diff --git a/paddle/operators/bipartite_match_op.cc b/paddle/operators/bipartite_match_op.cc
index b0f7376d272a66e0b01d6b3f7e546372397772f7..83c8778fe4cec4d9d80de691e117a39fdd92f494 100644
--- a/paddle/operators/bipartite_match_op.cc
+++ b/paddle/operators/bipartite_match_op.cc
@@ -21,8 +21,6 @@ namespace operators {
 using Tensor = framework::Tensor;
 using LoDTensor = framework::LoDTensor;
 
-constexpr char kEPS = 1e-6;
-
 class BipartiteMatchOp : public framework::OperatorWithKernel {
  public:
   using framework::OperatorWithKernel::OperatorWithKernel;
@@ -46,6 +44,7 @@ class BipartiteMatchKernel : public framework::OpKernel<T> {
   // The match_dist must be initialized to 0 at first.
   void BipartiteMatch(const Tensor& dist, int* match_indices,
                       T* match_dist) const {
+    constexpr T kEPS = static_cast<T>(1e-6);
     PADDLE_ENFORCE_EQ(dist.dims().size(), 2, "The rank of dist must be 2.");
     int64_t row = dist.dims()[0];
     int64_t col = dist.dims()[1];
diff --git a/python/paddle/v2/fluid/tests/test_bipartite_match_op.py b/python/paddle/v2/fluid/tests/test_bipartite_match_op.py
index 34101b1da46d46d0e7a995ba80d8644dc586065d..74138298978c7c18936f53761b313887f07aea81 100644
--- a/python/paddle/v2/fluid/tests/test_bipartite_match_op.py
+++ b/python/paddle/v2/fluid/tests/test_bipartite_match_op.py
@@ -16,13 +16,13 @@ import numpy as np
 from op_test import OpTest
 
 
-def bipartite_match(distance, match_indices, match_dis):
+def bipartite_match(distance, match_indices, match_dist):
     """Bipartite Matching algorithm.
     Arg:
         distance (numpy.array) : The distance of two entries with shape [M, N].
         match_indices (numpy.array): the matched indices from column to row
             with shape [1, N], it must be initialized to -1.
-        match_dis (numpy.array): The matched distance from column to row
+        match_dist (numpy.array): The matched distance from column to row
             with shape [1, N], it must be initialized to 0.
     """
     match_pair = []
@@ -36,13 +36,13 @@ def bipartite_match(distance, match_indices, match_dis):
     row_indices = -1 * np.ones((row, ), dtype=np.int)
 
     idx = 0
-    for i, j, dis in match_sorted:
+    for i, j, dist in match_sorted:
         if idx >= row:
             break
-        if match_indices[j] == -1 and row_indices[i] == -1 and dis > 0:
+        if match_indices[j] == -1 and row_indices[i] == -1 and dist > 0:
             match_indices[j] = i
             row_indices[i] = j
-            match_dis[j] = dis
+            match_dist[j] = dist
             idx += 1
 
 
@@ -55,24 +55,24 @@ def batch_bipartite_match(distance, lod):
     n = len(lod) - 1
     m = distance.shape[1]
     match_indices = -1 * np.ones((n, m), dtype=np.int)
-    match_dis = np.zeros((n, m), dtype=np.float32)
+    match_dist = np.zeros((n, m), dtype=np.float32)
     for i in range(len(lod) - 1):
         bipartite_match(distance[lod[i]:lod[i + 1], :], match_indices[i, :],
-                        match_dis[i, :])
-    return match_indices, match_dis
+                        match_dist[i, :])
+    return match_indices, match_dist
 
 
 class TestBipartiteMatchOpForWithLoD(OpTest):
     def setUp(self):
         self.op_type = 'bipartite_match'
         lod = [[0, 5, 11, 23]]
-        dis = np.random.random((23, 217)).astype('float32')
-        match_indices, match_dis = batch_bipartite_match(dis, lod[0])
+        dist = np.random.random((23, 217)).astype('float32')
+        match_indices, match_dist = batch_bipartite_match(dist, lod[0])
 
-        self.inputs = {'DistMat': (dis, lod)}
+        self.inputs = {'DistMat': (dist, lod)}
         self.outputs = {
             'ColToRowMatchIndices': (match_indices),
-            'ColToRowMatchDis': (match_dis),
+            'ColToRowMatchDis': (match_dist),
         }
 
     def test_check_output(self):
@@ -83,13 +83,13 @@ class TestBipartiteMatchOpWithoutLoD(OpTest):
     def setUp(self):
         self.op_type = 'bipartite_match'
         lod = [[0, 8]]
-        dis = np.random.random((8, 17)).astype('float32')
-        match_indices, match_dis = batch_bipartite_match(dis, lod[0])
+        dist = np.random.random((8, 17)).astype('float32')
+        match_indices, match_dist = batch_bipartite_match(dist, lod[0])
 
-        self.inputs = {'DistMat': dis}
+        self.inputs = {'DistMat': dist}
         self.outputs = {
-            'ColToRowMatchIndices': (match_indices),
-            'ColToRowMatchDis': (match_dis),
+            'ColToRowMatchIndices': match_indices,
+            'ColToRowMatchDis': match_dist,
         }
 
     def test_check_output(self):