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 +1,67 @@
+//   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/elementwise_divide_grad_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
+#include "paddle/phi/kernels/cpu/elementwise_grad.h"
+#include "paddle/phi/kernels/funcs/elementwise_functor.h"
+#include "paddle/phi/kernels/impl/elementwise_grad_kernel_impl.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void DivideGradKernel(const Context& dev_ctx,
+                      const DenseTensor& x,
+                      const DenseTensor& y,
+                      const DenseTensor& out,
+                      const DenseTensor& dout,
+                      int axis,
+                      DenseTensor* dx,
+                      DenseTensor* dy) {
+  funcs::ElementwiseGradPreProcess(dout, dx);
+  funcs::ElemwiseGradCompute<Context, T, DivGradDX<T>, DivGradDY<T>>(
+      dev_ctx, x, y, out, dout, axis, dx, dy, DivGradDX<T>(), DivGradDY<T>());
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(divide_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::DivideGradKernel,
+                   float,
+                   double,
+                   int8_t,
+                   uint8_t,
+                   int16_t,
+                   int,
+                   int64_t,
+                   bool,
+                   phi::complex64,
+                   phi::complex128) {}
+
+PD_REGISTER_KERNEL(divide_double_grad,
+                   CPU,
+                   ALL_LAYOUT,
+                   phi::DivideDoubleGradKernel,
+                   float,
+                   double,
+                   int,
+                   int64_t,
+                   bool,
+                   phi::complex64,
+                   phi::complex128) {}