class_docstr: A speaker model with ResNet layers. 
class_docstr_tok: ["A","speaker","model","with","ResNet","layers","."]
docstr: resnet_block. 
docstr_tok: ["resnet_block","."]
code: def resnet(self, inputs):
      """resnet_block."""
      layers_list = self.netconf["layers_list"]
      logging.info("layers_list : {}".format(layers_list))
      filters_list = self.netconf["filters_list"]
      logging.info("filters_list : {}".format(filters_list))
      strides_list = self.netconf["strides_list"]
      logging.info("strides_list : {}".format(strides_list))
      block_mode = self.netconf["block_mode"]
      logging.info("block_mode : {}".format(block_mode))
  
      with tf.variable_scope("resnet"):
          x = tf.identity(inputs)
          with tf.variable_scope("input_layer"):
              x = common_layers.conv2d(
                  x,
                  "input_conv",
                  (3, 3),
                  self.input_channels,
                  filters_list[0],
                  [1, 1],
                  bias=False,
              )
              x = tf.layers.batch_normalization(
                  x,
                  axis=-1,
                  momentum=0.9,
                  training=self.train,
                  name="input_bn",
              )
              x = self.prelu_layer(x, "input_prelu")
  
          for index, layer_num in enumerate(layers_list):
              unit_name = "resblock-" + str(index + 1)
              with tf.variable_scope(unit_name):
                  x = self.resnet_block(
                      x,
                      block_mode,
                      layer_num,
                      filters_list[index],
                      filters_list[index + 1],
                      strides_list[index],
                  )
  
      return x
  
imports: import math
  from absl import logging
  import delta.compat
  import tensorflow.keras.layers
  from delta import utils
  from delta.layers import common_layers
  from delta.models.base_model import RawModel
  from delta.utils.register import registers
  from delta.utils.loss.loss_utils import arcface_loss
  from delta.utils.hparam import HParams
label_desc: Use image node_id 9 for calling the SpeakerResNetRawModel obj's underlying member method code with example usage: obj.resnet(inputs) and returns: x