docstr: Used for forward pass through embedder network.
  
  :param F: backend api, either `mxnet.nd` or `mxnet.sym` (if block has been hybridized).
  :param x: image representing environment state, of shape (batch_size, in_channels, height, width).
  :return: embedding of environment state, of shape (batch_size, channels).
code: def hybrid_forward(
      self, F: ModuleType, x: nd_sym_type, *args, **kwargs
  ) -> nd_sym_type:
      """
      Used for forward pass through embedder network.
  
      :param F: backend api, either `mxnet.nd` or `mxnet.sym` (if block has been hybridized).
      :param x: image representing environment state, of shape (batch_size, in_channels, height, width).
      :return: embedding of environment state, of shape (batch_size, channels).
      """
      return super(TensorEmbedder, self).hybrid_forward(
          F, x, *args, **kwargs
      )
  
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 3 for calling the TensorEmbedder obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: super