[PHI] Code auto-generate for Sparse API (#40060)

* suppport sparse api in yaml

* support auto-gen code of sparse api

* do some refactor

* add unittest test_sparse_conv_api

* add unitest file
Co-authored-by: Nzkh2016 <zhangkaihuo@baidu.com>

.gitignore

@@ -7,9 +7,11 @@ paddle/fluid/op_use_default_grad_maker_DEV.spec
 paddle/fluid/op_use_default_grad_maker_PR.spec
 paddle/phi/api/backward/backward_api.h
 paddle/phi/api/include/api.h
+paddle/phi/api/include/sparse_api.h
 paddle/phi/api/lib/api.cc
 paddle/phi/api/lib/dygraph_api.*
 paddle/phi/api/lib/backward_api.cc
+paddle/phi/api/lib/sparse_api.cc
 paddle/phi/extension.h
 paddle/phi/include/*
 paddle/phi/infermeta/generated.*

paddle/phi/api/lib/CMakeLists.txt

@@ -32,6 +32,14 @@ set(bw_api_source_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/lib/backward_api.cc)
 set(bw_api_header_file_tmp ${bw_api_header_file}.tmp)
 set(bw_api_source_file_tmp ${bw_api_source_file}.tmp)
 
+# sparse api file
+set(sparse_api_gen_file ${CMAKE_SOURCE_DIR}/python/paddle/utils/code_gen/sparse_api_gen.py)
+set(sparse_api_yaml_file ${CMAKE_SOURCE_DIR}/python/paddle/utils/code_gen/sparse_api.yaml)
+set(sparse_api_header_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/include/sparse_api.h)
+set(sparse_api_source_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/lib/sparse_api.cc)
+set(sparse_api_header_file_tmp ${api_header_file}.tmp)
+set(sparse_api_source_file_tmp ${api_source_file}.tmp)
+
 # wrapped infermeta file
 set(wrapped_infermeta_gen_file ${CMAKE_SOURCE_DIR}/python/paddle/utils/code_gen/wrapped_infermeta_gen.py)
 set(api_yaml_file ${CMAKE_SOURCE_DIR}/python/paddle/utils/code_gen/api.yaml)
@@ -73,6 +81,19 @@ add_custom_command(
   DEPENDS ${bw_api_yaml_file} ${bw_api_gen_file} ${api_gen_base}
   VERBATIM)
 
+# generate sparse api
+add_custom_command(
+  OUTPUT ${sparse_api_header_file} ${sparse_api_source_file}
+  COMMAND ${PYTHON_EXECUTABLE} ${sparse_api_gen_file}
+                 --api_yaml_path ${sparse_api_yaml_file}
+                 --api_header_path ${sparse_api_header_file_tmp}
+                 --api_source_path ${sparse_api_source_file_tmp}
+  COMMAND ${CMAKE_COMMAND} -E copy_if_different ${sparse_api_header_file_tmp} ${sparse_api_header_file}
+  COMMAND ${CMAKE_COMMAND} -E copy_if_different ${sparse_api_source_file_tmp} ${sparse_api_source_file}
+  COMMENT "copy_if_different ${sparse_api_header_file} ${sparse_sparse_api_source_file}"
+  DEPENDS ${sparse_api_yaml_file} ${sparse_api_gen_file} ${api_gen_base}
+  VERBATIM)
+
 # generate wrapped infermeta
 add_custom_command(
   OUTPUT ${wrapped_infermeta_header_file} ${wrapped_infermeta_source_file}
@@ -87,12 +108,14 @@ cc_library(op_meta_info SRCS op_meta_info.cc DEPS phi_tensor_raw)
 cc_library(wrapped_infermeta SRCS ${wrapped_infermeta_source_file} DEPS phi)
 
 cc_library(kernel_dispatch SRCS kernel_dispatch.cc DEPS phi_tensor_raw phi_context kernel_factory)
+cc_library(api_gen_utils SRCS api_gen_utils.cc DEPS phi_tensor_raw selected_rows sparse_csr_tensor sparse_coo_tensor)
 cc_library(phi_data_transform SRCS data_transform.cc DEPS phi_tensor_raw transfer_layout_kernel cast_kernel data_device_transform)
-cc_library(api_custom_impl SRCS api_custom_impl.cc DEPS phi_tensor_raw phi kernel_dispatch phi_data_transform)
+cc_library(api_custom_impl SRCS api_custom_impl.cc DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils phi_data_transform)
+cc_library(sparse_api_custom_impl SRCS sparse_api_custom_impl.cc DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils phi_data_transform)
 
-cc_library(sparse_api SRCS sparse_api.cc DEPS phi_tensor_raw phi kernel_dispatch phi_data_transform)
-cc_library(phi_function_api SRCS ${api_source_file} DEPS phi_tensor_raw phi kernel_dispatch phi_data_transform api_custom_impl)
-cc_library(phi_dygraph_api SRCS ${dygraph_api_source_file} DEPS phi_tensor_raw phi kernel_dispatch phi_data_transform)
-cc_library(phi_bw_function_api SRCS ${bw_api_source_file} DEPS phi_tensor_raw phi kernel_dispatch backward_infermeta phi_data_transform phi_function_api api_custom_impl)
+cc_library(sparse_api SRCS sparse_api.cc DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils sparse_api_custom_impl)
+cc_library(phi_function_api SRCS ${api_source_file} DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils phi_data_transform api_custom_impl)
+cc_library(phi_dygraph_api SRCS ${dygraph_api_source_file} DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils phi_data_transform)
+cc_library(phi_bw_function_api SRCS ${bw_api_source_file} DEPS phi_tensor_raw phi kernel_dispatch api_gen_utils backward_infermeta phi_data_transform phi_function_api api_custom_impl)
 
 cc_library(phi_tensor SRCS tensor_method.cc DEPS phi_tensor_raw phi_function_api)

paddle/phi/api/lib/api_custom_impl.cc

@@ -14,8 +14,8 @@ limitations under the License. */
 
 #include "paddle/phi/api/lib/api_custom_impl.h"
 
+#include "paddle/phi/api/lib/api_gen_utils.h"
 #include "paddle/phi/api/lib/api_registry.h"
-#include "paddle/phi/api/lib/api_utils.h"
 #include "paddle/phi/api/lib/data_transform.h"
 #include "paddle/phi/api/lib/kernel_dispatch.h"
 #include "paddle/phi/api/lib/utils/storage.h"

paddle/phi/api/lib/api_utils.h → paddle/phi/api/lib/api_gen_utils.cc

@@ -12,26 +12,18 @@ 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/phi/api/include/tensor.h"
-#include "paddle/phi/api/lib/utils/storage.h"
-#include "paddle/phi/core/compat/convert_utils.h"
-#include "paddle/phi/core/dense_tensor.h"
-#include "paddle/phi/core/meta_tensor.h"
-#include "paddle/phi/core/selected_rows.h"
+#include "paddle/phi/api/lib/api_gen_utils.h"
 
 namespace paddle {
 namespace experimental {
 
 /* ------------------ for input ----------------------- */
 
-inline std::shared_ptr<phi::DenseTensor> TensorToDenseTensor(
-    const Tensor& tensor) {
+std::shared_ptr<phi::DenseTensor> TensorToDenseTensor(const Tensor& tensor) {
   return std::dynamic_pointer_cast<phi::DenseTensor>(tensor.impl());
 }
 
-inline std::shared_ptr<phi::DenseTensor> TensorToDenseTensor(
+std::shared_ptr<phi::DenseTensor> TensorToDenseTensor(
     const paddle::optional<Tensor>& tensor) {
   if (tensor) {
     return std::dynamic_pointer_cast<phi::DenseTensor>(tensor->impl());
@@ -39,7 +31,7 @@ inline std::shared_ptr<phi::DenseTensor> TensorToDenseTensor(
   return nullptr;
 }
 
-inline std::unique_ptr<std::vector<phi::DenseTensor>> TensorToDenseTensor(
+std::unique_ptr<std::vector<phi::DenseTensor>> TensorToDenseTensor(
     const std::vector<Tensor>& tensors) {
   auto pt_tensors = std::make_unique<std::vector<phi::DenseTensor>>();
   pt_tensors->reserve(tensors.size());
@@ -52,12 +44,11 @@ inline std::unique_ptr<std::vector<phi::DenseTensor>> TensorToDenseTensor(
   return std::move(pt_tensors);
 }
 
-inline std::shared_ptr<phi::SelectedRows> TensorToSelectedRows(
-    const Tensor& tensor) {
+std::shared_ptr<phi::SelectedRows> TensorToSelectedRows(const Tensor& tensor) {
   return std::dynamic_pointer_cast<phi::SelectedRows>(tensor.impl());
 }
 
-inline std::shared_ptr<phi::SelectedRows> TensorToSelectedRows(
+std::shared_ptr<phi::SelectedRows> TensorToSelectedRows(
     const paddle::optional<Tensor>& tensor) {
   if (tensor) {
     return std::dynamic_pointer_cast<phi::SelectedRows>(tensor->impl());
@@ -67,11 +58,11 @@ inline std::shared_ptr<phi::SelectedRows> TensorToSelectedRows(
 
 /* ----------------- for infer_meta --------------------- */
 
-inline phi::MetaTensor MakeMetaTensor(const phi::DenseTensor& tensor) {
+phi::MetaTensor MakeMetaTensor(const phi::DenseTensor& tensor) {
   return phi::MetaTensor(tensor);
 }
 
-inline paddle::optional<phi::MetaTensor> MakeMetaTensor(
+paddle::optional<phi::MetaTensor> MakeMetaTensor(
     const paddle::optional<const phi::DenseTensor&>& tensor) {
   if (tensor) {
     return {phi::MetaTensor(*tensor)};
@@ -79,7 +70,7 @@ inline paddle::optional<phi::MetaTensor> MakeMetaTensor(
   return {paddle::none};
 }
 
-inline std::vector<phi::MetaTensor> MakeMetaTensor(
+std::vector<phi::MetaTensor> MakeMetaTensor(
     const std::vector<phi::DenseTensor>& tensors) {
   std::vector<phi::MetaTensor> meta_tensors;
   meta_tensors.reserve(tensors.size());
@@ -89,11 +80,11 @@ inline std::vector<phi::MetaTensor> MakeMetaTensor(
   return meta_tensors;
 }
 
-inline phi::MetaTensor MakeMetaTensor(const phi::SelectedRows& tensor) {
+phi::MetaTensor MakeMetaTensor(const phi::SelectedRows& tensor) {
   return phi::MetaTensor(tensor);
 }
 
-inline paddle::optional<phi::MetaTensor> MakeMetaTensor(
+paddle::optional<phi::MetaTensor> MakeMetaTensor(
     const paddle::optional<const phi::SelectedRows&>& tensor) {
   if (tensor) {
     return {phi::MetaTensor(*tensor)};
@@ -103,7 +94,7 @@ inline paddle::optional<phi::MetaTensor> MakeMetaTensor(
 
 /* ------------------ for output ----------------------- */
 
-inline phi::DenseTensor* SetKernelOutput(Backend backend, Tensor* out) {
+phi::DenseTensor* SetKernelOutput(Backend backend, Tensor* out) {
   if (!out->initialized()) {
     auto dense_tensor = std::make_shared<phi::DenseTensor>(
         phi::make_intrusive<SharedStorage>(phi::TransToPhiPlace(backend)),
@@ -114,8 +105,9 @@ inline phi::DenseTensor* SetKernelOutput(Backend backend, Tensor* out) {
   return static_cast<phi::DenseTensor*>(out->impl().get());
 }
 
-inline std::vector<phi::DenseTensor*> SetKernelOutput(
-    size_t out_size, Backend backend, std::vector<Tensor>* out) {
+std::vector<phi::DenseTensor*> SetKernelOutput(size_t out_size,
+                                               Backend backend,
+                                               std::vector<Tensor>* out) {
   out->reserve(out_size);
   std::vector<phi::DenseTensor*> results(out_size);
   for (size_t i = 0; i < out_size; ++i) {
@@ -129,8 +121,7 @@ inline std::vector<phi::DenseTensor*> SetKernelOutput(
   return results;
 }
 
-inline phi::SelectedRows* SetSelectedRowsKernelOutput(Backend backend,
-                                                      Tensor* out) {
+phi::SelectedRows* SetSelectedRowsKernelOutput(Backend backend, Tensor* out) {
   if (!out->initialized()) {
     auto select_rows = std::make_shared<phi::SelectedRows>();
     out->set_impl(select_rows);
@@ -139,5 +130,29 @@ inline phi::SelectedRows* SetSelectedRowsKernelOutput(Backend backend,
   return static_cast<phi::SelectedRows*>(out->impl().get());
 }
 
+phi::TensorBase* SetSparseKernelOutput(Tensor* out, TensorType type) {
+  if (!out->initialized()) {
+    if (type == TensorType::SPARSE_COO) {
+      auto sparse_tensor = std::make_shared<phi::SparseCooTensor>(
+          phi::DenseTensor(), phi::DenseTensor(), phi::DDim{-1});
+      out->set_impl(sparse_tensor);
+      return sparse_tensor.get();
+    } else if (type == TensorType::SPARSE_CSR) {
+      auto sparse_tensor =
+          std::make_shared<phi::SparseCsrTensor>(phi::DenseTensor(),
+                                                 phi::DenseTensor(),
+                                                 phi::DenseTensor(),
+                                                 phi::DDim{-1});
+      out->set_impl(sparse_tensor);
+      return sparse_tensor.get();
+    } else {
+      auto dense_tensor = std::make_shared<phi::DenseTensor>();
+      out->set_impl(dense_tensor);
+      return dense_tensor.get();
+    }
+  }
+  return out->impl().get();
+}
+
 }  // namespace experimental
 }  // namespace paddle

paddle/phi/api/lib/api_gen_utils.h

+/* Copyright (c) 2022 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/phi/api/include/tensor.h"
+#include "paddle/phi/api/lib/utils/storage.h"
+#include "paddle/phi/core/compat/convert_utils.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/meta_tensor.h"
+#include "paddle/phi/core/selected_rows.h"
+#include "paddle/phi/core/sparse_coo_tensor.h"
+#include "paddle/phi/core/sparse_csr_tensor.h"
+
+namespace paddle {
+namespace experimental {
+
+enum class TensorType { DENSE_TENSOR, SPARSE_CSR, SPARSE_COO };
+
+/* ------------------ for input ----------------------- */
+
+std::shared_ptr<phi::DenseTensor> TensorToDenseTensor(const Tensor& tensor);
+
+std::shared_ptr<phi::DenseTensor> TensorToDenseTensor(
+    const paddle::optional<Tensor>& tensor);
+
+std::unique_ptr<std::vector<phi::DenseTensor>> TensorToDenseTensor(
+    const std::vector<Tensor>& tensors);
+
+std::shared_ptr<phi::SelectedRows> TensorToSelectedRows(const Tensor& tensor);
+
+std::shared_ptr<phi::SelectedRows> TensorToSelectedRows(
+    const paddle::optional<Tensor>& tensor);
+
+/* ----------------- for infer_meta --------------------- */
+
+phi::MetaTensor MakeMetaTensor(const phi::DenseTensor& tensor);
+
+paddle::optional<phi::MetaTensor> MakeMetaTensor(
+    const paddle::optional<const phi::DenseTensor&>& tensor);
+
+std::vector<phi::MetaTensor> MakeMetaTensor(
+    const std::vector<phi::DenseTensor>& tensors);
+
+phi::MetaTensor MakeMetaTensor(const phi::SelectedRows& tensor);
+
+paddle::optional<phi::MetaTensor> MakeMetaTensor(
+    const paddle::optional<const phi::SelectedRows&>& tensor);
+
+/* ------------------ for output ----------------------- */
+
+phi::DenseTensor* SetKernelOutput(Backend backend, Tensor* out);
+
+std::vector<phi::DenseTensor*> SetKernelOutput(size_t out_size,
+                                               Backend backend,
+                                               std::vector<Tensor>* out);
+
+phi::SelectedRows* SetSelectedRowsKernelOutput(Backend backend, Tensor* out);
+
+phi::TensorBase* SetSparseKernelOutput(Tensor* out, TensorType type);
+
+}  // namespace experimental
+}  // namespace paddle

paddle/phi/api/lib/sparse_api.cc → paddle/phi/api/lib/sparse_api_custom_impl.cc

@@ -12,7 +12,7 @@ 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. */
 
-#include "paddle/phi/api/include/sparse_api.h"
+#include "paddle/phi/api/lib/sparse_api_custom_impl.h"
 
 #include <memory>
 #include "glog/logging.h"
@@ -20,31 +20,14 @@ limitations under the License. */
 #include "paddle/phi/api/lib/kernel_dispatch.h"
 #include "paddle/phi/api/lib/utils/storage.h"
 #include "paddle/phi/core/kernel_registry.h"
-#include "paddle/phi/infermeta/unary.h"
-
-PD_DECLARE_KERNEL(dense_to_sparse_coo, CPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(sparse_csr_to_coo, CPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(dense_to_sparse_csr, CPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(sparse_coo_to_csr, CPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(sparse_coo_to_dense, CPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(sparse_csr_to_dense, CPU, ALL_LAYOUT);
-
-#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
-PD_DECLARE_KERNEL(dense_to_sparse_coo, GPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(sparse_csr_to_coo, GPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(dense_to_sparse_csr, GPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(sparse_coo_to_csr, GPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(sparse_coo_to_dense, GPU, ALL_LAYOUT);
-PD_DECLARE_KERNEL(sparse_csr_to_dense, GPU, ALL_LAYOUT);
-#endif
 
 namespace paddle {
 namespace experimental {
 namespace sparse {
 
-PADDLE_API Tensor to_sparse_coo(const Tensor& x,
-                                Backend backend,
-                                const int64_t sparse_dim) {
+Tensor to_sparse_coo_impl(const Tensor& x,
+                          Backend backend,
+                          const int64_t sparse_dim) {
   if (x.layout() == phi::DataLayout::SPARSE_COO) {
     return x;
   }
@@ -105,7 +88,7 @@ PADDLE_API Tensor to_sparse_coo(const Tensor& x,
   return out;
 }
 
-PADDLE_API Tensor to_sparse_csr(const Tensor& x, Backend backend) {
+Tensor to_sparse_csr_impl(const Tensor& x, Backend backend) {
   if (x.layout() == phi::DataLayout::SPARSE_CSR) {
     return x;
   }
@@ -171,7 +154,7 @@ PADDLE_API Tensor to_sparse_csr(const Tensor& x, Backend backend) {
   return out;
 }
 
-PADDLE_API Tensor to_dense(const Tensor& x, Backend backend) {
+Tensor to_dense_impl(const Tensor& x, Backend backend) {
   if (x.layout() != phi::DataLayout::SPARSE_CSR &&
       x.layout() != phi::DataLayout::SPARSE_COO) {
     return x;

paddle/phi/api/include/sparse_api.h → paddle/phi/api/lib/sparse_api_custom_impl.h

@@ -21,13 +21,13 @@ namespace paddle {
 namespace experimental {
 namespace sparse {
 
-PADDLE_API Tensor to_sparse_coo(const Tensor& x,
-                                Backend backend,
-                                const int64_t sparse_dim);
+Tensor to_dense_impl(const Tensor& x, Backend backend);
 
-PADDLE_API Tensor to_sparse_csr(const Tensor& x, Backend backend);
+Tensor to_sparse_coo_impl(const Tensor& x,
+                          Backend backend,
+                          const int64_t sparse_dim);
 
-PADDLE_API Tensor to_dense(const Tensor& x, Backend backend);
+Tensor to_sparse_csr_impl(const Tensor& x, Backend backend);
 
 }  // namespace sparse
 }  // namespace experimental

paddle/phi/kernels/sparse/cpu/convolution.h

@@ -107,7 +107,9 @@ void ProductRuleBook(const Context& dev_ctx,
 
   f_calc_rulebook(nullptr);
   // alloc the rulebook
-  rulebook->ResizeAndAllocate({3, rulebook_len});
+  DenseTensorMeta rulebook_meta(
+      DataType::INT32, {3, rulebook_len}, DataLayout::NCHW);
+  rulebook->set_meta(rulebook_meta);
   dev_ctx.Alloc(rulebook, rulebook->dtype(), rulebook->numel() * sizeof(int));
   int* rulebook_ptr = rulebook->data<int>();
   f_calc_rulebook(rulebook_ptr);

paddle/phi/tests/api/CMakeLists.txt

@@ -25,3 +25,4 @@ cc_test(test_concat_api SRCS test_concat_api.cc DEPS phi_tensor phi_api phi_api_
 cc_test(test_split_api SRCS test_split_api.cc DEPS phi_tensor phi_api phi_api_utils)
 cc_test(test_data_transform SRCS test_data_transform.cc DEPS phi_tensor phi_api phi_api_utils)
 cc_test(test_sparse_utils_api SRCS test_sparse_utils_api.cc DEPS phi_tensor phi_api phi_api_utils)
+cc_test(test_sparse_conv_api SRCS test_sparse_conv_api.cc DEPS phi_tensor phi_api phi_api_utils)

paddle/phi/tests/api/test_sparse_conv_api.cc

+/* Copyright (c) 2022 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. */
+
+#include <gtest/gtest.h>
+#include <memory>
+
+#include "paddle/phi/api/include/api.h"
+
+#include "paddle/phi/api/include/sparse_api.h"
+
+#include "paddle/phi/api/lib/utils/allocator.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/sparse_coo_tensor.h"
+
+template <typename T>
+void TestConv3dBase(const std::vector<int>& indices,
+                    const std::vector<T>& features,
+                    const phi::DDim& x_dims,
+                    const std::vector<T>& kernel,
+                    const phi::DDim& kernel_dims,
+                    const std::vector<int>& correct_out_indices,
+                    const std::vector<T>& correct_out_features,
+                    const phi::DDim& correct_out_dims,
+                    const int non_zero_num,
+                    const std::vector<int>& paddings,
+                    const std::vector<int>& strides,
+                    const std::vector<int>& dilations,
+                    const float diff = 1e-3) {
+  const auto alloc = std::make_unique<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+
+  const int in_channels = kernel_dims[3];
+  const int out_channels = kernel_dims[4];
+
+  phi::DenseTensor indices_tensor(
+      alloc.get(),
+      phi::DenseTensorMeta(
+          phi::DataType::INT32, {4, non_zero_num}, phi::DataLayout::NCHW));
+  memcpy(
+      indices_tensor.data<int>(), indices.data(), indices.size() * sizeof(int));
+
+  phi::DenseTensor features_tensor(
+      alloc.get(),
+      phi::DenseTensorMeta(paddle::experimental::CppTypeToDataType<T>::Type(),
+                           {non_zero_num, in_channels},
+                           phi::DataLayout::NHWC));
+  memcpy(
+      features_tensor.data<T>(), features.data(), features.size() * sizeof(T));
+
+  auto x_tensor = std::make_shared<phi::SparseCooTensor>(
+      indices_tensor, features_tensor, x_dims);
+  paddle::experimental::Tensor x(x_tensor);
+
+  auto kernel_tensor = std::make_shared<phi::DenseTensor>(
+      alloc.get(),
+      phi::DenseTensorMeta(paddle::experimental::CppTypeToDataType<T>::Type(),
+                           kernel_dims,
+                           phi::DataLayout::NHWC));
+  paddle::experimental::Tensor weight(kernel_tensor);
+
+  memcpy(kernel_tensor->mutable_data<T>(paddle::platform::CPUPlace()),
+         kernel.data(),
+         kernel.size() * sizeof(T));
+
+  if (!std::is_same<T, phi::dtype::float16>::value) {
+    auto outs = paddle::experimental::sparse::conv3d(
+        x, weight, paddings, dilations, strides, 1);
+
+    auto out = std::dynamic_pointer_cast<phi::SparseCooTensor>(
+        std::get<0>(outs).impl());
+    ASSERT_EQ(correct_out_dims.size(), out->dims().size());
+    for (int i = 0; i < correct_out_dims.size(); i++) {
+      ASSERT_EQ(correct_out_dims[i], out->dims()[i]);
+    }
+    ASSERT_EQ((int64_t)correct_out_features.size() / out_channels, out->nnz());
+
+    int cmp_indices = memcmp(correct_out_indices.data(),
+                             out->non_zero_indices().data<int>(),
+                             correct_out_indices.size() * sizeof(int));
+    ASSERT_EQ(cmp_indices, 0);
+
+    for (uint64_t i = 0; i < correct_out_features.size(); i++) {
+      float tmp = std::fabs(static_cast<float>(
+          correct_out_features[i] - out->non_zero_elements().data<T>()[i]));
+      ASSERT_LT(tmp, diff);
+    }
+  }
+}
+
+void TestConv3d(const std::vector<int>& indices,
+                const std::vector<float>& features,
+                const phi::DDim& x_dims,
+                const std::vector<float>& kernel,
+                const phi::DDim& kernel_dims,
+                const std::vector<int>& correct_out_indices,
+                const std::vector<float>& correct_out_features,
+                const phi::DDim& correct_out_dims,
+                const int non_zero_num,
+                const std::vector<int>& paddings,
+                const std::vector<int>& strides,
+                const std::vector<int>& dilations) {
+  // test float
+  TestConv3dBase<float>(indices,
+                        features,
+                        x_dims,
+                        kernel,
+                        kernel_dims,
+                        correct_out_indices,
+                        correct_out_features,
+                        correct_out_dims,
+                        non_zero_num,
+                        paddings,
+                        strides,
+                        dilations);
+}
+
+TEST(API, sparse_conv2d) {
+  const auto alloc = std::make_shared<paddle::experimental::DefaultAllocator>(
+      paddle::platform::CPUPlace());
+  const int in_channels = 1;
+  const int out_channels = 1;
+  phi::DDim x_dims = {1, 1, 5, 5, in_channels};
+  phi::DDim kernel_dims = {1, 3, 3, in_channels, out_channels};
+  phi::DDim out_dims = {1, 1, 3, 3, out_channels};
+  std::vector<int> paddings = {0, 0, 0};
+  std::vector<int> strides = {1, 1, 1};
+  std::vector<int> dilations = {1, 1, 1};
+
+  const int non_zero_num = 3;
+  std::vector<int> indices_flatten = {0, 0, 0, 0, 0, 0, 0, 4, 0, 3, 2, 4};
+
+  std::vector<float> features = {-0.79394531, -0.3125, -0.55029297};
+  // 3*3*3=27
+  std::vector<float> kernel = {0.65820312,
+                               0.75048828,
+                               0.21411133,
+                               0.17370605,
+                               0.85546875,
+                               0.53076172,
+                               0.28833008,
+                               0.71044922,
+                               0.00659943};
+
+  std::vector<int> out_indices_flatten = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                          0, 0, 2, 2, 2, 1, 2, 0, 1, 2};
+
+  std::vector<float> out_features = {
+      -0.17004, -0.71338, -0.00206, -0.22205, -0.09009};
+
+  TestConv3d(indices_flatten,
+             features,
+             x_dims,
+             kernel,
+             kernel_dims,
+             out_indices_flatten,
+             out_features,
+             out_dims,
+             non_zero_num,
+             paddings,
+             strides,
+             dilations);
+}

python/paddle/utils/code_gen/api_base.py

@@ -43,7 +43,9 @@ class BaseAPI(object):
             self.is_base_api = False
             self.invoke = api_item_yaml['invoke']
         else:
-            self.infer_meta = self.parse_infer_meta(api_item_yaml['infer_meta'])
+            if 'infer_meta' in api_item_yaml:
+                self.infer_meta = self.parse_infer_meta(api_item_yaml[
+                    'infer_meta'])
             self.kernel = self.parse_kernel(api_item_yaml['kernel'])
             self.support_selected_rows_kernel = False if len(self.kernel[
                 'func']) == 1 else True
@@ -182,9 +184,9 @@ class BaseAPI(object):
                 'Tensor': 'Tensor',
                 'Tensor[]': 'std::vector<Tensor>'
             }
-            if re.search(r'\(\w*\)', output_item):
+            if re.search(r'\([a-zA-Z0-9_@]*\)', output_item):
                 result = re.search(
-                    r"(?P<out_type>[a-zA-Z0-9_[\]]+)\s*\((?P<name>\w+)\)",
+                    r"(?P<out_type>[a-zA-Z0-9_[\]]+)\s*\((?P<name>[a-zA-Z0-9_@]+)\)",
                     output_item)
                 out_type = result.group('out_type')
                 assert out_type in output_type_map, \
@@ -499,11 +501,8 @@ PADDLE_API {self.outputs['return_type']} {self.get_api_func_name() + '_'}({self.
     def get_kernel_args(self, code_indent):
         input_trans_map = {
             'const Tensor&': 'const phi::DenseTensor&',
-            'const Tensor &': 'const phi::DenseTensor&',
             'const std::vector<Tensor>&':
             'const std::vector<phi::DenseTensor>&',
-            'const std::vector<Tensor> &':
-            'const std::vector<phi::DenseTensor>&',
             'const paddle::optional<Tensor>&':
             'paddle::optional<const phi::DenseTensor&>',
             'const paddle::optional<std::vector<Tensor>>&':
@@ -592,7 +591,6 @@ PADDLE_API {self.outputs['return_type']} {self.get_api_func_name() + '_'}({self.
     def get_selected_rows_kernel_args(self, code_indent):
         input_trans_map = {
             'const Tensor&': 'const phi::SelectedRows&',
-            'const Tensor &': 'const phi::SelectedRows&',
             'const paddle::optional<Tensor>&':
             'paddle::optional<const phi::SelectedRows&>'
         }

python/paddle/utils/code_gen/api_gen.py

@@ -105,7 +105,7 @@ def source_include(header_file_path):
 
 #include "paddle/phi/api/lib/api_custom_impl.h"
 #include "paddle/phi/api/lib/api_registry.h"
-#include "paddle/phi/api/lib/api_utils.h"
+#include "paddle/phi/api/lib/api_gen_utils.h"
 #include "paddle/phi/api/lib/data_transform.h"
 #include "paddle/phi/api/lib/kernel_dispatch.h"
 #include "paddle/phi/api/lib/utils/storage.h"

python/paddle/utils/code_gen/backward_api_gen.py

@@ -146,7 +146,7 @@ def source_include(header_file_path):
 
 #include "paddle/phi/api/lib/api_custom_impl.h"
 #include "paddle/phi/api/lib/api_registry.h"
-#include "paddle/phi/api/lib/api_utils.h"
+#include "paddle/phi/api/lib/api_gen_utils.h"
 #include "paddle/phi/api/lib/data_transform.h"
 #include "paddle/phi/api/lib/kernel_dispatch.h"
 #include "paddle/phi/api/lib/utils/storage.h"

python/paddle/utils/code_gen/sparse_api.yaml

+- sparse_api : conv3d
+  args : (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups)
+  output : Tensor(out@SparseCooTensor), Tensor(rulebook@DenseTensor)
+  kernel :
+    func : sparse_conv3d
+    layout : x
+
+- sparse_api : to_dense
+  args : (Tensor x, Backend backend)
+  output : Tensor(out@DenseTensor)
+  invoke : to_dense_impl(x, backend)
+
+- sparse_api : to_sparse_coo
+  args : (Tensor x, Backend backend, int64_t sparse_dim)
+  output : Tensor(out@SparseCooTensor)
+  invoke : to_sparse_coo_impl(x, backend, sparse_dim)
+
+- sparse_api : to_sparse_csr
+  args : (Tensor x, Backend backend)
+  output : Tensor(out@SparseCsrTensor)
+  invoke : to_sparse_csr_impl(x, backend)

python/paddle/utils/code_gen/sparse_api_gen.py

+# Copyright (c) 2022 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.
+
+import os
+import yaml
+import argparse
+import re
+
+from api_base import BaseAPI
+
+
+class SparseAPI(BaseAPI):
+    def __init__(self, api_item_yaml):
+        super(SparseAPI, self).__init__(api_item_yaml)
+
+    def get_api_name(self, api_item_yaml):
+        return api_item_yaml['sparse_api']
+
+    def get_api_func_name(self):
+        return self.api
+
+    def get_return_type(self, out_type_list):
+        return out_type_list[0] if len(
+            out_type_list) == 1 else "std::tuple<" + ",".join(
+                out_type_list) + ">"
+
+    def gene_api_declaration(self):
+        return f"""
+// {", ".join(self.outputs['names'])}
+PADDLE_API {self.outputs['return_type']} {self.get_api_func_name()}({self.args_str['args_declare']});
+"""
+
+    def get_kernel_tensor_out_type(self, output_name):
+        sparse_type = 'TensorType::DENSE_TENSOR'
+        if output_name.endswith('@SparseCooTensor'):
+            sparse_type = 'TensorType::SPARSE_COO'
+        elif output_name.endswith('@SparseCsrTensor'):
+            sparse_type = 'TensorType::SPARSE_CSR'
+        return sparse_type
+
+    def gene_output(self,
+                    output_type_list,
+                    set_out_func,
+                    code_indent,
+                    inplace_flag=False):
+        kernel_output = ""
+        output_names = []
+        output_create = ""
+
+        if len(output_type_list) == 1:
+            kernel_output = 'kernel_out'
+            output_names.append('kernel_out')
+            inplace_assign = " = " + self.inplace_map[self.outputs['names'][
+                0]] if inplace_flag and self.inplace_map is not None and self.outputs[
+                    'names'][0] in self.inplace_map else ""
+            output_create = f"""
+  {self.outputs['return_type']} out{inplace_assign};
+  auto* kernel_out = {set_out_func}(&out, {self.get_kernel_tensor_out_type(self.outputs['names'][0])});"""
+
+        elif len(output_type_list) > 1:
+            output_create = f"""
+  {self.outputs['return_type']} out;"""
+
+            for i in range(len(output_type_list)):
+                kernel_output = kernel_output + f'kernel_out_{i}, '
+                output_names.append(f'kernel_out_{i}')
+                if inplace_flag and self.inplace_map is not None and self.outputs[
+                        'names'][i] in self.inplace_map:
+                    output_create = output_create + f"""
+  std::get<{i}>(out) = {self.inplace_map[self.outputs['names'][i]]};"""
+
+                output_create = output_create + f"""
+  auto* kernel_out_{i} = {set_out_func}(&std::get<{i}>(out), {self.get_kernel_tensor_out_type(self.outputs['names'][i])});"""
+
+            kernel_output = kernel_output[:-2]
+        else:
+            raise ValueError(
+                "{} : Output error: the output should not be empty.".format(
+                    self.api))
+
+        return kernel_output, output_names, output_create
+
+    def gen_sparse_kernel_context(self, kernel_output_names):
+        input_trans_map = {
+            'const Tensor&': 'const phi::TenseBase&',
+            'const std::vector<Tensor>&': 'const std::vector<phi::TenseBase>&',
+            'const paddle::optional<Tensor>&':
+            'paddle::optional<const phi::TenseBase&>'
+        }
+        out_trans_map = {
+            'Tensor': 'phi::TenseBase*',
+            'std::vector<Tensor>': 'std::vector<phi::TenseBase*>'
+        }
+        input_names = self.inputs['names']
+        input_infos = self.inputs['input_info']
+
+        attr_names = self.attrs['names']
+        kernel_param = self.kernel['param']
+        if kernel_param is None:
+            kernel_param = input_names + attr_names
+
+        kernel_context_code = ""
+        for param in kernel_param:
+            if param in input_names:
+                if param in self.optional_vars:
+                    raise ValueError(
+                        f"{self.api} : Unsupport optional input({param}) for sparse api."
+                    )
+                else:
+                    kernel_context_code = kernel_context_code + f"""
+  kernel_context.EmplaceBackInput({param}.impl().get());"""
+
+                continue
+            if param in attr_names:
+                # set attr for kernel_context
+                if 'ScalarArray' in self.attrs['attr_info'][param][0]:
+                    param = 'phi::ScalarArray(' + param + ')'
+                elif 'Scalar' in self.attrs['attr_info'][param][0]:
+                    param = 'phi::Scalar(' + param + ')'
+            elif isinstance(param, bool):
+                param = str(param).lower()
+            else:
+                param + str(param) + ", "
+            kernel_context_code = kernel_context_code + f"""
+  kernel_context.EmplaceBackAttr({param});"""
+
+        for out_name in kernel_output_names:
+            kernel_context_code = kernel_context_code + f"""
+  kernel_context.EmplaceBackOutput({out_name});"""
+
+        return kernel_context_code
+
+    def gen_sparse_kernel_code(self, inplace_flag=False):
+        _, kernel_output_names, output_create = self.gene_output(
+            self.outputs['types'], 'SetSparseKernelOutput', '', inplace_flag)
+
+        kernel_context_code = self.gen_sparse_kernel_context(
+            kernel_output_names)
+
+        return f"""
+  auto phi_kernel = phi::KernelFactory::Instance().SelectKernelOrThrowError(
+      "{self.kernel['func'][0]}", {{kernel_backend, kernel_layout, kernel_data_type}});
+  VLOG(6) << "{self.api} api sparse kernel key: [" << kernel_backend << ", " << kernel_layout << ", "<< kernel_data_type << "]";
+  VLOG(6) << "{self.api} api sparse kernel: " << phi_kernel;
+
+  auto* dev_ctx = GetDeviceContextByBackend(kernel_backend);
+  auto kernel_context = phi::KernelContext(dev_ctx);
+{output_create}
+{kernel_context_code}
+  phi_kernel(&kernel_context);
+
+  return out;"""
+
+    def gene_base_api_code(self, inplace_flag=False):
+        api_func_name = self.get_api_func_name()
+        return f"""
+PADDLE_API {self.outputs['return_type']} {api_func_name}({self.args_str["args_define"]}) {{
+{self.gene_kernel_select()}
+{self.gen_sparse_kernel_code(inplace_flag)}
+}}
+"""
+
+
+def header_include():
+    return """
+#include <tuple>
+
+#include "paddle/phi/api/include/tensor.h"
+#include "paddle/phi/common/scalar.h"
+#include "paddle/phi/common/scalar_array.h"
+#include "paddle/utils/optional.h"
+"""
+
+
+def source_include(header_file_path):
+    return f"""
+#include "{header_file_path}"
+#include <memory>
+
+#include "glog/logging.h"
+
+#include "paddle/phi/api/lib/api_registry.h"
+#include "paddle/phi/api/lib/api_gen_utils.h"
+#include "paddle/phi/api/lib/data_transform.h"
+#include "paddle/phi/api/lib/kernel_dispatch.h"
+#include "paddle/phi/api/lib/sparse_api_custom_impl.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/declarations.h"
+"""
+
+
+def api_register():
+    return """
+PD_REGISTER_API(Test);
+"""
+
+
+def api_namespace():
+    return ("""
+namespace paddle {
+namespace experimental {
+namespace sparse {
+
+""", """
+
+}  // namespace sparse
+}  // namespace experimental
+}  // namespace paddle
+""")
+
+
+def generate_api(api_yaml_path, header_file_path, source_file_path):
+
+    with open(api_yaml_path, 'r') as f:
+        apis = yaml.load(f, Loader=yaml.FullLoader)
+    header_file = open(header_file_path, 'w')
+    source_file = open(source_file_path, 'w')
+
+    namespace = api_namespace()
+
+    header_file.write("#pragma once\n")
+    header_file.write(header_include())
+    header_file.write(namespace[0])
+
+    include_header_file = "paddle/phi/api/include/sparse_api.h"
+    source_file.write(source_include(include_header_file))
+    source_file.write(namespace[0])
+
+    for api in apis:
+        sparse_api = SparseAPI(api)
+        header_file.write(sparse_api.gene_api_declaration())
+        source_file.write(sparse_api.gene_api_code())
+
+    header_file.write(namespace[1])
+    source_file.write(namespace[1])
+
+    source_file.write(api_register())
+
+    header_file.close()
+    source_file.close()
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description='Generate PaddlePaddle C++ Sparse API files')
+    parser.add_argument(
+        '--api_yaml_path',
+        help='path to sparse api yaml file',
+        default='python/paddle/utils/code_gen/sparse_api.yaml')
+
+    parser.add_argument(
+        '--api_header_path',
+        help='output of generated api header code file',
+        default='paddle/phi/api/include/sparse_api.h')
+
+    parser.add_argument(
+        '--api_source_path',
+        help='output of generated api source code file',
+        default='paddle/phi/api/lib/sparse_api.cc')
+
+    options = parser.parse_args()
+
+    api_yaml_path = options.api_yaml_path
+    header_file_path = options.api_header_path
+    source_file_path = options.api_source_path
+
+    generate_api(api_yaml_path, header_file_path, source_file_path)
+
+
+if __name__ == '__main__':
+    main()