snapshot..

modules/deeplearning/espcn.py

@@ -613,18 +613,18 @@ class ESPCN:
 
         print('loss, acc: ', self.test_loss.result().numpy(), self.test_accuracy.result().numpy())
 
-        labels = np.concatenate(self.test_labels)
-        self.test_labels = labels
-
-        preds = np.concatenate(self.test_preds)
-        self.test_probs = preds
-
-        if NumClasses == 2:
-            preds = np.where(preds > 0.5, 1, 0)
-        else:
-            preds = np.argmax(preds, axis=1)
-
-        self.test_preds = preds
+        # labels = np.concatenate(self.test_labels)
+        # self.test_labels = labels
+        #
+        # preds = np.concatenate(self.test_preds)
+        # self.test_probs = preds
+        #
+        # if NumClasses == 2:
+        #     preds = np.where(preds > 0.5, 1, 0)
+        # else:
+        #     preds = np.argmax(preds, axis=1)
+        #
+        # self.test_preds = preds
 
     def do_evaluate(self, nda_lr, param, ckpt_dir):
 
@@ -659,6 +659,7 @@ class ESPCN:
         self.do_training()
 
     def run_restore(self, filename, ckpt_dir):
+        self.num_data_samples = 1000
         self.setup_test_pipeline(filename)
         self.build_model()
         self.build_training()