class_docstr: main model 
class_docstr_tok: ["main","model"]
docstr: output layers
docstr_tok: ["output","layers"]
code: def logits_layer(self, x):
      """output layers"""
      with tf.variable_scope("logits"):
          logits = common_layers.linear(
              x,
              "logits-matmul",
              [
                  self.netconf["hidden1"],
                  self.taskconf["classes"]["num"],
              ],
          )
      return logits
  
imports: from absl import logging
  import delta.compat
  from delta import utils
  from delta.layers import common_layers
  from delta.data.feat.tf_speech_feature import speech_params, extract_feature
  from delta.models.base_model import RawModel
  from delta.utils.register import registers
label_desc: Use image node_id 10 for calling the EmoCRNNRawModel obj's underlying member method code with example usage: obj.logits_layer(x) and returns: logits