Stabilize prelu gradient check

python/paddle/v2/framework/tests/test_prelu_op.py

@@ -7,6 +7,14 @@ class PReluTest(OpTest):
     def setUp(self):
         self.op_type = "prelu"
         x_np = np.random.normal(size=(10, 10)).astype("float32")
+
+        for pos, val in np.ndenumerate(x_np):
+            # Since zero point in prelu is not differentiable, avoid randomize
+            # zero.
+            while abs(val) < 1e-3:
+                x_np[pos] = np.random.normal()
+                val = x_np[pos]
+
         x_np_sign = np.sign(x_np)
         x_np = x_np_sign * np.maximum(x_np, .005)
         alpha_np = np.array([.1])