chore: import upstream snapshot with attribution

paddle/phi/kernels/xpu/multinomial_kernel.cc

@@ -0,0 +1,85 @@
+// 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 "paddle/phi/kernels/multinomial_kernel.h"
+#include "paddle/phi/kernels/funcs/multinomial_kernel_helper.h"
+
+#include "paddle/phi/backends/xpu/enforce_xpu.h"
+#include "paddle/phi/core/kernel_registry.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 int_num_samples = num_samples.to<int64_t>();
+  int64_t* out_data = dev_ctx.template Alloc<int64_t>(out);
+  auto in_dims = x.dims();
+  int64_t dim_size = in_dims.size();
+  const int64_t num_categories = in_dims[dim_size - 1];
+  const int64_t num_distributions = dim_size > 1 ? in_dims[dim_size - 2] : 1;
+  int64_t seed = dev_ctx.GetGenerator()->Random64();
+
+  // If replacement is False, it's not a replaceable sample. Every category
+  // can be used only once.
+  if (!replacement) {
+    MultinomialInputChecker<T, Context>(dev_ctx, x, num_samples);
+  }
+
+  xpu::ctx_guard RAII_GUARD(dev_ctx.x_context());
+  const float* in_data = nullptr;
+  if (!std::is_same<T, float>::value) {
+    // multinomial only accept float as input
+    using XPUType = typename XPUTypeTrait<T>::Type;
+    auto numel = x.numel();
+    float* cast_buffer = RAII_GUARD.alloc_l3_or_gm<float>(numel);
+    int r =
+        xpu::cast<XPUType, float>(dev_ctx.x_context(),
+                                  reinterpret_cast<const XPUType*>(x.data<T>()),
+                                  cast_buffer,
+                                  numel);
+    PADDLE_ENFORCE_XDNN_SUCCESS(r, "cast");
+    in_data = cast_buffer;
+  } else {
+    in_data = reinterpret_cast<const float*>(x.data<T>());
+  }
+
+  // int multinomial(Context* xpu_ctx, const T* x, TID* y, int64_t num_samples,
+  // int64_t num_categories, int64_t num_distributions, bool replacement,
+  // int64_t seed);
+  int r = xpu::multinomial<float, int64_t>(dev_ctx.x_context(),
+                                           in_data,
+                                           out_data,
+                                           int_num_samples,
+                                           num_categories,
+                                           num_distributions,
+                                           replacement,
+                                           seed);
+  PADDLE_ENFORCE_XDNN_SUCCESS(r, "multinomial");
+}
+
+}  // namespace phi
+
+PD_REGISTER_KERNEL(multinomial,
+                   XPU,
+                   ALL_LAYOUT,
+                   phi::MultinomialKernel,
+                   float,
+                   phi::float16,
+                   phi::bfloat16) {
+  kernel->OutputAt(0).SetDataType(phi::DataType::INT64);
+}