a patch for fixing random seeds in gradient checkers

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

 import unittest
 import numpy as np
+import random
 import itertools
 import paddle.v2.framework.core as core
 from paddle.v2.framework.op import Operator
@@ -192,6 +193,21 @@ def get_gradient(scope, op, inputs, outputs, grad_name, place,
 
 
 class OpTest(unittest.TestCase):
+    @classmethod
+    def setUpClass(cls):
+        '''Fix random seeds to remove randomness from tests'''
+        cls._np_rand_state = np.random.get_state()
+        cls._py_rand_state = random.getstate()
+
+        np.random.seed(123)
+        random.seed(124)
+
+    @classmethod
+    def tearDownClass(cls):
+        '''Restore random seeds'''
+        np.random.set_state(cls._np_rand_state)
+        random.setstate(cls._py_rand_state)
+
     def check_output_with_place(self, place, atol):
         self.scope = core.Scope()
         op_inputs = self.inputs if hasattr(self, "inputs") else dict()

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

@@ -43,7 +43,7 @@ class TestSoftmaxWithCrossEntropyOp2(OpTest):
     def setUp(self):
         self.op_type = "softmax_with_cross_entropy"
         batch_size = 2
-        class_num = 17
+        class_num = 37
 
         logits = np.random.uniform(0.1, 1.0,
                                    [batch_size, class_num]).astype("float32")