[MXNET-173]fix acc metric shape miss match (apache#10446)

* fix acc metric shape miss match

* add unit test

* fix style

* fix python2 division

python/mxnet/metric.py

@@ -417,11 +417,14 @@ def update(self, labels, preds):
                 pred_label = ndarray.argmax(pred_label, axis=self.axis)
             pred_label = pred_label.asnumpy().astype('int32')
             label = label.asnumpy().astype('int32')
+            # flatten before checking shapes to avoid shape miss match
+            label = label.flat
+            pred_label = pred_label.flat
 
             labels, preds = check_label_shapes(label, pred_label)
 
-            self.sum_metric += (pred_label.flat == label.flat).sum()
-            self.num_inst += len(pred_label.flat)
+            self.sum_metric += (pred_label == label).sum()
+            self.num_inst += len(pred_label)
 
 
 @register

tests/python/unittest/test_metric.py

@@ -54,6 +54,17 @@ def test_acc():
     expected_acc = (np.argmax(pred, axis=1) == label).sum().asscalar() / label.size
     assert acc == expected_acc
 
+def test_acc_2d_label():
+    # label maybe provided in 2d arrays in custom data iterator
+    pred = mx.nd.array([[0.3, 0.7], [0, 1.], [0.4, 0.6], [0.8, 0.2], [0.3, 0.5], [0.6, 0.4]])
+    label = mx.nd.array([[0, 1, 1], [1, 0, 1]])
+    metric = mx.metric.create('acc')
+    metric.update([label], [pred])
+    _, acc = metric.get()
+    expected_acc = (np.argmax(pred, axis=1).asnumpy() == label.asnumpy().ravel()).sum() / \
+                   float(label.asnumpy().ravel().size)
+    assert acc == expected_acc
+
 def test_f1():
     microF1 = mx.metric.create("f1", average="micro")
     macroF1 = mx.metric.F1(average="macro")