diff --git a/paddle/operators/fill_constant_batch_size_like_op.cc b/paddle/operators/fill_constant_batch_size_like_op.cc
index 58c9f1cd2c79c150aaed7753641f6ad6120dd0f5..0244adb42392c707d755e95c7abdebd826c219b4 100644
--- a/paddle/operators/fill_constant_batch_size_like_op.cc
+++ b/paddle/operators/fill_constant_batch_size_like_op.cc
@@ -36,7 +36,12 @@ class FillConstantBatchSizeLikeOp : public framework::OperatorWithKernel {
                    [](int a) { return static_cast<int64_t>(a); });
     auto dims = framework::make_ddim(shape_int64);
 
-    dims[0] = ctx->GetInputDim("Input")[0];
+    int dim_idx = ctx->Attrs().Get<int>("dim_idx");
+    PADDLE_ENFORCE_GE(dim_idx, 0);
+    PADDLE_ENFORCE_GT(static_cast<int>(shape.size()), dim_idx);
+    PADDLE_ENFORCE_GT(ctx->GetInputDim("Input").size(), dim_idx);
+
+    dims[dim_idx] = ctx->GetInputDim("Input")[dim_idx];
     ctx->SetOutputDim("Out", dims);
   }
 
@@ -57,15 +62,18 @@ class FillConstantBatchSizeLikeOpMaker
                  "(int, default 5 (FP32)) "
                  "Output data type")
         .SetDefault(framework::DataType::FP32);
-    AddAttr<std::vector<int>>("shape", "(vector<int>) The shape of the output");
-    AddAttr<float>("value", "(float, default 0) The value to be filled")
-        .SetDefault(0.0f);
     AddInput("Input",
              "(Tensor) Tensor "
-             "whose first dimension is used to specify the batch_size");
+             "whose dim_idx th dimension is used to specify the batch_size");
     AddOutput("Out",
               "(Tensor) Tensor of specified shape will be filled "
               "with the specified value");
+    AddAttr<std::vector<int>>("shape", "(vector<int>) The shape of the output");
+    AddAttr<int>("dim_idx",
+                 "(int, default 0) the index of batch size dimension")
+        .SetDefault(0);
+    AddAttr<float>("value", "(float, default 0) The value to be filled")
+        .SetDefault(0.0f);
     AddComment(R"DOC(Fill up a variable with specified constant value.)DOC");
   }
 };
diff --git a/python/paddle/v2/framework/tests/test_fill_constant_batch_size_like_op.py b/python/paddle/v2/framework/tests/test_fill_constant_batch_size_like_op.py
index 065a9133dca25fac988f9493c1527e0d8f9821dc..319ae52fb38ee122808a6e6b0e44d3a3787d8e53 100644
--- a/python/paddle/v2/framework/tests/test_fill_constant_batch_size_like_op.py
+++ b/python/paddle/v2/framework/tests/test_fill_constant_batch_size_like_op.py
@@ -3,13 +3,27 @@ import numpy as np
 from op_test import OpTest
 
 
-class TestFillConstantBatchSizeLikeOp(OpTest):
+class TestFillConstantBatchSizeLikeWhenFirstDimIsBatchSize(OpTest):
     def setUp(self):
         self.op_type = "fill_constant_batch_size_like"
         self.inputs = {'Input': np.random.random((219, 232)).astype("float32")}
-        self.attrs = {'value': 3.5, 'shape': [-1, 132, 777]}
+        self.attrs = {'value': 3.5, 'shape': [-1, 132, 7]}
 
-        out = np.random.random((219, 132, 777)).astype("float32")
+        out = np.random.random((219, 132, 7)).astype("float32")
+        out.fill(3.5)
+        self.outputs = {'Out': out}
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestFillConstantBatchSizeLikeWhenSecondDimIsBatchSize(OpTest):
+    def setUp(self):
+        self.op_type = "fill_constant_batch_size_like"
+        self.inputs = {'Input': np.random.random((219, 232)).astype("float32")}
+        self.attrs = {'value': 3.5, 'shape': [132, -1, 7], 'dim_idx': 1}
+
+        out = np.random.random((132, 232, 7)).astype("float32")
         out.fill(3.5)
         self.outputs = {'Out': out}