Standard sparse conv name (#44353)

paddle/phi/api/yaml/sparse_api.yaml

@@ -84,7 +84,7 @@
   args : (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm)
   output : Tensor(out), Tensor(rulebook)
   kernel :
-    func : sparse_conv3d{sparse_coo, dense -> sparse_coo, dense}
+    func : conv3d_coo{sparse_coo, dense -> sparse_coo, dense}
     layout : x
   intermediate : rulebook
   backward : conv3d_grad

paddle/phi/api/yaml/sparse_bw_api.yaml

@@ -76,7 +76,7 @@
   args : (Tensor x, Tensor kernel, Tensor rulebook, Tensor out_grad, int[] paddings, int[] dilations, int[] strides, int groups, bool subm)
   output : Tensor(x_grad), Tensor(kernel_grad)
   kernel :
-    func : sparse_conv3d_grad{sparse_coo, dense, dense, sparse_coo -> sparse_coo, dense}
+    func : conv3d_coo_grad{sparse_coo, dense, dense, sparse_coo -> sparse_coo, dense}
 
 - backward_api : coo_to_dense_grad
   forward : coo_to_dense(Tensor x) -> Tensor(out)

paddle/phi/kernels/sparse/convolution_grad_kernel.h → paddle/phi/kernels/sparse/conv_grad_kernel.h

@@ -17,13 +17,12 @@ limitations under the License. */
 #include "paddle/phi/core/dense_tensor.h"
 #include "paddle/phi/core/sparse_coo_tensor.h"
 #include "paddle/phi/kernels/empty_kernel.h"
-#include "paddle/phi/kernels/sparse/convolution_kernel.h"
 
 namespace phi {
 namespace sparse {
 
 template <typename T, typename Context>
-void Conv3dGradKernel(const Context& dev_ctx,
+void Conv3dCooGradKernel(const Context& dev_ctx,
                          const SparseCooTensor& x,
                          const DenseTensor& kernel,
                          const DenseTensor& rulebook,
@@ -37,7 +36,7 @@ void Conv3dGradKernel(const Context& dev_ctx,
                          DenseTensor* kernel_grad);
 
 template <typename T, typename Context>
-std::tuple<SparseCooTensor, DenseTensor> Conv3dGrad(
+std::tuple<SparseCooTensor, DenseTensor> Conv3dCooGrad(
     const Context& dev_ctx,
     const SparseCooTensor& x,
     const DenseTensor& kernel,
@@ -52,7 +51,7 @@ std::tuple<SparseCooTensor, DenseTensor> Conv3dGrad(
   DenseTensor kernel_grad;
 
   // TODO(zhangkaihuo): call InferMeta func here
-  Conv3dGradKernel<T, Context>(dev_ctx,
+  Conv3dCooGradKernel<T, Context>(dev_ctx,
                                   x,
                                   kernel,
                                   rulebook,

paddle/phi/kernels/sparse/convolution_kernel.h → paddle/phi/kernels/sparse/conv_kernel.h

@@ -23,7 +23,7 @@ namespace phi {
 namespace sparse {
 
 template <typename T, typename Context>
-void Conv3dKernel(const Context& dev_ctx,
+void Conv3dCooKernel(const Context& dev_ctx,
                      const SparseCooTensor& x,
                      const DenseTensor& kernel,
                      const std::vector<int>& paddings,
@@ -35,7 +35,7 @@ void Conv3dKernel(const Context& dev_ctx,
                      DenseTensor* rulebook);
 
 template <typename T, typename Context>
-SparseCooTensor Conv3d(const Context& dev_ctx,
+SparseCooTensor Conv3dCoo(const Context& dev_ctx,
                           const SparseCooTensor& x,
                           const DenseTensor kernel,
                           const std::vector<int>& paddings,
@@ -45,7 +45,7 @@ SparseCooTensor Conv3d(const Context& dev_ctx,
                           const bool subm,
                           DenseTensor* rulebook) {
   SparseCooTensor coo;
-  Conv3dKernel<T, Context>(dev_ctx,
+  Conv3dCooKernel<T, Context>(dev_ctx,
                               x,
                               kernel,
                               paddings,

paddle/phi/kernels/sparse/cpu/convolution_grad_kernel.cc → paddle/phi/kernels/sparse/cpu/conv_grad_kernel.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/kernels/sparse/convolution_grad_kernel.h"
+#include "paddle/phi/kernels/sparse/conv_grad_kernel.h"
 
 #include "paddle/phi/core/visit_type.h"
 #include "paddle/phi/kernels/funcs/blas/blas.h"
@@ -31,7 +31,7 @@ namespace sparse {
 // x_grad = out_grad * transpose(kenrel)
 // kernel_grad = transpose(x) * out_grad
 template <typename T, typename IntT = int>
-void Conv3dGradCPUKernel(const CPUContext& dev_ctx,
+void Conv3dCooGradCPUKernel(const CPUContext& dev_ctx,
                             const SparseCooTensor& x,
                             const DenseTensor& kernel,
                             const DenseTensor& rulebook,
@@ -178,7 +178,7 @@ void Conv3dGradCPUKernel(const CPUContext& dev_ctx,
 }
 
 template <typename T, typename Context>
-void Conv3dGradKernel(const Context& dev_ctx,
+void Conv3dCooGradKernel(const Context& dev_ctx,
                          const SparseCooTensor& x,
                          const DenseTensor& kernel,
                          const DenseTensor& rulebook,
@@ -191,8 +191,8 @@ void Conv3dGradKernel(const Context& dev_ctx,
                          SparseCooTensor* x_grad,
                          DenseTensor* kernel_grad) {
   PD_VISIT_INTEGRAL_TYPES(
-      x.non_zero_indices().dtype(), "Conv3dGradCPUKernel", ([&] {
-        Conv3dGradCPUKernel<T, data_t>(dev_ctx,
+      x.non_zero_indices().dtype(), "Conv3dCooGradCPUKernel", ([&] {
+        Conv3dCooGradCPUKernel<T, data_t>(dev_ctx,
                                           x,
                                           kernel,
                                           rulebook,
@@ -210,10 +210,10 @@ void Conv3dGradKernel(const Context& dev_ctx,
 }  // namespace sparse
 }  // namespace phi
 
-PD_REGISTER_KERNEL(sparse_conv3d_grad,
+PD_REGISTER_KERNEL(conv3d_coo_grad,
                    CPU,
                    ALL_LAYOUT,
-                   phi::sparse::Conv3dGradKernel,
+                   phi::sparse::Conv3dCooGradKernel,
                    float,
                    double) {
   kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);

paddle/phi/kernels/sparse/cpu/convolution_kernel.cc → paddle/phi/kernels/sparse/cpu/conv_kernel.cc

@@ -27,7 +27,7 @@ namespace sparse {
  * out: (N, D, H, W, OC)
  **/
 template <typename T, typename IntT = int>
-void Conv3dCPUKernel(const CPUContext& dev_ctx,
+void Conv3dCooCPUKernel(const CPUContext& dev_ctx,
                         const SparseCooTensor& x,
                         const DenseTensor& kernel,
                         const std::vector<int>& paddings,
@@ -151,7 +151,7 @@ void Conv3dCPUKernel(const CPUContext& dev_ctx,
 }
 
 template <typename T, typename Context>
-void Conv3dKernel(const Context& dev_ctx,
+void Conv3dCooKernel(const Context& dev_ctx,
                      const SparseCooTensor& x,
                      const DenseTensor& kernel,
                      const std::vector<int>& paddings,
@@ -162,8 +162,8 @@ void Conv3dKernel(const Context& dev_ctx,
                      SparseCooTensor* out,
                      DenseTensor* rulebook) {
   PD_VISIT_INTEGRAL_TYPES(
-      x.non_zero_indices().dtype(), "Conv3dCPUKernel", ([&] {
-        Conv3dCPUKernel<T, data_t>(dev_ctx,
+      x.non_zero_indices().dtype(), "Conv3dCooCPUKernel", ([&] {
+        Conv3dCooCPUKernel<T, data_t>(dev_ctx,
                                       x,
                                       kernel,
                                       paddings,
@@ -180,6 +180,6 @@ void Conv3dKernel(const Context& dev_ctx,
 }  // namespace phi
 
 PD_REGISTER_KERNEL(
-    sparse_conv3d, CPU, ALL_LAYOUT, phi::sparse::Conv3dKernel, float, double) {
+    conv3d_coo, CPU, ALL_LAYOUT, phi::sparse::Conv3dCooKernel, float, double) {
   kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
 }

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

@@ -21,7 +21,7 @@ limitations under the License. */
 #include "paddle/phi/core/sparse_coo_tensor.h"
 #include "paddle/phi/core/tensor_meta.h"
 #include "paddle/phi/kernels/funcs/blas/blas.h"
-#include "paddle/phi/kernels/sparse/convolution_kernel.h"
+#include "paddle/phi/kernels/sparse/conv_kernel.h"
 
 namespace phi {
 namespace sparse {

paddle/phi/kernels/sparse/gpu/convolution_grad_kernel.cu → paddle/phi/kernels/sparse/gpu/conv_grad_kernel.cu

@@ -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/kernels/sparse/convolution_grad_kernel.h"
+#include "paddle/phi/kernels/sparse/conv_grad_kernel.h"
 
 #include "glog/logging.h"
 #include "paddle/phi/backends/gpu/gpu_context.h"
@@ -39,7 +39,7 @@ namespace sparse {
 // x_grad = out_grad * transpose(kenrel)
 // kernel_grad = transpose(x) * out_grad
 template <typename T, typename IntT>
-void Conv3dGradGPUKernel(const GPUContext& dev_ctx,
+void Conv3dCooGradGPUKernel(const GPUContext& dev_ctx,
                             const SparseCooTensor& x,
                             const DenseTensor& kernel,
                             const DenseTensor& rulebook,
@@ -220,7 +220,7 @@ void Conv3dGradGPUKernel(const GPUContext& dev_ctx,
 }
 
 template <typename T, typename Context>
-void Conv3dGradKernel(const Context& dev_ctx,
+void Conv3dCooGradKernel(const Context& dev_ctx,
                          const SparseCooTensor& x,
                          const DenseTensor& kernel,
                          const DenseTensor& rulebook,
@@ -233,8 +233,8 @@ void Conv3dGradKernel(const Context& dev_ctx,
                          SparseCooTensor* x_grad,
                          DenseTensor* kernel_grad) {
   PD_VISIT_INTEGRAL_TYPES(
-      x.non_zero_indices().dtype(), "Conv3dGradGPUKernel", ([&] {
-        Conv3dGradGPUKernel<T, data_t>(dev_ctx,
+      x.non_zero_indices().dtype(), "Conv3dCooGradGPUKernel", ([&] {
+        Conv3dCooGradGPUKernel<T, data_t>(dev_ctx,
                                           x,
                                           kernel,
                                           rulebook,
@@ -252,10 +252,10 @@ void Conv3dGradKernel(const Context& dev_ctx,
 }  // namespace sparse
 }  // namespace phi
 
-PD_REGISTER_KERNEL(sparse_conv3d_grad,
+PD_REGISTER_KERNEL(conv3d_coo_grad,
                    GPU,
                    ALL_LAYOUT,
-                   phi::sparse::Conv3dGradKernel,
+                   phi::sparse::Conv3dCooGradKernel,
                    float,
                    double,
                    phi::dtype::float16) {

paddle/phi/kernels/sparse/gpu/convolution_kernel.cu → paddle/phi/kernels/sparse/gpu/conv_kernel.cu

@@ -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/kernels/sparse/convolution_kernel.h"
+#include "paddle/phi/kernels/sparse/conv_kernel.h"
 
 #include "paddle/phi/backends/gpu/gpu_context.h"
 #include "paddle/phi/core/kernel_registry.h"
@@ -27,7 +27,7 @@ namespace phi {
 namespace sparse {
 
 template <typename T, typename IntT>
-void Conv3dGPUKernel(const GPUContext& dev_ctx,
+void Conv3dCooGPUKernel(const GPUContext& dev_ctx,
                         const SparseCooTensor& x,
                         const DenseTensor& kernel,
                         const std::vector<int>& paddings,
@@ -190,7 +190,7 @@ void Conv3dGPUKernel(const GPUContext& dev_ctx,
  * out: (N, D, H, W, OC)
  **/
 template <typename T, typename Context>
-void Conv3dKernel(const Context& dev_ctx,
+void Conv3dCooKernel(const Context& dev_ctx,
                      const SparseCooTensor& x,
                      const DenseTensor& kernel,
                      const std::vector<int>& paddings,
@@ -201,8 +201,8 @@ void Conv3dKernel(const Context& dev_ctx,
                      SparseCooTensor* out,
                      DenseTensor* rulebook) {
   PD_VISIT_INTEGRAL_TYPES(
-      x.non_zero_indices().dtype(), "Conv3dGPUKernel", ([&] {
-        Conv3dGPUKernel<T, data_t>(dev_ctx,
+      x.non_zero_indices().dtype(), "Conv3dCooGPUKernel", ([&] {
+        Conv3dCooGPUKernel<T, data_t>(dev_ctx,
                                       x,
                                       kernel,
                                       paddings,
@@ -218,10 +218,10 @@ void Conv3dKernel(const Context& dev_ctx,
 }  // namespace sparse
 }  // namespace phi
 
-PD_REGISTER_KERNEL(sparse_conv3d,
+PD_REGISTER_KERNEL(conv3d_coo,
                    GPU,
                    ALL_LAYOUT,
-                   phi::sparse::Conv3dKernel,
+                   phi::sparse::Conv3dCooKernel,
                    float,
                    double,
                    phi::dtype::float16) {

paddle/phi/kernels/sparse/gpu/convolution.cu.h

@@ -28,7 +28,7 @@ limitations under the License. */
 #include "paddle/phi/kernels/funcs/math_function.h"
 #include "paddle/phi/kernels/funcs/sparse/utils.cu.h"
 #include "paddle/phi/kernels/primitive/compute_primitives.h"
-#include "paddle/phi/kernels/sparse/convolution_kernel.h"
+#include "paddle/phi/kernels/sparse/conv_kernel.h"
 
 namespace phi {
 namespace sparse {

paddle/phi/tests/api/test_sparse_conv_api.cc

@@ -23,7 +23,7 @@ limitations under the License. */
 #include "paddle/phi/core/kernel_registry.h"
 #include "paddle/phi/core/sparse_coo_tensor.h"
 
-PD_DECLARE_KERNEL(sparse_conv3d, CPU, ALL_LAYOUT);
+PD_DECLARE_KERNEL(conv3d_coo, CPU, ALL_LAYOUT);
 
 template <typename T>
 void TestConv3dBase(const std::vector<int>& indices,

paddle/phi/tests/kernels/test_sparse_conv3d_dev_api.cc

@@ -23,8 +23,8 @@ limitations under the License. */
 #include "paddle/phi/core/kernel_registry.h"
 #include "paddle/phi/core/tensor_utils.h"
 #include "paddle/phi/kernels/sparse/coalesce_kernel.h"
-#include "paddle/phi/kernels/sparse/convolution_grad_kernel.h"
-#include "paddle/phi/kernels/sparse/convolution_kernel.h"
+#include "paddle/phi/kernels/sparse/conv_grad_kernel.h"
+#include "paddle/phi/kernels/sparse/conv_kernel.h"
 
 namespace phi {
 namespace tests {
@@ -114,7 +114,7 @@ void TestConv3dBase(const std::vector<IntT>& indices,
   if (!std::is_same<T, phi::dtype::float16>::value) {
     DenseTensor rulebook = phi::Empty(
         dev_ctx_cpu, DenseTensorMeta(indices_dtype, {1}, DataLayout::NCHW));
-    SparseCooTensor out = sparse::Conv3d<T>(dev_ctx_cpu,
+    SparseCooTensor out = sparse::Conv3dCoo<T>(dev_ctx_cpu,
                                                x_tensor,
                                                kernel_tensor,
                                                paddings,
@@ -139,7 +139,7 @@ void TestConv3dBase(const std::vector<IntT>& indices,
 
     if (backward) {
       std::tuple<SparseCooTensor, DenseTensor> grads =
-          sparse::Conv3dGrad<T>(dev_ctx_cpu,
+          sparse::Conv3dCooGrad<T>(dev_ctx_cpu,
                                    x_tensor,
                                    kernel_tensor,
                                    rulebook,
@@ -198,7 +198,7 @@ void TestConv3dBase(const std::vector<IntT>& indices,
 
   DenseTensor d_rulebook = phi::Empty(
       dev_ctx_gpu, DenseTensorMeta(indices_dtype, {1}, DataLayout::NCHW));
-  SparseCooTensor d_out = sparse::Conv3d<T>(dev_ctx_gpu,
+  SparseCooTensor d_out = sparse::Conv3dCoo<T>(dev_ctx_gpu,
                                                d_x_tensor,
                                                d_kernel_tensor,
                                                paddings,
@@ -242,7 +242,7 @@ void TestConv3dBase(const std::vector<IntT>& indices,
 
   if (backward) {
     std::tuple<SparseCooTensor, DenseTensor> grads =
-        sparse::Conv3dGrad<T>(dev_ctx_gpu,
+        sparse::Conv3dCooGrad<T>(dev_ctx_gpu,
                                  d_x_tensor,
                                  d_kernel_tensor,
                                  d_rulebook,