code: def _build_network(x, weights, biases):
      # Add customized layers
      _tf = _lazy_import_tensorflow()
      for i in range(len(weights.keys())):
          weight_name = "sound_dense{}_weight".format(i)
          bias_name = "sound_dense{}_bias".format(i)
          if i == 0:
              curr_dense = _tf.nn.xw_plus_b(
                  x,
                  weights=weights[weight_name],
                  biases=biases[bias_name],
              )
          else:
              curr_dense = _tf.nn.xw_plus_b(
                  curr_dense,
                  weights=weights[weight_name],
                  biases=biases[bias_name],
              )
          if i == (len(weights.keys()) - 1):
              out = _tf.nn.softmax(curr_dense)
          else:
              curr_dense = _tf.nn.relu(curr_dense)
  
      return out, curr_dense
  
file_path: turicreate/src/python/turicreate/toolkits/sound_classifier/_tf_sound_classifier.py
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  from .._tf_model import TensorFlowModel
  import turicreate.toolkits._tf_utils
  from turicreate._deps.minimal_package import _minimal_package_import_check
label_desc: Use image node_id 3 for calling the SoundClassifierTensorFlowModel obj's underlying member method code with example usage: obj._build_network(x, weights, biases) and returns: out,  curr_dense