From 6461e800a5404762e6105a4080625bee64b1c2b0 Mon Sep 17 00:00:00 2001
From: Krzysztof Binias <krzysztof.binias@intel.com>
Date: Thu, 22 Mar 2018 15:47:02 +0100
Subject: [PATCH] Inheritance added for MKLDNN tests

---
 .../tests/unittests/test_activation_op.py     | 50 ++++++-------------
 1 file changed, 16 insertions(+), 34 deletions(-)

diff --git a/python/paddle/fluid/tests/unittests/test_activation_op.py b/python/paddle/fluid/tests/unittests/test_activation_op.py
index 1d53737ac1..4a2b35322d 100644
--- a/python/paddle/fluid/tests/unittests/test_activation_op.py
+++ b/python/paddle/fluid/tests/unittests/test_activation_op.py
@@ -507,58 +507,46 @@ class TestSwish(OpTest):
 
 
 #--------------------test MKLDNN--------------------
-class TestMKLDNNRelu(OpTest):
+class TestMKLDNNRelu(TestRelu):
     def setUp(self):
-        self.op_type = "relu"
+        super(TestMKLDNNRelu, self).setUp()
+
         x = np.random.uniform(-1, 1, [2, 4, 3, 5]).astype("float32")
         # The same reason with TestAbs
         x[np.abs(x) < 0.005] = 0.02
-        self.inputs = {'X': x}
-        self.outputs = {'Out': np.maximum(self.inputs['X'], 0)}
-        self.attrs = {"use_mkldnn": True}
-
-    def test_check_output(self):
-        self.check_output()
+        out = np.maximum(x, 0)
 
-    def test_check_grad(self):
-        self.check_grad(['X'], 'Out', max_relative_error=0.007)
+        self.inputs = {'X': OpTest.np_dtype_to_fluid_dtype(x)}
+        self.outputs = {'Out': out}
+        self.attrs = {"use_mkldnn": True}
 
 
-class TestMKLDNNTanh(OpTest):
+class TestMKLDNNTanh(TestTanh):
     def setUp(self):
-        self.op_type = "tanh"
+        super(TestMKLDNNTanh, self).setUp()
+
         self.inputs = {
             'X': np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32")
         }
         self.outputs = {'Out': np.tanh(self.inputs['X'])}
         self.attrs = {"use_mkldnn": True}
 
-    def test_check_output(self):
-        self.check_output()
 
-    def test_check_grad(self):
-        self.check_grad(['X'], 'Out', max_relative_error=0.007)
-
-
-class TestMKLDNNSqrt(OpTest):
+class TestMKLDNNSqrt(TestSqrt):
     def setUp(self):
-        self.op_type = "sqrt"
+        super(TestMKLDNNSqrt, self).setUp()
+
         self.inputs = {
             'X': np.random.uniform(0.1, 1, [2, 4, 3, 5]).astype("float32")
         }
         self.outputs = {'Out': np.sqrt(self.inputs['X'])}
         self.attrs = {"use_mkldnn": True}
 
-    def test_check_output(self):
-        self.check_output()
-
-    def test_check_grad(self):
-        self.check_grad(['X'], 'Out', max_relative_error=0.007)
-
 
-class TestMKLDNNAbs(OpTest):
+class TestMKLDNNAbs(TestAbs):
     def setUp(self):
-        self.op_type = "abs"
+        super(TestMKLDNNAbs, self).setUp()
+
         x = np.random.uniform(-1, 1, [2, 4, 3, 5]).astype("float32")
         # The same reason with TestAbs
         x[np.abs(x) < 0.005] = 0.02
@@ -566,12 +554,6 @@ class TestMKLDNNAbs(OpTest):
         self.outputs = {'Out': np.abs(self.inputs['X'])}
         self.attrs = {"use_mkldnn": True}
 
-    def test_check_output(self):
-        self.check_output()
-
-    def test_check_grad(self):
-        self.check_grad(['X'], 'Out', max_relative_error=0.007)
-
 
 if __name__ == "__main__":
     unittest.main()
-- 
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