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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2025 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/backends/xpu/xpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/full_kernel.h"
namespace xpu = baidu::xpu::api;
namespace phi {
template <typename T, typename Context>
void MoECombineForwardKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& combine_weights,
const DenseTensor& scatter_index,
DenseTensor* y) {
int64_t seq_len = combine_weights.dims()[0];
int64_t k = combine_weights.dims()[1];
int64_t hidden_size = x.dims()[1];
using XPUType = typename XPUTypeTrait<T>::Type;
auto x_data = reinterpret_cast<const XPUType*>(x.data<T>());
auto weight_data =
reinterpret_cast<const XPUType*>(combine_weights.data<T>());
auto index_data = scatter_index.data<int>();
auto y_data = reinterpret_cast<XPUType*>(y->data<T>());
int ret = xpu::moe_combine<XPUType, int>(dev_ctx.x_context(),
x_data,
weight_data,
index_data,
y_data,
k,
seq_len,
hidden_size);
PADDLE_ENFORCE_XDNN_SUCCESS(ret, "moe_combine");
}
template <typename T, typename Context>
void MoeCombineKernel(const Context& dev_ctx,
const DenseTensor& x,
const DenseTensor& combine_weights,
const DenseTensor& scatter_index,
DenseTensor* y) {
PD_CHECK(x.dims().size() == 2 && combine_weights.dims().size() == 2 &&
scatter_index.dims().size() == 2,
"The shape of X must be 2.");
PD_CHECK(scatter_index.dtype() == DataType::INT32,
"MoE combine only supports int32 for scatter_index!");
dev_ctx.template Alloc<T>(y);
MoECombineForwardKernel<T, Context>(
dev_ctx, x, combine_weights, scatter_index, y);
}
} // namespace phi
PD_REGISTER_KERNEL(moe_combine,
XPU,
ALL_LAYOUT,
phi::MoeCombineKernel,
float,
phi::bfloat16,
phi::float16) {}