move split/reshape prim api to auto generated file

cmake/cblas.cmake

@@ -96,6 +96,7 @@ if(NOT DEFINED CBLAS_PROVIDER)
         STATUS
           "Found OpenBLAS (include: ${OPENBLAS_INC_DIR}, library: ${CBLAS_LIBRARIES})"
       )
+
       message(
         STATUS "Found lapack in OpenBLAS (include: ${OPENBLAS_LAPACKE_INC_DIR})"
       )

paddle/fluid/prim/api/api.yaml

@@ -43,3 +43,5 @@
 - sin
 - cos
 - where
+- reshape
+- split

paddle/fluid/prim/api/auto_code_generated/eager_gen.py

@@ -225,14 +225,20 @@ class BaseAPI:
         return inputs, attrs
 
     def parse_output(self, outputs_list):
-
+        output_types_map = {
+            'Tensor[]': 'std::vector<Tensor>',
+        }
         out_type_list = []
         out_name_list = []
         out_size_expr_list = []
         for output_dict in outputs_list:
             if output_dict['intermediate']:
                 continue
-            out_type_list.append(output_dict['typename'])
+            out_type_list.append(
+                output_types_map.get(
+                    output_dict['typename'], output_dict['typename']
+                )
+            )
             out_name_list.append(output_dict['name'])
             if 'size' in output_dict.keys():
                 out_size_expr_list.append(output_dict['size'])

paddle/fluid/prim/api/auto_code_generated/template/utils.cc.j2

@@ -115,7 +115,7 @@ op->SetInput("{{input.fluid_name | to_pascal}}", {std::static_pointer_cast<prim:
   {%- if output.typename is tensor_sequence -%} {#- render the output of type std::Vector<Tensor> -#}
 std::vector<Tensor> {{output.name}};
 std::vector<std::string> {{output.name}}_names;
-for (auto i=0; i<{{output.size}}; i++) {
+for (size_t i=0; i<{{output.size}}; i++) {
   auto tmp = empty<DescTensor>({}, phi::DataType::FLOAT32, paddle::Place());
   {{output.name}}.push_back(tmp);
   {{output.name}}_names.push_back(std::static_pointer_cast<prim::DescTensor>(tmp.impl())->Name());

paddle/fluid/prim/api/manual_prim/eager_prim_api.cc

@@ -19,12 +19,6 @@
 namespace paddle {
 namespace prim {
 
-template <>
-Tensor reshape<Tensor>(const Tensor& x, const IntArray& shape) {
-  VLOG(4) << "Eager Prim API reshape_ad_func call";
-  return ::reshape_ad_func(x, shape);
-}
-
 template <>
 Tensor full<Tensor>(const IntArray& shape,
                     const Scalar& value,
@@ -34,14 +28,6 @@ Tensor full<Tensor>(const IntArray& shape,
   return ::full_ad_func(shape, value, dtype, place);
 }
 
-template <>
-std::vector<Tensor> split<Tensor>(const Tensor& x,
-                                  const IntArray& sections,
-                                  const Scalar& axis) {
-  VLOG(4) << "Eager Prim API split_ad_func call";
-  return ::split_ad_func(x, sections, axis);
-}
-
 template <>
 Tensor cast<Tensor>(const Tensor& x, DataType dtype) {
   return ::cast_ad_func(x, dtype);

paddle/fluid/prim/api/manual_prim/prim_manual_api.h

@@ -29,20 +29,12 @@ using Scalar = paddle::experimental::Scalar;
 using IntArray = paddle::experimental::IntArray;
 using DataType = phi::DataType;
 
-template <typename T>
-Tensor reshape(const Tensor& x, const IntArray& shape);
-
 template <typename T>
 Tensor full(const IntArray& shape,
             const Scalar& value,
             DataType dtype = DataType::FLOAT32,
             const Place& place = CPUPlace());
 
-template <typename T>
-std::vector<Tensor> split(const Tensor& x,
-                          const IntArray& sections,
-                          const Scalar& axis);
-
 template <typename T>
 Tensor cast(const Tensor& x, DataType dtype);
 

paddle/fluid/prim/api/manual_prim/static_prim_api.cc

@@ -37,24 +37,6 @@
 namespace paddle {
 namespace prim {
 
-template <>
-Tensor reshape<DescTensor>(const Tensor& x, const IntArray& shape) {
-  framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();
-  framework::OpDesc* op = block->AppendOp();
-  // TODO(cxxly): move to auto generate dir.
-  op->SetType("reshape2");
-  op->SetInput("X",
-               {std::static_pointer_cast<prim::DescTensor>(x.impl())->Name()});
-  auto out = empty<DescTensor>({}, x.dtype(), paddle::Place());
-  op->SetOutput(
-      "Out", {std::static_pointer_cast<prim::DescTensor>(out.impl())->Name()});
-  op->SetAttr("shape", unsafe_vector_cast<int64_t, int>(shape.GetData()));
-  op->CheckAttrs();
-  op->InferVarType(block);
-  op->InferShape(*block);
-  return out;
-}
-
 template <>
 Tensor full<DescTensor>(const IntArray& shape,
                         const Scalar& value,
@@ -127,32 +109,6 @@ Tensor full<DescTensor>(const IntArray& shape,
   return out;
 }
 
-template <>
-std::vector<Tensor> split<DescTensor>(const Tensor& x,
-                                      const IntArray& sections,
-                                      const Scalar& axis) {
-  int elem_num = sections.size();
-  std::vector<std::string> outs_name;
-  std::vector<Tensor> outs;
-  for (int i = 0; i < elem_num; ++i) {
-    Tensor out = empty<DescTensor>({}, x.dtype(), paddle::Place());
-    std::string out_name =
-        std::static_pointer_cast<prim::DescTensor>(out.impl())->Name();
-    outs_name.push_back(std::move(out_name));
-    outs.push_back(out);
-  }
-  framework::BlockDesc* block = StaticCompositeContext::Instance().GetBlock();
-  framework::OpDesc* op = block->AppendOp();
-  op->SetType("split");
-  op->SetAttr("sections", sections.GetData());
-  op->SetAttr("axis", axis.to<int>());
-  op->SetOutput("Out", outs_name);
-  op->CheckAttrs();
-  op->InferVarType(block);
-  op->InferShape(*block);
-  return outs;
-}
-
 template <>
 Tensor cast<DescTensor>(const Tensor& x, DataType dtype) {
   Tensor out = empty<DescTensor>({}, DataType::FLOAT32, paddle::Place());