class_docstr: Uses the features as the representation. This representation graph does no transformation to the features.
code: def connect_representation_graph(
      self, tf_features, n_components, n_features, node_name_ending
  ):
      if n_components != n_features:
          raise ValueError(
              "{} requires n_features and n_components to be equal. Either adjust n_components or use a "
              "different representation graph. n_features = {}, n_components = {}".format(
                  self.__class__.__name__, n_features, n_components
              )
          )
  
      return (
          tf.sparse_tensor_to_dense(
              tf_features, validate_indices=False
          ),
          [],
      )
  
imports: import abc
  import tensorflow
label_desc: Use image node_id 1 for calling the FeaturePassThroughRepresentationGraph obj's underlying member method code with example usage: obj.connect_representation_graph(tf_features, n_components, n_features, node_name_ending) and returns: tf,  list