with example: obj = DeepFactorNetworkBase(global_model, local_model, embedder)