【PTen】Add fill_constant kernel using ScalarArray in pten (#37481)

* add scalar and scalar_array

* remove DenseTensor include from Scalar and ScalarArray

* remove inner header from scalar_array

* refactor the method of fill_constant and add some comment

* add fill_constant kernel using ScalarArray

* modify some prompt

* remove fill_constant kernel with no shape

paddle/fluid/framework/operator.cc

@@ -30,6 +30,7 @@ limitations under the License. */
 #include "paddle/fluid/platform/enforce.h"
 #include "paddle/fluid/platform/profiler.h"
 #include "paddle/pten/common/scalar.h"
+#include "paddle/pten/common/scalar_array.h"
 
 namespace paddle {
 namespace framework {
@@ -1903,26 +1904,59 @@ void OperatorWithKernel::BuildPtenKernelContext(
   }
 
   for (size_t i = 0; i < attr_names.size(); ++i) {
-    auto& attr = Attrs().at(attr_names[i]);
-    if (attr_defs[i].type_index == std::type_index(typeid(pten::Scalar))) {
+    if (attr_defs[i].type_index == std::type_index(typeid(pten::ScalarArray))) {
+      auto attr_iter = Attrs().find(attr_names[i]);
+      if (attr_iter != Attrs().end()) {  // shape is in the attribute
+        if (std::type_index(attr_iter->second.type()) ==
+            std::type_index(typeid(std::vector<int64_t>))) {
+          pt_kernel_context_->EmplaceBackAttr(std::move(pten::ScalarArray(
+              BOOST_GET_CONST(std::vector<int64_t>, attr_iter->second))));
+        } else {
+          PADDLE_THROW(platform::errors::Unimplemented(
+              "Unsupported cast op attribute `%s` to ScalarArray when "
+              "construct KernelContext.",
+              attr_names[i]));
+        }
+      } else {  // shape is in the input
+        auto& ins_vector = ctx.inputs.at(attr_names[i]);
+        if (ins_vector.size() == 1) {  // ShapeTensor
+          pt_kernel_context_->EmplaceBackAttr(std::move(
+              experimental::MakePtenScalarArrayFromVar(*ins_vector.front())));
+        } else {  // ShapeTensorList
+          pt_kernel_context_->EmplaceBackAttr(std::move(
+              experimental::MakePtenScalarArrayFromVarList(ins_vector)));
+        }
+      }
+    } else if (attr_defs[i].type_index ==
+               std::type_index(typeid(pten::Scalar))) {
       // TODO(chenweihang): support other attrs later
       // TODO(zhangyunfei): Scalar should hold scaler type, and we should check
       // attribtue type by attr_defs
-      if (std::type_index(attr.type()) == std::type_index(typeid(float))) {
-        pt_kernel_context_->EmplaceBackAttr(
-            std::move(pten::Scalar(BOOST_GET_CONST(float, attr))));
-      } else if (std::type_index(attr.type()) ==
-                 std::type_index(typeid(std::string))) {
-        pt_kernel_context_->EmplaceBackAttr(
-            std::move(pten::Scalar(BOOST_GET_CONST(std::string, attr))));
+      auto attr_iter = Attrs().find(attr_names[i]);
+      if (attr_iter != Attrs().end()) {  // scalar is in the attribute
+        auto& attr = Attrs().at(attr_names[i]);
+        if (std::type_index(attr.type()) == std::type_index(typeid(float))) {
+          pt_kernel_context_->EmplaceBackAttr(
+              std::move(pten::Scalar(BOOST_GET_CONST(float, attr))));
+        } else if (std::type_index(attr.type()) ==
+                   std::type_index(typeid(std::string))) {
+          pt_kernel_context_->EmplaceBackAttr(
+              std::move(pten::Scalar(BOOST_GET_CONST(std::string, attr))));
+        } else {
+          PADDLE_THROW(platform::errors::Unimplemented(
+              "Unsupported cast op attribute `%s` to Scalar when construct "
+              "KernelContext.",
+              attr_names[i]));
+        }
       } else {
-        PADDLE_THROW(platform::errors::Unimplemented(
-            "unsupported cast op attribute `%s` to Scalar when construct "
-            "KernelContext.",
-            attr_names[i]));
+        auto& ins_vector = ctx.inputs.at(attr_names[i]);
+        pt_kernel_context_->EmplaceBackAttr(std::move(
+            experimental::MakePtenScalarFromVar(*ins_vector.front())));
       }
+
     } else {
       // TODO(chenweihang): support other attrs later
+      auto& attr = Attrs().at(attr_names[i]);
       if (attr_defs[i].type_index == std::type_index(typeid(int))) {
         pt_kernel_context_->EmplaceBackAttr(BOOST_GET_CONST(int, attr));
       } else if (attr_defs[i].type_index == std::type_index(typeid(float))) {
@@ -1949,7 +1983,7 @@ void OperatorWithKernel::BuildPtenKernelContext(
 
       } else {
         PADDLE_THROW(platform::errors::Unimplemented(
-            "unsupported cast op attribute `%s` when construct "
+            "Unsupported cast op attribute `%s` when construct "
             "KernelContext.",
             attr_names[i]));
       }

paddle/fluid/imperative/prepared_operator.cc

@@ -19,6 +19,7 @@
 #include "paddle/fluid/imperative/infer_shape_context.h"
 #include "paddle/fluid/imperative/tracer.h"
 #include "paddle/pten/common/scalar.h"
+#include "paddle/pten/common/scalar_array.h"
 #include "paddle/utils/small_vector.h"
 #ifdef PADDLE_WITH_XPU
 #include "paddle/fluid/platform/device/xpu/xpu_op_list.h"
@@ -385,26 +386,66 @@ static void BuildDygraphPtenKernelContext(
   }
 
   for (size_t i = 0; i < attr_names.size(); ++i) {
-    auto& attr = GetAttr(attrs, default_attrs, attr_names[i]);
-    if (attr_defs[i].type_index == std::type_index(typeid(pten::Scalar))) {
+    if (attr_defs[i].type_index == std::type_index(typeid(pten::ScalarArray))) {
+      if (attrs.find(attr_names[i]) !=
+          attrs.end()) {  // shape is in the attribute
+        auto& attr = GetAttr(attrs, default_attrs, attr_names[i]);
+        if (std::type_index(attr.type()) ==
+            std::type_index(typeid(std::vector<int64_t>))) {
+          kernel_ctx->EmplaceBackAttr(std::move(
+              pten::ScalarArray(BOOST_GET_CONST(std::vector<int64_t>, attr))));
+        } else {
+          PADDLE_THROW(platform::errors::Unimplemented(
+              "Unsupported cast op attribute `%s` to VectorTensor when "
+              "construct KernelContext.",
+              attr_names[i]));
+        }
+      } else {  // shape is in the input
+        auto& ins_vector = ins.at(attr_names[i]);
+        if (ins_vector.size() == 1) {  // ShapeTensor
+          kernel_ctx->EmplaceBackAttr(std::move(
+              experimental::MakePtenScalarArrayFromVar(ins_vector[0]->Var())));
+        } else {  // ShapeTensorList
+          std::vector<framework::Variable*> variables;
+          variables.reserve(ins_vector.size());
+          for (const auto& var_base : ins_vector) {
+            variables.push_back(var_base->MutableVar());
+          }
+          kernel_ctx->EmplaceBackAttr(std::move(
+              experimental::MakePtenScalarArrayFromVarList(variables)));
+        }
+      }
+    } else if (attr_defs[i].type_index ==
+               std::type_index(typeid(pten::Scalar))) {
       // TODO(chenweihang): support other attrs later
       // TODO(zhangyunfei): Scalar should hold scaler type, and we should check
       // attribtue type by attr_defs
-      if (std::type_index(attr.type()) == std::type_index(typeid(float))) {
-        kernel_ctx->EmplaceBackAttr(
-            std::move(pten::Scalar(BOOST_GET_CONST(float, attr))));
-      } else if (std::type_index(attr.type()) ==
-                 std::type_index(typeid(std::string))) {
-        kernel_ctx->EmplaceBackAttr(
-            std::move(pten::Scalar(BOOST_GET_CONST(std::string, attr))));
-      } else {
-        PADDLE_THROW(platform::errors::Unimplemented(
-            "unsupported cast op attribute `%s` to Scalar when construct "
-            "KernelContext in dygraph.",
-            attr_names[i]));
+      if (attrs.find(attr_names[i]) != attrs.end() ||
+          default_attrs.find(attr_names[i]) !=
+              default_attrs.end()) {  // scalar is in the attribute
+        auto& attr = GetAttr(attrs, default_attrs, attr_names[i]);
+        if (std::type_index(attr.type()) == std::type_index(typeid(float))) {
+          kernel_ctx->EmplaceBackAttr(
+              std::move(pten::Scalar(BOOST_GET_CONST(float, attr))));
+        } else if (std::type_index(attr.type()) ==
+                   std::type_index(typeid(std::string))) {
+          kernel_ctx->EmplaceBackAttr(
+              std::move(pten::Scalar(BOOST_GET_CONST(std::string, attr))));
+        } else {
+          PADDLE_THROW(platform::errors::Unimplemented(
+              "Unsupported cast op attribute `%s` to Scalar when construct "
+              "KernelContext in dygraph.",
+              attr_names[i]));
+        }
+      } else {  // scalar is in the input
+        auto& ins_vector = ins.at(attr_names[i]);
+        kernel_ctx->EmplaceBackAttr(std::move(
+            experimental::MakePtenScalarFromVar(ins_vector[0]->Var())));
       }
+
     } else {
       // TODO(chenweihang): support other attrs later
+      auto& attr = GetAttr(attrs, default_attrs, attr_names[i]);
       if (attr_defs[i].type_index == std::type_index(typeid(int))) {
         kernel_ctx->EmplaceBackAttr(BOOST_GET_CONST(int, attr));
       } else if (attr_defs[i].type_index == std::type_index(typeid(float))) {
@@ -430,7 +471,7 @@ static void BuildDygraphPtenKernelContext(
         // TODO(YuanRisheng) Need support vector<int64_t> attr
       } else {
         PADDLE_THROW(platform::errors::Unimplemented(
-            "unsupported cast op attribute `%s` when construct "
+            "Unsupported cast op attribute `%s` when construct "
             "KernelContext in dygraph.",
             attr_names[i]));
       }

paddle/fluid/operators/fill_constant_op.cc

@@ -102,13 +102,23 @@ class FillConstantOp : public framework::OperatorWithKernel {
 
   framework::KernelSignature GetExpectedPtenKernelArgs(
       const framework::ExecutionContext& ctx) const override {
-    if (!ctx.HasInput("ShapeTensor") &&
-        ctx.MultiInput<framework::Tensor>("ShapeTensorList").empty() &&
-        !ctx.HasInput("ValueTensor") &&
-        !ctx.OutputVar("Out")->IsType<framework::SelectedRows>()) {
+    std::string shape;
+    if (ctx.HasInput("ShapeTensor")) {
+      shape = "ShapeTensor";
+    } else if (ctx.MultiInput<framework::Tensor>("ShapeTensorList").size()) {
+      shape = "ShapeTensorList";
+    } else {
+      shape = "shape";
+    }
+    std::string value;
+    if (ctx.HasInput("ValueTensor")) {
+      value = "ValueTensor";
+    } else {
       const auto& str_value = ctx.Attr<std::string>("str_value");
-      std::string value = str_value.empty() ? "value" : "str_value";
-      return framework::KernelSignature("fill_constant.scalar", {}, {value},
+      value = str_value.empty() ? "value" : "str_value";
+    }
+    if (!ctx.OutputVar("Out")->IsType<framework::SelectedRows>()) {
+      return framework::KernelSignature("fill_constant", {}, {shape, value},
                                         {"Out"});
     }
     return framework::KernelSignature("fill_constant.unregistered", {}, {}, {});

paddle/pten/api/lib/utils/tensor_utils.cc

@@ -97,6 +97,168 @@ std::unique_ptr<pten::DenseTensor> MakePtenDenseTensor(
   }
 }
 
+pten::Scalar MakePtenScalar(const paddle::framework::LoDTensor& src) {
+  PADDLE_ENFORCE_EQ(src.numel(),
+                    1,
+                    paddle::platform::errors::InvalidArgument(
+                        "The Scalar only supports Tensor with 1 element, "
+                        "but now Tensor has %d element.",
+                        src.numel()));
+  switch (src.type()) {
+    case paddle::framework::proto::VarType::FP32:
+      return {src.template data<float>()[0]};
+    case paddle::framework::proto::VarType::FP64:
+      return {src.template data<double>()[0]};
+    case paddle::framework::proto::VarType::FP16:
+      return {src.template data<float16>()[0]};
+    case paddle::framework::proto::VarType::BF16:
+      return {src.template data<bfloat16>()[0]};
+    case paddle::framework::proto::VarType::INT32:
+      return {src.template data<int32_t>()[0]};
+    case paddle::framework::proto::VarType::INT64:
+      return {src.template data<int64_t>()[0]};
+    case paddle::framework::proto::VarType::INT16:
+      return {src.template data<int16_t>()[0]};
+    case paddle::framework::proto::VarType::INT8:
+      return {src.template data<int8_t>()[0]};
+    case paddle::framework::proto::VarType::UINT8:
+      return {src.template data<uint8_t>()[0]};
+    case paddle::framework::proto::VarType::BOOL:
+      return {src.template data<bool>()[0]};
+    case paddle::framework::proto::VarType::COMPLEX64:
+      return {src.template data<complex64>()[0]};
+    case paddle::framework::proto::VarType::COMPLEX128:
+      return {src.template data<complex128>()[0]};
+    default:
+      PADDLE_THROW(paddle::platform::errors::InvalidArgument(
+          "Data type error. Don't support casting a %d LoDTensor to Scalar.",
+          src.type()));
+  }
+}
+
+pten::Scalar MakePtenScalarFromVar(const framework::Variable& variable) {
+  auto expected_place = pten::TransToFluidPlace(pten::Backend::CPU);
+  if (variable.IsType<framework::LoDTensor>()) {
+    const auto& tensor = variable.Get<framework::LoDTensor>();
+    if (!platform::is_same_place(tensor.place(), expected_place)) {
+      framework::LoDTensor tmp_tensor;
+      framework::TensorCopySync(tensor, expected_place, &tmp_tensor);
+      return MakePtenScalar(tmp_tensor);
+    } else {
+      return MakePtenScalar(tensor);
+    }
+  } else {
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "Unsupport casting input `%s` type to Scalar when call pt "
+        "kernel.",
+        framework::ToTypeName(variable.Type())));
+  }
+}
+
+pten::ScalarArray MakePtenScalarArray(const paddle::framework::LoDTensor& src) {
+  if (src.type() == paddle::framework::proto::VarType::INT64) {
+    return {src.data<int64_t>(), src.numel()};
+  } else if (src.type() == paddle::framework::proto::VarType::INT32) {
+    return {src.data<int32_t>(), src.numel()};
+  } else {
+    PADDLE_THROW(paddle::platform::errors::InvalidArgument(
+        "Data type error. When cast a LoDTensor to ScalarArray, "
+        "the data type of LoDTensor must be int32 or int64, "
+        "but now data type is %s.",
+        src.type()));
+  }
+}
+
+pten::ScalarArray MakePtenScalarArrayFromVar(
+    const framework::Variable& variable) {
+  auto expected_place = pten::TransToFluidPlace(pten::Backend::CPU);
+  if (variable.IsType<framework::LoDTensor>()) {
+    const auto& tensor = variable.Get<framework::LoDTensor>();
+    if (!platform::is_same_place(tensor.place(), expected_place)) {
+      framework::LoDTensor tmp_tensor;
+      framework::TensorCopySync(tensor, expected_place, &tmp_tensor);
+      return MakePtenScalarArray(tmp_tensor);
+    } else {
+      return MakePtenScalarArray(tensor);
+    }
+  } else {
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "Unsupport casting input `%s` type to ScalarArray when call pt "
+        "kernel.",
+        framework::ToTypeName(variable.Type())));
+  }
+}
+
+pten::ScalarArray MakePtenScalarArrayFromVarList(
+    const std::vector<framework::Variable*>& variable_list) {
+  if (variable_list.size() == 0) {
+    return pten::ScalarArray();
+  }
+  auto expected_place = pten::TransToFluidPlace(pten::Backend::CPU);
+
+  paddle::framework::proto::VarType::Type data_type;
+  auto* first_var = variable_list.front();
+  if (first_var->IsType<framework::LoDTensor>()) {
+    const auto& tensor = first_var->Get<framework::LoDTensor>();
+    data_type = tensor.type();
+  } else {
+    PADDLE_THROW(platform::errors::Unimplemented(
+        "Unsupport casting input `%s` type to VectorTensor when call pt "
+        "kernel.",
+        framework::ToTypeName(first_var->Type())));
+  }
+
+  std::vector<int64_t> vector_data;
+  vector_data.reserve(variable_list.size());
+
+  if (data_type == paddle::framework::proto::VarType::INT64) {
+    for (auto* var : variable_list) {
+      if (var->IsType<framework::LoDTensor>()) {
+        const auto& tensor = var->Get<framework::LoDTensor>();
+        if (!platform::is_same_place(tensor.place(), expected_place)) {
+          framework::LoDTensor tmp_tensor;
+          framework::TensorCopySync(tensor, expected_place, &tmp_tensor);
+          vector_data.push_back(*tmp_tensor.data<int64_t>());
+        } else {
+          vector_data.push_back(*tensor.data<int64_t>());
+        }
+      } else {
+        PADDLE_THROW(platform::errors::Unimplemented(
+            "Unsupport casting input `%s` type to VectorTensor when call pt "
+            "kernel.",
+            framework::ToTypeName(var->Type())));
+      }
+    }
+
+  } else if (data_type == paddle::framework::proto::VarType::INT32) {
+    for (auto* var : variable_list) {
+      if (var->IsType<framework::LoDTensor>()) {
+        const auto& tensor = var->Get<framework::LoDTensor>();
+        if (!platform::is_same_place(tensor.place(), expected_place)) {
+          framework::LoDTensor tmp_tensor;
+          framework::TensorCopySync(tensor, expected_place, &tmp_tensor);
+          vector_data.push_back(*tmp_tensor.data<int32_t>());
+        } else {
+          vector_data.push_back(*tensor.data<int32_t>());
+        }
+      } else {
+        PADDLE_THROW(platform::errors::Unimplemented(
+            "Unsupport casting input `%s` type to VectorTensor when call pt "
+            "kernel.",
+            framework::ToTypeName(var->Type())));
+      }
+    }
+  } else {
+    PADDLE_THROW(paddle::platform::errors::InvalidArgument(
+        "Data type error. When cast a LoDTensor to VectorTensor, "
+        "the data type of LoDTensor must be int32 or int64, "
+        "but now data type is %s.",
+        data_type));
+  }
+
+  return {vector_data};
+}
+
 std::unique_ptr<pten::TensorBase> MakePtenTensorBaseFromVar(
     const framework::Variable& variable, const pten::TensorArgDef& arg_def) {
   auto expected_place = pten::TransToFluidPlace(arg_def.backend);

paddle/pten/api/lib/utils/tensor_utils.h

@@ -21,6 +21,8 @@ limitations under the License. */
 
 #include "paddle/pten/api/lib/utils/allocator.h"
 #include "paddle/pten/api/lib/utils/storage.h"
+#include "paddle/pten/common/scalar.h"
+#include "paddle/pten/common/scalar_array.h"
 #include "paddle/pten/core/convert_utils.h"
 #include "paddle/pten/core/dense_tensor.h"
 #include "paddle/pten/core/kernel_factory.h"
@@ -34,6 +36,18 @@ std::unique_ptr<pten::DenseTensor> MakePtenDenseTensor(
 std::unique_ptr<pten::DenseTensor> MakePtenDenseTensor(
     const paddle::framework::LoDTensor& src);
 
+pten::Scalar MakePtenScalar(const paddle::framework::LoDTensor& src);
+
+pten::ScalarArray MakePtenScalarArray(const paddle::framework::LoDTensor& src);
+
+pten::Scalar MakePtenScalarFromVar(const framework::Variable& variable);
+
+pten::ScalarArray MakePtenScalarArrayFromVar(
+    const framework::Variable& variable);
+
+pten::ScalarArray MakePtenScalarArrayFromVarList(
+    const std::vector<framework::Variable*>& variable_list);
+
 std::unique_ptr<pten::TensorBase> MakePtenTensorBaseFromVar(
     const framework::Variable& variable, const pten::TensorArgDef& arg_def);
 

paddle/pten/common/scalar_array.h

@@ -118,7 +118,7 @@ class ScalarArrayBase {
   /// \brief Assign the data_ from const data pointer value of type T.
   template <typename TYPE>
   void AssignData(const TYPE* value_data, int64_t n) {
-    if (value_data) {
+    if (value_data || n == 0) {
       array_.reserve(n);
       for (auto i = 0; i < n; ++i) {
         array_.push_back(static_cast<int64_t>(value_data[i]));

paddle/pten/kernels/cpu/creation.cc

@@ -52,16 +52,9 @@ void FillAnyLike(const CPUContext& dev_ctx,
 
 template <typename T>
 void FillConstant(const CPUContext& dev_ctx,
+                  const ScalarArray& shape,
                   const Scalar& val,
                   DenseTensor* out) {
-  eigen::fill<CPUContext, T>(dev_ctx, out, val.to<T>());
-}
-
-template <typename T>
-void FillConstantDynamicShape(const CPUContext& dev_ctx,
-                              const ScalarArray& shape,
-                              const Scalar& val,
-                              DenseTensor* out) {
   out->Resize(paddle::framework::make_ddim(shape.GetData()));
   eigen::fill<CPUContext, T>(dev_ctx, out, val.to<T>());
 }
@@ -81,26 +74,10 @@ PT_REGISTER_KERNEL("fill_any_like",
                    bool,
                    paddle::platform::float16) {}
 
-PT_REGISTER_KERNEL("fill_constant.scalar",
-                   CPU,
-                   ANY,
-                   pten::FillConstant,
-                   float,
-                   double,
-                   uint8_t,
-                   int16_t,
-                   int,
-                   int64_t,
-                   bool,
-                   paddle::platform::float16,
-                   paddle::platform::bfloat16,
-                   paddle::platform::complex<float>,
-                   paddle::platform::complex<double>) {}
-
 PT_REGISTER_KERNEL("fill_constant",
                    CPU,
                    ANY,
-                   pten::FillConstantDynamicShape,
+                   pten::FillConstant,
                    float,
                    double,
                    uint8_t,

paddle/pten/kernels/cpu/creation.h

@@ -31,13 +31,8 @@ void FillAnyLike(const CPUContext& dev_ctx,
 
 template <typename T>
 void FillConstant(const CPUContext& dev_ctx,
+                  const ScalarArray& shape,
                   const Scalar& val,
                   DenseTensor* out);
 
-template <typename T>
-void FillConstantDynamicShape(const CPUContext& dev_ctx,
-                              const ScalarArray& shape,
-                              const Scalar& val,
-                              DenseTensor* out);
-
 }  // namespace pten

paddle/pten/kernels/cuda/creation.cu

@@ -53,16 +53,9 @@ void FillAnyLike(const CUDAContext& dev_ctx,
 
 template <typename T>
 void FillConstant(const CUDAContext& dev_ctx,
+                  const ScalarArray& shape,
                   const Scalar& val,
                   DenseTensor* out) {
-  eigen::fill<CUDAContext, T>(dev_ctx, out, val.to<T>());
-}
-
-template <typename T>
-void FillConstantDynamicShape(const CUDAContext& dev_ctx,
-                              const ScalarArray& shape,
-                              const Scalar& val,
-                              DenseTensor* out) {
   out->Resize(paddle::framework::make_ddim(shape.GetData()));
   eigen::fill<CUDAContext, T>(dev_ctx, out, val.to<T>());
 }
@@ -82,25 +75,10 @@ PT_REGISTER_KERNEL("fill_any_like",
                    bool,
                    paddle::platform::float16) {}
 
-PT_REGISTER_KERNEL("fill_constant.scalar",
-                   CUDA,
-                   ANY,
-                   pten::FillConstant,
-                   float,
-                   double,
-                   uint8_t,
-                   int16_t,
-                   int,
-                   int64_t,
-                   bool,
-                   paddle::platform::float16,
-                   paddle::platform::complex<float>,
-                   paddle::platform::complex<double>) {}
-
 PT_REGISTER_KERNEL("fill_constant",
                    CUDA,
                    ANY,
-                   pten::FillConstantDynamicShape,
+                   pten::FillConstant,
                    float,
                    double,
                    uint8_t,

paddle/pten/kernels/cuda/creation.h

@@ -34,15 +34,10 @@ void FillAnyLike(const CUDAContext& dev_ctx,
 
 template <typename T>
 void FillConstant(const CUDAContext& dev_ctx,
+                  const ScalarArray& shape,
                   const Scalar& val,
                   DenseTensor* out);
 
-template <typename T>
-void FillConstantDynamicShape(const CUDAContext& dev_ctx,
-                              const ScalarArray& shape,
-                              const Scalar& val,
-                              DenseTensor* out);
-
 }  // namespace pten
 
 #endif