docstr: Schemes are the pre-defined network architectures of various depths and complexities that can be used. Are used
  to create Block when ImageEmbedder is initialised.
  
  :return: dictionary of schemes, with key of type EmbedderScheme enum and value being list of mxnet.gluon.Block.
code: def schemes(self) -> dict:
      """
      Schemes are the pre-defined network architectures of various depths and complexities that can be used. Are used
      to create Block when ImageEmbedder is initialised.
  
      :return: dictionary of schemes, with key of type EmbedderScheme enum and value being list of mxnet.gluon.Block.
      """
      return {
          EmbedderScheme.Empty: [],
          EmbedderScheme.Shallow: [
              Conv2d(num_filters=32, kernel_size=8, strides=4)
          ],
          # Use for Atari DQN
          EmbedderScheme.Medium: [
              Conv2d(num_filters=32, kernel_size=8, strides=4),
              Conv2d(num_filters=64, kernel_size=4, strides=2),
              Conv2d(num_filters=64, kernel_size=3, strides=1),
          ],
          # Use for Carla
          EmbedderScheme.Deep: [
              Conv2d(num_filters=32, kernel_size=5, strides=2),
              Conv2d(num_filters=32, kernel_size=3, strides=1),
              Conv2d(num_filters=64, kernel_size=3, strides=2),
              Conv2d(num_filters=64, kernel_size=3, strides=1),
              Conv2d(num_filters=128, kernel_size=3, strides=2),
              Conv2d(num_filters=128, kernel_size=3, strides=1),
              Conv2d(num_filters=256, kernel_size=3, strides=2),
              Conv2d(num_filters=256, kernel_size=3, strides=1),
          ],
      }
  
file_path: coach/rl_coach/architectures/mxnet_components/embedders/image_embedder.py
imports: from typing import Union
  from types import ModuleType
  import mxnet
  from rl_coach.architectures.embedder_parameters import InputEmbedderParameters
  from rl_coach.architectures.mxnet_components.embedders.embedder import InputEmbedder
  from rl_coach.architectures.mxnet_components.layers import Conv2d
  from rl_coach.base_parameters import EmbedderScheme
label_desc: Use image node_id 2 for calling the ImageEmbedder obj's underlying member method code with example usage: obj.schemes() and returns: dict