chore: import upstream snapshot with attribution

paddle/phi/kernels/cpu/multinomial_kernel.cc

@@ -0,0 +1,50 @@
+/* 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/multinomial_kernel.h"
+
+#include "paddle/phi/backends/cpu/cpu_context.h"
+#include "paddle/phi/core/kernel_registry.h"
+#include "paddle/phi/kernels/funcs/multinomial_functor.h"
+
+namespace phi {
+
+template <typename T, typename Context>
+void MultinomialKernel(const Context& dev_ctx,
+                       const DenseTensor& x,
+                       const Scalar& num_samples,
+                       bool replacement,
+                       DenseTensor* out) {
+  auto* in_data = x.data<T>();
+  int64_t* out_data = dev_ctx.template Alloc<int64_t>(out);
+  auto in_dims = x.dims();
+  int in_rank = in_dims.size();
+  const int64_t num_categories = in_dims[in_rank - 1];
+  const int64_t num_distributions = in_rank > 1 ? in_dims[in_rank - 2] : 1;
+
+  funcs::MultinomialFunctor<T>(dev_ctx,
+                               out_data,
+                               in_data,
+                               num_samples.to<int>(),
+                               replacement,
+                               num_categories,
+                               num_distributions);
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    multinomial, CPU, ALL_LAYOUT, phi::MultinomialKernel, float, double) {
+  kernel->OutputAt(0).SetDataType(phi::DataType::INT64);
+}