【PTen】Adjust the format of full kernel (#38596)

* adjust the full kernel

* remove creation.h

* use Empty to create tensor in full

paddle/fluid/operators/fill_any_like_op.h

@@ -20,7 +20,7 @@ limitations under the License. */
 #include "paddle/fluid/framework/pten_utils.h"
 
 #include "paddle/pten/include/core.h"
-#include "paddle/pten/include/creation.h"
+#include "paddle/pten/kernels/full_kernel.h"
 
 namespace paddle {
 namespace operators {
@@ -65,7 +65,7 @@ class FillAnyLikeKernel : public framework::OpKernel<T> {
 
     const auto& dev_ctx = context.template device_context<DeviceContext>();
     // call new kernel
-    pten::FullLike<T>(dev_ctx, value, pt_out.get());
+    pten::FullLikeKernel<T>(dev_ctx, value, pt_out.get());
   }
 };
 

paddle/pten/all.h

@@ -16,7 +16,6 @@ limitations under the License. */
 
 // developer apis
 #include "paddle/pten/include/core.h"
-#include "paddle/pten/include/creation.h"
 #include "paddle/pten/include/infermeta.h"
 #include "paddle/pten/include/linalg.h"
 #include "paddle/pten/include/manipulation.h"

paddle/pten/include/creation.h

-// Copyright (c) 2021 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.
-
-#pragma once
-
-#include "paddle/pten/api/lib/utils/storage.h"
-#include "paddle/pten/include/infermeta.h"
-#include "paddle/pten/kernels/empty_kernel.h"
-#include "paddle/pten/kernels/full_kernel.h"
-
-namespace pten {
-
-// TODO(YuanRisheng) This function name should be same as User API name.
-// TODO(zyfncg) Automatic code generation
-template <typename T, typename ContextT>
-DenseTensor Full(const ContextT& dev_ctx,
-                 const ScalarArray& shape,
-                 const Scalar& val,
-                 DataType dtype = DataType::FLOAT32,
-                 Backend backend = Backend::CPU,  // Is backend needed here?
-                 DataLayout layout = DataLayout::NCHW) {
-  auto out_meta = CreateInferMeta(shape, dtype, layout);
-  pten::DenseTensor dense_out(
-      pten::make_intrusive<paddle::experimental::SharedStorage>(
-          dev_ctx.GetPlace()),
-      std::move(out_meta));
-  Full<T, ContextT>(dev_ctx, shape, val, &dense_out);
-  return dense_out;
-}
-
-template <typename T, typename ContextT>
-DenseTensor FullLike(
-    const ContextT& dev_ctx,
-    const DenseTensor& x,
-    const Scalar& val,
-    DataType dtype = DataType::UNDEFINED,
-    Backend backend = Backend::UNDEFINED,  // Is backend needed here?
-    DataLayout layout = DataLayout::UNDEFINED) {
-  auto out_meta = CreateLikeInferMeta(x.meta(), dtype, layout);
-  pten::DenseTensor dense_out(
-      pten::make_intrusive<paddle::experimental::SharedStorage>(
-          dev_ctx.GetPlace()),
-      std::move(out_meta));
-  FullLike<T, ContextT>(dev_ctx, val, &dense_out);
-  return dense_out;
-}
-
-}  // namespace pten

paddle/pten/kernels/cpu/full_kernel.cc

@@ -21,7 +21,7 @@ limitations under the License. */
 PT_REGISTER_CTX_KERNEL(full,
                        CPU,
                        ALL_LAYOUT,
-                       pten::Full,
+                       pten::FullKernel,
                        float,
                        double,
                        uint8_t,
@@ -37,7 +37,7 @@ PT_REGISTER_CTX_KERNEL(full,
 PT_REGISTER_CTX_KERNEL(full_like,
                        CPU,
                        ALL_LAYOUT,
-                       pten::FullLike,
+                       pten::FullLikeKernel,
                        float,
                        double,
                        int,

paddle/pten/kernels/full_kernel.h

@@ -18,15 +18,47 @@
 #include "paddle/pten/common/scalar_array.h"
 #include "paddle/pten/core/dense_tensor.h"
 
+#include "paddle/pten/infermeta/nullary.h"
+#include "paddle/pten/kernels/empty_kernel.h"
+
 namespace pten {
 
 template <typename T, typename Context>
-void Full(const Context& dev_ctx,
-          const ScalarArray& shape,
-          const Scalar& val,
-          DenseTensor* out);
+void FullKernel(const Context& dev_ctx,
+                const ScalarArray& shape,
+                const Scalar& val,
+                DenseTensor* out);
+
+template <typename T, typename Context>
+void FullLikeKernel(const Context& dev_ctx,
+                    const Scalar& val,
+                    DenseTensor* out);
+
+template <typename T, typename Context>
+DenseTensor Full(const Context& dev_ctx,
+                 const ScalarArray& shape,
+                 const Scalar& val,
+                 DataType dtype = DataType::FLOAT32,
+                 Backend backend = Backend::CPU,  // Is backend needed here?
+                 DataLayout layout = DataLayout::NCHW) {
+  auto out_meta = CreateInferMeta(shape, dtype, layout);
+  auto dense_out = Empty<T, Context>(dev_ctx, std::move(out_meta));
+  FullKernel<T, Context>(dev_ctx, shape, val, &dense_out);
+  return dense_out;
+}
 
 template <typename T, typename Context>
-void FullLike(const Context& dev_ctx, const Scalar& val, DenseTensor* out);
+DenseTensor FullLike(
+    const Context& dev_ctx,
+    const DenseTensor& x,
+    const Scalar& val,
+    DataType dtype = DataType::UNDEFINED,
+    Backend backend = Backend::UNDEFINED,  // Is backend needed here?
+    DataLayout layout = DataLayout::UNDEFINED) {
+  auto out_meta = CreateLikeInferMeta(x.meta(), dtype, layout);
+  auto dense_out = Empty<T, Context>(dev_ctx, std::move(out_meta));
+  FullLikeKernel<T, Context>(dev_ctx, val, &dense_out);
+  return dense_out;
+}
 
 }  // namespace pten

paddle/pten/kernels/gpu/full_kernel.cu

@@ -21,7 +21,7 @@ limitations under the License. */
 PT_REGISTER_CTX_KERNEL(full,
                        GPU,
                        ALL_LAYOUT,
-                       pten::Full,
+                       pten::FullKernel,
                        float,
                        double,
                        uint8_t,
@@ -36,7 +36,7 @@ PT_REGISTER_CTX_KERNEL(full,
 PT_REGISTER_CTX_KERNEL(full_like,
                        GPU,
                        ALL_LAYOUT,
-                       pten::FullLike,
+                       pten::FullLikeKernel,
                        float,
                        double,
                        int,

paddle/pten/kernels/impl/full_kernel_impl.h

@@ -24,7 +24,7 @@ limitations under the License. */
 
 namespace pten {
 
-template <typename Context, typename T, typename VType>
+template <typename T, typename Context, typename VType>
 void FullValue(const Context& dev_ctx, DenseTensor* tensor, VType val) {
   tensor->mutable_data<T>();
   auto t = pten::EigenVector<T>::Flatten(*tensor);
@@ -32,16 +32,18 @@ void FullValue(const Context& dev_ctx, DenseTensor* tensor, VType val) {
 }
 
 template <typename T, typename Context>
-void Full(const Context& dev_ctx,
-          const ScalarArray& shape,
-          const Scalar& val,
-          DenseTensor* out) {
+void FullKernel(const Context& dev_ctx,
+                const ScalarArray& shape,
+                const Scalar& val,
+                DenseTensor* out) {
   out->Resize(paddle::framework::make_ddim(shape.GetData()));
-  FullValue<Context, T>(dev_ctx, out, val.to<T>());
+  FullValue<T>(dev_ctx, out, val.to<T>());
 }
 
 template <typename T, typename Context>
-void FullLike(const Context& dev_ctx, const Scalar& val, DenseTensor* out) {
+void FullLikeKernel(const Context& dev_ctx,
+                    const Scalar& val,
+                    DenseTensor* out) {
   auto value = val.to<float>();
   using CommonType = typename std::common_type<
       float,
@@ -66,7 +68,7 @@ void FullLike(const Context& dev_ctx, const Scalar& val, DenseTensor* out) {
           static_cast<CommonType>(std::numeric_limits<T>::lowest()),
           static_cast<CommonType>(std::numeric_limits<T>::max()),
           static_cast<float>(value)));
-  FullValue<Context, T>(dev_ctx, out, value);
+  FullValue<T>(dev_ctx, out, value);
 }
 
 }  // namespace pten

paddle/pten/tests/kernels/test_creation_dev_api.cc

@@ -15,7 +15,8 @@ limitations under the License. */
 #include <gtest/gtest.h>
 #include <memory>
 
-#include "paddle/pten/include/creation.h"
+#include "paddle/pten/kernels/empty_kernel.h"
+#include "paddle/pten/kernels/full_kernel.h"
 
 #include "paddle/pten/api/lib/utils/allocator.h"
 #include "paddle/pten/core/dense_tensor.h"