docstr: Builds the classifier sub-network.
docstr_tok: ["Builds","the","classifier","sub-network","."]
code: def __init__(self, cf, conv):
      """
      Builds the classifier sub-network.
      """
      super(Classifier, self).__init__()
      self.dim = conv.dim
      self.n_classes = cf.head_classes
      n_input_channels = cf.end_filts
      n_features = cf.n_rpn_features
      n_output_channels = cf.n_anchors_per_pos * cf.head_classes
      anchor_stride = cf.rpn_anchor_stride
  
      self.conv_1 = conv(
          n_input_channels,
          n_features,
          ks=3,
          stride=anchor_stride,
          pad=1,
          relu=cf.relu,
      )
      self.conv_2 = conv(
          n_features,
          n_features,
          ks=3,
          stride=anchor_stride,
          pad=1,
          relu=cf.relu,
      )
      self.conv_3 = conv(
          n_features,
          n_features,
          ks=3,
          stride=anchor_stride,
          pad=1,
          relu=cf.relu,
      )
      self.conv_4 = conv(
          n_features,
          n_features,
          ks=3,
          stride=anchor_stride,
          pad=1,
          relu=cf.relu,
      )
      self.conv_final = conv(
          n_features,
          n_output_channels,
          ks=3,
          stride=anchor_stride,
          pad=1,
          relu=None,
      )
  
imports: import utils.model_utils
  import utils.exp_utils
  import sys
  from cuda_functions.nms_2D.pth_nms import nms_gpu
  from cuda_functions.nms_3D.pth_nms import nms_gpu
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils
label_desc: Use image node_id 1 to create a new Classifier object from inherited base classes: nn with example: obj = Classifier(cf, conv)