class_docstr: SSD: Single Shot MultiBox Detector
      
class_docstr_tok: ["SSD",":","Single","Shot","MultiBox","Detector"]
docstr: Get trainable vars included in the module.
          
docstr_tok: ["Get","trainable","vars","included","in","the","module","."]
code: def get_trainable_vars(self):
      """Get trainable vars included in the module."""
      trainable_vars = snt.get_variables_in_module(self)
      if self._config.base_network.trainable:
          pretrained_trainable_vars = (
              self.feature_extractor.get_trainable_vars()
          )
          tf.logging.info(
              "Training {} vars from pretrained module.".format(
                  len(pretrained_trainable_vars)
              )
          )
          trainable_vars += pretrained_trainable_vars
      else:
          tf.logging.info(
              "Not training variables from pretrained module"
          )
  
      return trainable_vars
  
file_path: luminoth/luminoth/models/ssd/ssd.py
imports: import numpy
  import sonnet
  import tensorflow
  from sonnet.python.modules.conv import Conv2D
  from luminoth.models.ssd.feature_extractor import SSDFeatureExtractor
  from luminoth.models.ssd.proposal import SSDProposal
  from luminoth.models.ssd.target import SSDTarget
  from luminoth.models.ssd.utils import generate_raw_anchors, adjust_bboxes
  from luminoth.utils.losses import smooth_l1_loss
  from luminoth.utils.bbox_transform import clip_boxes
label_desc: Use image node_id 5 for calling the SSD obj's underlying member method code with example usage: obj.get_trainable_vars() and returns: trainable_vars