diff --git a/paddle/fluid/operators/mkldnn/transpose_mkldnn_op.cc b/paddle/fluid/operators/mkldnn/transpose_mkldnn_op.cc
index e41bfb80dfc0452955f7978f74ccfea184886b69..4debc7ca5ec90d6cc781d10e817e9ed8650f12aa 100644
--- a/paddle/fluid/operators/mkldnn/transpose_mkldnn_op.cc
+++ b/paddle/fluid/operators/mkldnn/transpose_mkldnn_op.cc
@@ -73,6 +73,29 @@ class TransposeMKLDNNOpKernel : public paddle::framework::OpKernel<T> {
   }
 };
 
+template <typename T>
+class TransposeINT8MKLDNNOpKernel : public paddle::framework::OpKernel<T> {
+ public:
+  void Compute(const paddle::framework::ExecutionContext& ctx) const override {
+    std::vector<int> axis = ctx.Attr<std::vector<int>>("axis");
+    std::vector<int> axis_int8 = {0, 2, 3, 1};
+    if (axis.size() != 1) {
+      PADDLE_ENFORCE_EQ(axis.size(), axis_int8.size());
+      for (size_t i = 0; i < axis.size(); i++) {
+        PADDLE_ENFORCE_EQ(axis[i], axis_int8[i],
+                          "Current INT8 MKLDNN Transpose kernel only surpport "
+                          "axis with [0, 2, 3, 1] due to MKL-DNN kernel "
+                          "implementation.");
+      }
+    }
+    auto* input = ctx.Input<Tensor>("X");
+    auto* output = ctx.Output<Tensor>("Out");
+    output->ShareDataWith(*input);
+    output->set_layout(DataLayout::kMKLDNN);
+    output->set_format(input->format());
+  }
+};
+
 template <typename T>
 class TransposeMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
  public:
@@ -140,7 +163,10 @@ class TransposeMKLDNNGradOpKernel : public paddle::framework::OpKernel<T> {
 namespace ops = paddle::operators;
 
 REGISTER_OP_KERNEL(transpose2, MKLDNN, ::paddle::platform::CPUPlace,
-                   ops::TransposeMKLDNNOpKernel<float>);
+                   ops::TransposeMKLDNNOpKernel<float>,
+                   ops::TransposeINT8MKLDNNOpKernel<uint8_t>,
+                   ops::TransposeINT8MKLDNNOpKernel<int8_t>);
+
 REGISTER_OP_KERNEL(transpose, MKLDNN, ::paddle::platform::CPUPlace,
                    ops::TransposeMKLDNNOpKernel<float>);
 
diff --git a/python/paddle/fluid/tests/unittests/mkldnn/test_transpose_int8_mkldnn_op.py b/python/paddle/fluid/tests/unittests/mkldnn/test_transpose_int8_mkldnn_op.py
new file mode 100644
index 0000000000000000000000000000000000000000..a8127bcc781378fa5ef4a189a0b14d079a793946
--- /dev/null
+++ b/python/paddle/fluid/tests/unittests/mkldnn/test_transpose_int8_mkldnn_op.py
@@ -0,0 +1,78 @@
+# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+from paddle.fluid.tests.unittests.op_test import OpTest
+from mkldnn_op_test import format_reorder
+
+
+class TestTransposeOp(OpTest):
+    def setUp(self):
+        self.init_op_type()
+        self.initTestCase()
+        self.initInputData()
+        self.use_mkldnn = True
+        self.axis = (0, 2, 3, 1)
+
+        self.inputs = {
+            'X': format_reorder(self.input_data, self.shape)
+        }  #transform data format to 'NHWC' for INT8 transpose specially.
+
+        self.attrs = {
+            'axis': list(self.axis),
+            'use_mkldnn': self.use_mkldnn,
+        }
+
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype('int8'),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+    def init_op_type(self):
+        self.op_type = "transpose2"
+
+    def test_check_output(self):
+        self.check_output(no_check_set=['XShape'])
+
+    def initTestCase(self):
+        self.shape = (2, 3, 4, 5)
+
+    def initInputData(self):
+        self.input_data = (
+            np.random.randint(0, 100, self.shape) - 50).astype('int8')
+
+
+class TestINT8Case(TestTransposeOp):
+    def initTestCase(self):
+        self.shape = (2, 4, 6, 8)
+
+    def initInputData(self):
+        self.input_data = (
+            np.random.randint(0, 100, self.shape) - 50).astype('int8')
+
+
+class TestUINT8Case(TestTransposeOp):
+    def initTestCase(self):
+        self.shape = (1, 3, 5, 7)
+
+    def initDataType(self):
+        self.input_data = (np.random.randint(0, 100,
+                                             self.shape)).astype('uint8')
+
+
+if __name__ == '__main__':
+    unittest.main()