chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/bernoulli_kernel.cc

@@ -0,0 +1,57 @@
+// 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/bernoulli_kernel.h"
+
+#include <random>
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+
+namespace phi {
+
+template <typename T>
+inline T BernoulliFunctor(T p, T rand) {
+  PADDLE_ENFORCE_LE(p,
+                    1.0,
+                    common::errors::OutOfRange(
+                        "The probability should be <= 1, but got %f", p));
+  PADDLE_ENFORCE_GE(p,
+                    0.0,
+                    common::errors::OutOfRange(
+                        "The probability should be >= 0, but got %f", p));
+  return static_cast<T>(rand < p);
+}
+
+template <typename T, typename Context>
+void BernoulliKernel(const Context& dev_ctx,
+                     const DenseTensor& x,
+                     DenseTensor* out) {
+  auto numel = x.numel();
+  auto* x_data = x.data<T>();
+  T* out_data = dev_ctx.template Alloc<T>(out);
+
+  std::uniform_real_distribution<T> dist(0.0, 1.0);
+  auto gen_ptr = dev_ctx.GetGenerator();
+  auto engine = gen_ptr->GetCPUEngine();
+
+  for (int64_t i = 0; i < numel; ++i) {
+    out_data[i] = BernoulliFunctor(x_data[i], dist(*engine));
+  }
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    bernoulli, CPU, ALL_LAYOUT, phi::BernoulliKernel, float, double) {}