wehub-resource-sync
86 lines
3.3 KiB
C++
86 lines
3.3 KiB
C++
// Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/phi/kernels/multinomial_kernel.h"
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#include "paddle/phi/kernels/funcs/multinomial_kernel_helper.h"
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#include "paddle/phi/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/core/kernel_registry.h"
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namespace phi {
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template <typename T, typename Context>
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void MultinomialKernel(const Context& dev_ctx,
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const DenseTensor& x,
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const Scalar& num_samples,
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bool replacement,
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DenseTensor* out) {
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auto int_num_samples = num_samples.to<int64_t>();
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int64_t* out_data = dev_ctx.template Alloc<int64_t>(out);
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auto in_dims = x.dims();
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int64_t dim_size = in_dims.size();
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const int64_t num_categories = in_dims[dim_size - 1];
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const int64_t num_distributions = dim_size > 1 ? in_dims[dim_size - 2] : 1;
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int64_t seed = dev_ctx.GetGenerator()->Random64();
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// If replacement is False, it's not a replaceable sample. Every category
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// can be used only once.
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if (!replacement) {
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MultinomialInputChecker<T, Context>(dev_ctx, x, num_samples);
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}
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xpu::ctx_guard RAII_GUARD(dev_ctx.x_context());
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const float* in_data = nullptr;
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if (!std::is_same<T, float>::value) {
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// multinomial only accept float as input
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using XPUType = typename XPUTypeTrait<T>::Type;
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auto numel = x.numel();
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float* cast_buffer = RAII_GUARD.alloc_l3_or_gm<float>(numel);
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int r =
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xpu::cast<XPUType, float>(dev_ctx.x_context(),
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reinterpret_cast<const XPUType*>(x.data<T>()),
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cast_buffer,
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numel);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "cast");
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in_data = cast_buffer;
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} else {
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in_data = reinterpret_cast<const float*>(x.data<T>());
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}
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// int multinomial(Context* xpu_ctx, const T* x, TID* y, int64_t num_samples,
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// int64_t num_categories, int64_t num_distributions, bool replacement,
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// int64_t seed);
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int r = xpu::multinomial<float, int64_t>(dev_ctx.x_context(),
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in_data,
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out_data,
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int_num_samples,
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num_categories,
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num_distributions,
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replacement,
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seed);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "multinomial");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(multinomial,
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XPU,
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ALL_LAYOUT,
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phi::MultinomialKernel,
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float,
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phi::float16,
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phi::bfloat16) {
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kernel->OutputAt(0).SetDataType(phi::DataType::INT64);
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}
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