implement test() for classifing target data.

moayadeldin · Aug 21, 2017 · 34e487d · 34e487d
1 parent 332e662
commit 34e487d
Showing 1 changed file with 26 additions and 1 deletion.
diff --git a/core/test.py b/core/test.py
@@ -1,6 +1,31 @@
 """Test script to classify target data."""
 
+import torch
+import torch.nn as nn
+
+from utils import make_variable
+
 
 def eval_tgt(model_src, model_tgt, data_loader):
     """Evaluation for target encoder by source classifier on target dataset."""
-    pass
+    print("=== Evaluating classifier for encoded target domain ===")
+    model_src.eval()
+    model_tgt.eval()
+    loss = 0
+    acc = 0
+    criterion = nn.NLLLoss()
+
+    for (images, labels) in data_loader:
+        images = make_variable(images, volatile=True)
+        labels = make_variable(labels).squeeze_()
+
+        _, preds = model_tgt(images)
+        loss += criterion(preds, labels).data[0]
+
+        pred_cls = preds.data.max(1)[1]
+        acc += pred_cls.eq(labels.data).cpu().sum()
+
+    loss /= len(data_loader)
+    acc /= len(data_loader.dataset)
+
+    print("Avg Loss = {}, Avg Accuracy = {:2%}".format(loss, acc))