chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/eigh_grad_kernel_impl.h

@@ -0,0 +1,73 @@
+// 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
+
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/kernels/complex_kernel.h"
+#include "paddle/phi/kernels/elementwise_divide_kernel.h"
+#include "paddle/phi/kernels/elementwise_multiply_kernel.h"
+#include "paddle/phi/kernels/elementwise_subtract_kernel.h"
+#include "paddle/phi/kernels/funcs/diag_functor.h"
+#include "paddle/phi/kernels/funcs/eigen/common.h"
+#include "paddle/phi/kernels/funcs/math_function.h"
+#include "paddle/phi/kernels/funcs/unsqueeze.h"
+#include "paddle/phi/kernels/matmul_kernel.h"
+#include "paddle/phi/kernels/transpose_kernel.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void EighGradKernel(const Context& dev_ctx,
+                    const DenseTensor& out_w,
+                    const DenseTensor& out_v,
+                    const DenseTensor& dout_w,
+                    const DenseTensor& dout_v,
+                    DenseTensor* dx) {
+  dev_ctx.template Alloc<T>(dx);
+  if (out_v.numel() == 0) {
+    return;
+  }
+  auto& dims = out_v.dims();
+  const int m = dims[dims.size() - 1];
+  DenseTensor tV = TransposeLast2Dim<T>(dev_ctx, Conj<T>(dev_ctx, out_v));
+  DenseTensor W = Subtract<dtype::Real<T>>(
+      dev_ctx, funcs::Unsqueeze(out_w, -2), funcs::Unsqueeze(out_w, -1));
+  DenseTensor result = Matmul<T>(dev_ctx, tV, dout_v);
+  result.Resize(dims);
+  dev_ctx.template Alloc<T>(&result);
+
+  std::vector<int> out_shape = vectorize<int>(dims);
+  DenseTensor constant;
+  constant.Resize(out_shape);
+  dev_ctx.template Alloc<T>(&constant);
+  funcs::SetConstant<Context, T>()(dev_ctx, &constant, T(0.5));
+  result = Subtract<T>(
+      dev_ctx, result, Conj<T>(dev_ctx, TransposeLast2Dim<T>(dev_ctx, result)));
+  result = Multiply<T>(dev_ctx, result, constant);
+  if (result.type() != W.type()) {
+    auto x_vector = EigenVector<T>::Flatten(result);
+    auto y_vector = EigenVector<dtype::Real<T>>::Flatten(W);
+    auto out_vector = EigenVector<T>::Flatten(result);
+    auto& place = *dev_ctx.eigen_device();
+    out_vector.device(place) = x_vector / y_vector;
+  } else {
+    result = Divide<T>(dev_ctx, result, W);
+  }
+  result =
+      funcs::DiagFill<T, dtype::Real<T>>(dev_ctx, m, m, m, 0, dout_w, result);
+  *dx = Matmul<T>(dev_ctx, out_v, Matmul<T>(dev_ctx, result, tV));
+}
+
+}  // namespace phi