chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/digamma_grad_kernel_impl.h

@@ -0,0 +1,64 @@
+// 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 <unsupported/Eigen/SpecialFunctions>
+
+#include "paddle/phi/common/amp_type_traits.h"
+#include "paddle/phi/core/dense_tensor.h"
+#include "paddle/phi/kernels/funcs/for_range.h"
+
+namespace phi {
+
+template <typename T>
+struct DigammaGradFunctor {
+  DigammaGradFunctor(const T* dout, const T* x, T* output, int64_t numel)
+      : dout_(dout), x_(x), output_(output), numel_(numel) {}
+
+  HOSTDEVICE void operator()(int64_t idx) const {
+    using MPType = typename MPTypeTrait<T>::Type;
+    const MPType mp_dout = static_cast<MPType>(dout_[idx]);
+    const MPType mp_x = static_cast<MPType>(x_[idx]);
+    output_[idx] =
+        static_cast<T>(mp_dout * Eigen::numext::polygamma(MPType(1), mp_x));
+  }
+
+ private:
+  const T* dout_;
+  const T* x_;
+  T* output_;
+  int64_t numel_;
+};
+
+template <typename T, typename Context>
+void DigammaGradKernel(const Context& dev_ctx,
+                       const DenseTensor& x,
+                       const DenseTensor& out_grad,
+                       DenseTensor* x_grad) {
+  dev_ctx.template Alloc<T>(x_grad);
+  if (x_grad && x_grad->numel() == 0) {
+    return;
+  }
+
+  auto* dout_data = out_grad.data<T>();
+  auto* x_data = x.data<T>();
+  auto* dx_data = x_grad->data<T>();
+  auto numel = out_grad.numel();
+  funcs::ForRange<Context> for_range(dev_ctx, numel);
+  DigammaGradFunctor<T> functor(dout_data, x_data, dx_data, numel);
+  for_range(functor);
+}
+
+}  // namespace phi