remove redundant inference

Author: beautyremain

training/detectors/efficientnetb4_detector.py

@@ -58,8 +58,6 @@ def __init__(self, config):
         self.config = config
         self.backbone = self.build_backbone(config)
         self.loss_func = self.build_loss(config)
-        self.prob, self.label = [], []
-        self.correct, self.total = 0, 0
 
     def build_backbone(self, config):
         # prepare the backbone
@@ -111,26 +109,6 @@ def forward(self, data_dict: dict, inference=False) -> dict:
         prob = torch.softmax(pred, dim=1)[:, 1]
         # build the prediction dict for each output
         pred_dict = {'cls': pred, 'prob': prob, 'feat': features}
-        if inference:
-            self.prob.append(
-                pred_dict['prob']
-                .detach()
-                .squeeze()
-                .cpu()
-                .numpy()
-            )
-            self.label.append(
-                data_dict['label']
-                .detach()
-                .squeeze()
-                .cpu()
-                .numpy()
-            )
-            # deal with acc
-            _, prediction_class = torch.max(pred, 1)
-            correct = (prediction_class == data_dict['label']).sum().item()
-            self.correct += correct
-            self.total += data_dict['label'].size(0)
 
         return pred_dict