chore: import upstream snapshot with attribution

paddle/phi/kernels/reshape_grad_kernel.cc

@@ -0,0 +1,82 @@
+//   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.
+
+#include "paddle/phi/kernels/reshape_grad_kernel.h"
+
+#include "paddle/phi/backends/all_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
+#ifdef PADDLE_WITH_XPU
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#endif
+
+namespace phi {
+
+template <typename Context>
+void ReshapeGradKernel(const Context& dev_ctx,
+                       const DenseTensor& x,
+                       const DenseTensor& out_grad,
+                       DenseTensor* x_grad) {
+  if (x_grad->numel() == 0) {
+    dev_ctx.Alloc(x_grad, x_grad->dtype());
+    return;
+  }
+  // NOTE: [Why not to use x.dims() ?]
+  // Because inplace strategy is different between old IR and PIR,
+  // we need fix it into x.dims() after cleaning old IR system.
+  auto x_dims = x_grad->dims();
+  phi::Copy(dev_ctx, out_grad, dev_ctx.GetPlace(), false, x_grad);
+  x_grad->Resize(x_dims);
+}
+
+#ifdef PADDLE_WITH_XPU
+template <>
+void ReshapeGradKernel<XPUContext>(const XPUContext& dev_ctx,
+                                   const DenseTensor& x,
+                                   const DenseTensor& out_grad,
+                                   DenseTensor* x_grad) {
+  if (x_grad->numel() == 0) {
+    dev_ctx.Alloc(x_grad, x_grad->dtype());
+    return;
+  }
+  auto x_dims = x_grad->dims();
+  dev_ctx.Alloc(x_grad, out_grad.dtype());
+  auto* src_ptr = out_grad.data();
+  auto* dst_ptr = x_grad->data();
+  auto size = out_grad.numel() * phi::SizeOf(out_grad.dtype());
+  int ret = xpu::copy(dev_ctx.x_context(),
+                      reinterpret_cast<const int8_t*>(src_ptr),
+                      reinterpret_cast<int8_t*>(dst_ptr),
+                      size);
+  PADDLE_ENFORCE_XDNN_SUCCESS(ret, "copy");
+  x_grad->Resize(x_dims);
+}
+#endif
+
+template <typename Context>
+void ReshapeDoubleGradKernel(const Context& dev_ctx,
+                             const DenseTensor& out_grad,
+                             const DenseTensor& x_grad_grad,
+                             DenseTensor* out_grad_grad) {
+  ReshapeGradKernel(dev_ctx, out_grad, x_grad_grad, out_grad_grad);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL_FOR_ALL_BACKEND_DTYPE(reshape_grad,
+                                         ALL_LAYOUT,
+                                         phi::ReshapeGradKernel) {}
+PD_REGISTER_KERNEL_FOR_ALL_BACKEND_DTYPE(reshape_double_grad,
+                                         ALL_LAYOUT,
+                                         phi::ReshapeDoubleGradKernel) {}