class_docstr: EfficientDet keras network with train and test step.
docstr: Return regularization l2 loss loss.
docstr_tok: ["Return","regularization","l2","loss","loss","."]
code: def _reg_l2_loss(self, weight_decay, regex=r".*(kernel|weight):0$"):
      """Return regularization l2 loss loss."""
      var_match = re.compile(regex)
      return weight_decay * tf.add_n(
          [
              tf.nn.l2_loss(v)
              for v in self.trainable_variables
              if var_match.match(v.name)
          ]
      )
  
imports: import functools
  from absl import logging
  import tensorflow
  import hparams_config
  import utils
  from .backbone import efficientnet_builder
  from .utils import postprocess
  from .utils import layers
  from .utils import losses
  import re
label_desc: Use image node_id 3 for calling the EfficientDetNet obj's underlying member method code with example usage: obj._reg_l2_loss(weight_decay, regex) and returns: unknown