code: def _get_multidepth_cnn_eg12_common():
      """A network with 2 softmax layers mostly for debugging common operations."""
      cnn_layer_labels = get_cnn_layer_labels()
      layer_labels = [
          "ip",
          "op",
          "softmax",
          "fc",
          "softmax",
          "fc",
          "conv5",
          "avg-pool",
          "max-pool",
          "conv3",
          "conv3",
          "max-pool",
          "max-pool",
          "conv3",
          "conv7",
      ]
      num_filters_each_layer = [
          None,
          None,
          None,
          64,
          None,
          64,
          128,
          None,
          None,
          64,
          64,
          None,
          None,
          128,
          64,
      ]
      edges = [
          (0, 14),
          (14, 6),
          (14, 9),
          (14, 10),
          (6, 7),
          (7, 3),
          (3, 2),
          (2, 1),
          (9, 8),
          (8, 5),
          (5, 4),
          (4, 1),
          (10, 11),
          (11, 13),
          (13, 12),
          (12, 5),
      ]
      strides = [
          (1 if is_a_conv_layer_label(ll) else None)
          for ll in layer_labels
      ]
      return (
          layer_labels,
          edges,
          num_filters_each_layer,
          cnn_layer_labels,
          strides,
      )
  
imports: import numpy
  from scipy.sparse import dok_matrix
  from .neural_network import ConvNeuralNetwork, MultiLayerPerceptron, get_cnn_layer_labels, get_mlp_layer_labels, is_a_conv_layer_label
  from .nn_modifiers import NNModifier
  from ..utils.general_utils import get_dok_mat_with_set_coords
label_desc: Use image node_id 3 for calling a global function with example usage: _get_multidepth_cnn_eg12_common() and returns: layer_labels,  edges,  num_filters_each_layer,  cnn_layer_labels,  strides