chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/lgamma_kernel.cc

@@ -0,0 +1,55 @@
+// 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.
+
+#include "paddle/phi/kernels/lgamma_kernel.h"
+
+#include <unsupported/Eigen/SpecialFunctions>
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/for_range.h"
+
+namespace phi {
+template <typename T>
+struct LgammaFunctor {
+  LgammaFunctor(const T* input, T* output, int64_t numel)
+      : input_(input), output_(output), numel_(numel) {}
+
+  HOSTDEVICE void operator()(int64_t idx) const {
+    output_[idx] = Eigen::numext::lgamma(input_[idx]);
+  }
+
+ private:
+  const T* input_;
+  T* output_;
+  int64_t numel_;
+};
+
+template <typename T, typename Context>
+void LgammaKernel(const Context& dev_ctx,
+                  const DenseTensor& x,
+                  DenseTensor* out) {
+  auto numel = x.numel();
+  auto* x_data = x.data<T>();
+  auto* out_data = dev_ctx.template Alloc<T>(out);
+  if (out && out->numel() == 0) {
+    return;
+  }
+  funcs::ForRange<Context> for_range(dev_ctx, numel);
+  LgammaFunctor<T> functor(x_data, out_data, numel);
+  for_range(functor);
+}
+}  // namespace phi
+
+PD_REGISTER_KERNEL(lgamma, CPU, ALL_LAYOUT, phi::LgammaKernel, float, double) {}