wip inference

Deep-SAD-PyTorch/src/optim/DeepSAD_trainer.py

@@ -177,6 +177,8 @@ class DeepSADTrainer(BaseTrainer):
             batch_size=self.batch_size, num_workers=self.n_jobs_dataloader
         )
 
+        latent_dim = net.rep_dim
+
         # Set device for network
         net = net.to(self.device)
 
@@ -184,7 +186,9 @@ class DeepSADTrainer(BaseTrainer):
         logger.info("Starting inference...")
         n_batches = 0
         start_time = time.time()
-        all_outputs = np.zeros((len(inference_loader.dataset), 1024), dtype=np.float32)
+        all_outputs = np.zeros(
+            (len(inference_loader.dataset), latent_dim), dtype=np.float32
+        )
         scores = []
         net.eval()