chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/eigvalsh_kernel_impl.h

@@ -0,0 +1,45 @@
+/* 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/kernels/eigvalsh_kernel.h"
+
+#include "paddle/phi/kernels/funcs/values_vectors_functor.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void EigvalshKernel(const Context& dev_ctx,
+                    const DenseTensor& x,
+                    const std::string& uplo,
+                    bool is_test,
+                    DenseTensor* out_w,
+                    DenseTensor* out_v) {
+  if (x.numel() == 0) {
+    auto x_dim = x.dims();
+    auto w_dim = slice_ddim(x_dim, 0, x_dim.size() - 1);
+    out_w->Resize(w_dim);
+    out_v->Resize(x_dim);
+    dev_ctx.template Alloc<T>(out_w);
+    dev_ctx.template Alloc<T>(out_v);
+    return;
+  }
+  bool is_lower = (uplo == "L");
+  funcs::MatrixEighFunctor<Context, T> functor;
+  if (is_test) {
+    functor(dev_ctx, x, out_w, nullptr, is_lower, false);
+  } else {
+    functor(dev_ctx, x, out_w, out_v, is_lower, true);
+  }
+}
+
+}  // namespace phi