implemented inference

Deep-SAD-PyTorch/src/DeepSAD.py

@@ -86,6 +86,18 @@ class DeepSAD(object):
         self.results["train_time"] = self.trainer.train_time
         self.c = self.trainer.c.cpu().data.numpy().tolist()  # get as list
 
+    def inference(
+        self, dataset: BaseADDataset, device: str = "cuda", n_jobs_dataloader: int = 0
+    ):
+        """Tests the Deep SAD model on the test data."""
+
+        if self.trainer is None:
+            self.trainer = DeepSADTrainer(
+                self.c, self.eta, device=device, n_jobs_dataloader=n_jobs_dataloader
+            )
+
+        return self.trainer.infer(dataset, self.net)
+
     def test(
         self, dataset: BaseADDataset, device: str = "cuda", n_jobs_dataloader: int = 0
     ):