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pcdet/models/detectors/voxel_rcnn.py

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+from .detector3d_template import Detector3DTemplate
+
+
+class VoxelRCNN(Detector3DTemplate):
+    def __init__(self, model_cfg, num_class, dataset):
+        super().__init__(model_cfg=model_cfg, num_class=num_class, dataset=dataset)
+        self.module_list = self.build_networks()
+
+    def forward(self, batch_dict):
+        for cur_module in self.module_list:
+            batch_dict = cur_module(batch_dict)
+
+        if self.training:
+            loss, tb_dict, disp_dict = self.get_training_loss()
+
+            ret_dict = {
+                'loss': loss
+            }
+            return ret_dict, tb_dict, disp_dict
+        else:
+            pred_dicts, recall_dicts = self.post_processing(batch_dict)
+            return pred_dicts, recall_dicts
+
+    def get_training_loss(self):
+        disp_dict = {}
+        loss = 0
+        
+        loss_rpn, tb_dict = self.dense_head.get_loss()
+        loss_rcnn, tb_dict = self.roi_head.get_loss(tb_dict)
+
+        loss = loss + loss_rpn + loss_rcnn
+        
+        if hasattr(self.backbone_3d, 'get_loss'):
+            loss_backbone3d, tb_dict = self.backbone_3d.get_loss(tb_dict)
+            loss += loss_backbone3d
+            
+        return loss, tb_dict, disp_dict