chore: import upstream snapshot with attribution

2026-07-13 12:40:42 +08:00
commit e25996e7db
15472 changed files with 3536181 additions and 0 deletions
@@ -0,0 +1,96 @@
+/* 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 "paddle/phi/kernels/sparse/addmm_grad_kernel.h"
+
+#include "paddle/phi/backends/gpu/gpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/empty_kernel.h"
+#include "paddle/phi/kernels/funcs/blas/blas.h"
+#include "paddle/phi/kernels/sparse/matmul_grad_kernel.h"
+
+namespace phi {
+namespace sparse {
+
+template <typename T, typename Context>
+void AddmmCooDenseGradKernel(const Context& dev_ctx,
+                             const DenseTensor& input,
+                             const SparseCooTensor& x,
+                             const DenseTensor& y,
+                             const DenseTensor& dout,
+                             float alpha,
+                             float beta,
+                             DenseTensor* dinput,
+                             SparseCooTensor* dx,
+                             DenseTensor* dy) {
+  auto blas = funcs::GetBlas<Context, T>(dev_ctx);
+  if (dinput) {
+    dinput->Resize(input.dims());
+    dev_ctx.template Alloc<T>(dinput);
+
+    blas.VCOPY(input.numel(), dout.data<T>(), dinput->data<T>());
+    blas.SCAL(input.numel(), beta, dinput->data<T>());
+  }
+  DenseTensor dout_scale = EmptyLike<T, Context>(dev_ctx, dout);
+  blas.VCOPY(dout.numel(), dout.data<T>(), dout_scale.data<T>());
+  blas.SCAL(dout.numel(), alpha, dout_scale.data<T>());
+  MatmulCooDenseGradKernel<T, Context>(dev_ctx, x, y, dout_scale, dx, dy);
+}
+
+// Backward of "DENSE + CSR @ DENSE -> DENSE"
+template <typename T, typename Context>
+void AddmmCsrDenseGradKernel(const Context& dev_ctx,
+                             const DenseTensor& input,
+                             const SparseCsrTensor& x,
+                             const DenseTensor& y,
+                             const DenseTensor& dout,
+                             float alpha,
+                             float beta,
+                             DenseTensor* dinput,
+                             SparseCsrTensor* dx,
+                             DenseTensor* dy) {
+  auto blas = funcs::GetBlas<Context, T>(dev_ctx);
+  if (dinput) {
+    dinput->Resize(input.dims());
+    dev_ctx.template Alloc<T>(dinput);
+
+    blas.VCOPY(input.numel(), dout.data<T>(), dinput->data<T>());
+    blas.SCAL(input.numel(), beta, dinput->data<T>());
+  }
+  DenseTensor dout_scale = EmptyLike<T, Context>(dev_ctx, dout);
+  blas.VCOPY(dout.numel(), dout.data<T>(), dout_scale.data<T>());
+  blas.SCAL(dout.numel(), alpha, dout_scale.data<T>());
+  MatmulCsrDenseGradKernel<T, Context>(dev_ctx, x, y, dout_scale, dx, dy);
+}
+
+}  // namespace sparse
+}  // namespace phi
+
+PD_REGISTER_KERNEL(addmm_coo_dense_grad,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::sparse::AddmmCooDenseGradKernel,
+                   float,
+                   double) {
+  kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
+}
+
+PD_REGISTER_KERNEL(addmm_csr_dense_grad,
+                   GPU,
+                   ALL_LAYOUT,
+                   phi::sparse::AddmmCsrDenseGradKernel,
+                   float,
+                   double) {
+  kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_CSR);
+}