docstr: Used for forward pass through embedder network.
  
  :param F: backend api, either `nd` or `sym` (if block has been hybridized).
  :type F: nd or sym
  :param x: vector representing environment state, of shape (batch_size, in_channels).
  :return: embedding of environment state, of shape (batch_size, channels).
docstr_tok: ["Used","for","forward","pass","through","embedder","network",".",":","param","F",":","backend","api",",","either","`","nd","`","or","`","sym","`","(","if","block","has","been","hybridized",")",".",":","type","F",":","nd","or","sym",":","param","x",":","vector","representing","environment","state",",","of","shape","(","batch_size",",","in_channels",")",".",":","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 `nd` or `sym` (if block has been hybridized).
      :type F: nd or sym
      :param x: vector representing environment state, of shape (batch_size, in_channels).
      :return: embedding of environment state, of shape (batch_size, channels).
      """
      if (
          isinstance(x, nd.NDArray)
          and len(x.shape) != 2
          and self.scheme != EmbedderScheme.Empty
      ):
          raise ValueError(
              "Vector embedders expect the input size to have 2 dimensions. The given size is: {}".format(
                  x.shape
              )
          )
      return super(VectorEmbedder, self).hybrid_forward(
          F, x, *args, **kwargs
      )
  
file_path: coach/rl_coach/architectures/mxnet_components/embedders/vector_embedder.py
imports: from typing import Union
  from types import ModuleType
  import mxnet
  from mxnet import nd, sym
  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 Dense
  from rl_coach.base_parameters import EmbedderScheme
label_desc: Use image node_id 3 for calling the VectorEmbedder obj's underlying member method code with example usage: obj.hybrid_forward(F, x) and returns: super