diff --git a/src/operator/tensor/matrix_op-inl.h b/src/operator/tensor/matrix_op-inl.h
index 611dd7287206..4df32d6a6331 100644
--- a/src/operator/tensor/matrix_op-inl.h
+++ b/src/operator/tensor/matrix_op-inl.h
@@ -330,8 +330,11 @@ void Transpose(const nnvm::NodeAttrs& attrs,
                const std::vector<TBlob>& inputs,
                const std::vector<OpReqType>& req,
                const std::vector<TBlob>& outputs) {
+  if (req[0] == kNullOp) {
+    return;
+  }
   const TransposeParam& param = nnvm::get<TransposeParam>(attrs.parsed);
-  CHECK_EQ(req[0], kWriteTo) << "Transpose does not support inplace";
+  CHECK_EQ(req[0], kWriteTo) << "Transpose does not support kWriteInplace and kAddTo";
   if (param.axes.ndim() == 0) {
     mxnet::TShape axes(inputs[0].ndim(), -1);
     for (int i = 0; i < axes.ndim(); ++i) {
diff --git a/src/operator/tensor/matrix_op.cc b/src/operator/tensor/matrix_op.cc
index f02a38ac07c4..9137737095ab 100644
--- a/src/operator/tensor/matrix_op.cc
+++ b/src/operator/tensor/matrix_op.cc
@@ -322,8 +322,11 @@ static void TransposeComputeExCPU(const nnvm::NodeAttrs& attrs,
                                   const std::vector<NDArray>& inputs,
                                   const std::vector<OpReqType>& req,
                                   const std::vector<NDArray>& outputs) {
+  if (req[0] == kNullOp) {
+    return;
+  }
   const TransposeParam& param = nnvm::get<TransposeParam>(attrs.parsed);
-  CHECK_EQ(req[0], kWriteTo) << "Transpose does not support inplace";
+  CHECK_EQ(req[0], kWriteTo) << "Transpose does not support kWriteInplace and kAddTo";
   CHECK_EQ(inputs.size(), 1U);
   CHECK_EQ(outputs.size(), 1U);
 
diff --git a/tests/python/unittest/test_symbol.py b/tests/python/unittest/test_symbol.py
index 28f302f9ec15..ae770ed0644f 100644
--- a/tests/python/unittest/test_symbol.py
+++ b/tests/python/unittest/test_symbol.py
@@ -389,6 +389,22 @@ def test_children_same_name():
     for c in b.get_children():
         pass
 
+
+def test_transpose_nullop():
+    for dim in range(1, 7):
+        a = mx.sym.Variable('a')
+        b = mx.sym.transpose(a, axes=tuple(np.random.permutation(dim)))
+        c = mx.sym.zeros_like(b)
+
+        shape = rand_shape_nd(dim)
+        nd_a = mx.nd.random.normal(shape=shape)
+        c_out = c.eval(ctx=mx.cpu(), a=nd_a)
+        b_out = b.eval(ctx=mx.cpu(), a=nd_a)
+
+        assert mx.test_utils.same(c_out[0].asnumpy(),
+                                  np.zeros_like(b_out[0].asnumpy()))
+
+
 def test_gen_atomic_symbol_multiple_outputs():
     data=mx.sym.Variable('data')
     p = mx.sym.Variable('param')