chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/soft_relu_kernel.cc

@@ -0,0 +1,69 @@
+// Copyright (c) 2024 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 <glog/logging.h>
+
+#include <algorithm>
+#include <cmath>
+#include <memory>
+#include <string>
+#include <unordered_set>
+#include <utility>
+#include <vector>
+#ifndef _USE_MATH_DEFINES
+#define _USE_MATH_DEFINES
+#endif
+
+#include <type_traits>
+
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/core/tensor_utils.h"
+#include "paddle/phi/kernels/funcs/activation_functor.h"
+#include "paddle/phi/kernels/funcs/blas/blas.h"
+#include "paddle/phi/kernels/funcs/eigen/common.h"
+
+namespace phi {
+
+template <typename T>
+struct SoftReluFunctor {
+  float threshold;
+  void SetAttrs(float threshold_) { threshold = threshold_; }
+
+  template <typename Device, typename X, typename Out>
+  void operator()(Device d, X x, Out out) {
+    auto tmp = static_cast<T>(threshold);
+    auto temp = x.cwiseMax(-tmp).cwiseMin(tmp);
+    out.device(d) = (static_cast<T>(1) + temp.exp()).log();
+  }
+};
+
+template <typename T, typename Context>
+void SoftmaxKernel(const Context& dev_ctx,
+                   const DenseTensor& x,
+                   float threshold,
+                   DenseTensor* out) {
+  dev_ctx.template Alloc<T>(out);
+
+  auto x_flatten = EigenVector<T>::Flatten(x);
+  auto out_flatten = EigenVector<T>::Flatten(*out);
+  auto* eigen_dev = dev_ctx.eigen_device();
+  SoftReluFunctor<T> functor;
+  functor.SetAttrs(threshold);
+  functor(*eigen_dev, x_flatten, out_flatten);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    soft_relu, CPU, ALL_LAYOUT, phi::SoftmaxKernel, float, double) {}