diff --git a/paddle/fluid/operators/linspace_op.cc b/paddle/fluid/operators/linspace_op.cc
index 667c6e892956e29478f1401c3cb2622713433037..7cc07383bfa5f67a2404b220cb481d9017b40fd8 100644
--- a/paddle/fluid/operators/linspace_op.cc
+++ b/paddle/fluid/operators/linspace_op.cc
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
 limitations under the License. */
 
 #include "paddle/fluid/operators/linspace_op.h"
+#include <string>
 
 namespace paddle {
 namespace operators {
@@ -21,7 +22,7 @@ class LinspaceOp : public framework::OperatorWithKernel {
  public:
   using framework::OperatorWithKernel::OperatorWithKernel;
 
-  void InferShape(framework::InferShapeContext* ctx) const override {
+  void InferShape(framework::InferShapeContext *ctx) const override {
     OP_INOUT_CHECK(ctx->HasInput("Start"), "Input", "Start", "linspace");
     OP_INOUT_CHECK(ctx->HasInput("Stop"), "Input", "Stop", "linspace");
     OP_INOUT_CHECK(ctx->HasInput("Num"), "Input", "Num", "linspace");
@@ -50,11 +51,17 @@ class LinspaceOp : public framework::OperatorWithKernel {
 
  protected:
   framework::OpKernelType GetExpectedKernelType(
-      const framework::ExecutionContext& ctx) const override {
+      const framework::ExecutionContext &ctx) const override {
     return framework::OpKernelType(
         framework::proto::VarType::Type(ctx.Attr<int>("dtype")),
         ctx.GetPlace());
   }
+
+  framework::OpKernelType GetKernelTypeForVar(
+      const std::string &var_name, const framework::Tensor &tensor,
+      const framework::OpKernelType &expected_kernel_type) const override {
+    return expected_kernel_type;
+  }
 };
 
 class LinspaceOpMaker : public framework::OpProtoAndCheckerMaker {
diff --git a/python/paddle/fluid/layers/tensor.py b/python/paddle/fluid/layers/tensor.py
index cf52f3b00fb2739d186021dc51d6aa0f506be706..2fba578ec077f2a74388d433bf3ab5b3098e81ad 100644
--- a/python/paddle/fluid/layers/tensor.py
+++ b/python/paddle/fluid/layers/tensor.py
@@ -1453,11 +1453,14 @@ def linspace(start, stop, num, dtype=None, name=None):
     if not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
     if not isinstance(start, Variable):
-        tensor_start = fill_constant([1], dtype, start)
+        with device_guard("cpu"):
+            tensor_start = fill_constant([1], dtype, start)
     if not isinstance(stop, Variable):
-        tensor_stop = fill_constant([1], dtype, stop)
+        with device_guard("cpu"):
+            tensor_stop = fill_constant([1], dtype, stop)
     if not isinstance(num, Variable):
-        tensor_num = fill_constant([1], 'int32', num)
+        with device_guard("cpu"):
+            tensor_num = fill_constant([1], 'int32', num)
     if in_dygraph_mode():
         return core.ops.linspace(tensor_start, tensor_stop, tensor_num, 'dtype',
                                  dtype)