docstr: Schemes are the pre-defined network architectures of various depths and complexities that can be used. Are used
  to create Block when InputEmbedder is initialised.
  
  Note: Tensor embedder doesn't define any pre-defined scheme. User must provide custom scheme in preset.
  
  :return: dictionary of schemes, with key of type EmbedderScheme enum and value being list of mxnet.gluon.Block.
      For tensor embedder, this is an empty dictionary.
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 InputEmbedder is initialised.
  
      Note: Tensor embedder doesn't define any pre-defined scheme. User must provide custom scheme in preset.
  
      :return: dictionary of schemes, with key of type EmbedderScheme enum and value being list of mxnet.gluon.Block.
          For tensor embedder, this is an empty dictionary.
      """
      return {}
  
file_path: coach/rl_coach/architectures/mxnet_components/embedders/tensor_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
label_desc: Use image node_id 2 for calling the TensorEmbedder obj's underlying member method code with example usage: obj.schemes() and returns: dict