1 metric update should be in the for loop. 2 sample_num is the shape's first...

1 metric update should be in the for loop. 2 sample_num is the shape's first element 3 preds cast should use round, astype("int32") method will cast all the elements(which is less than 1) to 0.

python/paddle/fluid/metrics.py

@@ -227,7 +227,7 @@ class Precision(MetricBase):
                 metric.reset()
                 for data in train_reader():
                     loss, preds, labels = exe.run(fetch_list=[cost, preds, labels])
-                metric.update(preds=preds, labels=labels)
+                    metric.update(preds=preds, labels=labels)
                 numpy_precision = metric.eval()
     """
 
@@ -241,9 +241,10 @@ class Precision(MetricBase):
             raise ValueError("The 'preds' must be a numpy ndarray.")
         if not _is_numpy_(labels):
             raise ValueError("The 'labels' must be a numpy ndarray.")
-        sample_num = labels[0]
+        sample_num = labels.shape[0]
+        preds = np.rint(preds).astype("int32")
         for i in range(sample_num):
-            pred = preds[i].astype("int32")
+            pred = preds[i]
             label = labels[i]
             if label == 1:
                 if pred == label: