chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/eigvalsh_grad_kernel_impl.h

@@ -0,0 +1,54 @@
+/* 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
+
+#pragma once
+
+#include "paddle/phi/kernels/eigvalsh_grad_kernel.h"
+
+#include "paddle/phi/kernels/complex_kernel.h"
+#include "paddle/phi/kernels/funcs/complex_functors.h"
+#include "paddle/phi/kernels/funcs/eigen/common.h"
+#include "paddle/phi/kernels/matmul_kernel.h"
+#include "paddle/phi/kernels/transpose_kernel.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void EigvalshGradKernel(const Context& dev_ctx,
+                        const DenseTensor& out_v,
+                        const DenseTensor& out_w_grad,
+                        const std::string& uplo UNUSED,
+                        bool is_test UNUSED,
+                        DenseTensor* x_grad) {
+  if (x_grad->numel() == 0) {
+    dev_ctx.template Alloc<T>(x_grad);
+    return;
+  }
+  auto tV = TransposeLast2Dim<T>(dev_ctx, Conj<T>(dev_ctx, out_v));
+
+  x_grad->Resize(out_v.dims());
+  dev_ctx.template Alloc<T>(x_grad);
+
+  auto output_v_vector = EigenVector<T>::Flatten(out_v);
+  auto output_w_grad_vector = EigenVector<dtype::Real<T>>::Flatten(out_w_grad);
+  auto result_vector = EigenVector<T>::Flatten(*x_grad);
+  auto& place = *dev_ctx.eigen_device();
+  std::vector<int> broadcast_factor;
+  broadcast_factor.push_back(out_v.dims().at(out_v.dims().size() - 1));
+  result_vector.device(place) =
+      output_v_vector * output_w_grad_vector.broadcast(broadcast_factor);
+
+  *x_grad = Matmul<T>(dev_ctx, *x_grad, tV);
+}
+
+}  // namespace phi