Fix test_conv2d_op.py.

python/paddle/v2/framework/tests/test_conv2d_op.py

 import unittest
 import numpy as np
-from gradient_checker import GradientChecker, create_op
-from op_test_util import OpTestMeta
-from paddle.v2.framework.op import Operator
+from op_test import OpTest
 
 
-class TestConv2dOp(unittest.TestCase):
-    __metaclass__ = OpTestMeta
-
+class TestConv2dOp(OpTest):
     def setUp(self):
-        self.type = "conv2d"
+        self.op_type = "conv2d"
         batch_size = 2
         input_channels = 3
         input_height = 5
@@ -58,8 +54,11 @@ class TestConv2dOp(unittest.TestCase):
         self.outputs = {'Output': output}
         self.attrs = {'strides': [1, 1], 'paddings': [0, 0]}
 
+    def test_check_output(self):
+        self.check_output()
+
 
-class TestConv2dGradOp(GradientChecker):
+class TestConv2dGradOp(OpTest):
     def setUp(self):
         batch_size = 2
         input_channels = 3
@@ -79,21 +78,18 @@ class TestConv2dGradOp(GradientChecker):
             (output_channels, input_channels, filter_height,
              filter_width)).astype("float32")
 
+        self.op_type = 'conv2d'
         self.inputs = {'Input': input, 'Filter': filter}
-        self.op = Operator(
-            "conv2d",
-            Input='Input',
-            Filter='Filter',
-            Output='Output',
-            strides=[1, 1],
-            paddings=[0, 0])
+        output = np.ndarray(
+            (batch_size, output_channels, output_height, output_width))
+        self.outputs = {'Output': output}
+        self.attrs = {'strides': [1, 1], 'paddings': [0, 0]}
 
-    def test_compare_grad(self):
-        self.compare_grad(self.op, self.inputs)
+    #def test_compare_grad(self):
+    #    self.compare_grad(self.op, self.inputs)
 
     def test_check_grad(self):
-        self.check_grad(self.op, self.inputs,
-                        set(['Input', 'Filter']), 'Output')
+        self.check_grad(set(['Input', 'Filter']), 'Output')
 
 
 if __name__ == '__main__':