chore: import upstream snapshot with attribution

paddle/phi/kernels/impl/gammaincc_grad_kernel_impl.h

@@ -0,0 +1,66 @@
+// Copyright (c) 2023 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/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 IgammaGradFunctor {
+  IgammaGradFunctor(
+      const T* dout, const T* x, const T* a, T* output, int64_t numel)
+      : dout_(dout), x_(x), a_(a), output_(output), numel_(numel) {}
+
+  HOSTDEVICE void operator()(int64_t idx) const {
+    using MT = typename MPTypeTrait<T>::Type;
+    const MT mp_dout = static_cast<MT>(dout_[idx]);
+    const MT mp_x = static_cast<MT>(x_[idx]);
+    const MT mp_a = static_cast<MT>(a_[idx]);
+    const MT mp_a_1 = static_cast<MT>(a_[idx] - 1);
+    output_[idx] = static_cast<T>(mp_dout * -std::exp(-mp_x) *
+                                  std::pow(mp_x, mp_a_1) / std::tgamma(mp_a));
+  }
+
+ private:
+  const T* dout_;
+  const T* x_;
+  const T* a_;
+  T* output_;
+  int64_t numel_;
+};
+
+template <typename T, typename Context>
+void GammainccGradKernel(const Context& dev_ctx,
+                         const DenseTensor& x,
+                         const DenseTensor& y,
+                         const DenseTensor& d_out,
+                         DenseTensor* d_y) {
+  if (d_y && d_y->numel() == 0) {
+    dev_ctx.template Alloc<T>(d_y);
+    return;
+  }
+  auto numel = d_out.numel();
+  auto* dout_data = d_out.data<T>();
+  auto* x_data = x.data<T>();
+  auto* y_data = y.data<T>();
+  auto* dy_data =
+      dev_ctx.template Alloc<T>(d_y, static_cast<size_t>(numel * sizeof(T)));
+  funcs::ForRange<Context> for_range(dev_ctx, numel);
+  IgammaGradFunctor<T> functor(dout_data, y_data, x_data, dy_data, numel);
+  for_range(functor);
+}
+}  // namespace phi