chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/exponential_kernel.cc

@@ -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.
+
+#include "paddle/phi/kernels/exponential_kernel.h"
+
+#include <random>
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/common/amp_type_traits.h"
+#include "paddle/phi/core/generator.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/distribution_helper.h"
+namespace phi {
+
+template <typename T, typename Context>
+void ExponentialKernel(const Context& dev_ctx,
+                       const DenseTensor& x,
+                       float lambda,
+                       DenseTensor* out) {
+  T* out_data = dev_ctx.template Alloc<T>(out);
+  auto engine = dev_ctx.GetGenerator()->GetCPUEngine();
+
+  std::uniform_real_distribution<T> uniform(0.0, 1.0);
+  funcs::exponential_transform<T> trans(lambda);
+
+  for (int64_t i = 0; i < out->numel(); ++i) {
+    out_data[i] = trans(uniform(*engine));
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    exponential, CPU, ALL_LAYOUT, phi::ExponentialKernel, float, double) {}