wehub-resource-sync
53 lines
2.2 KiB
C++
53 lines
2.2 KiB
C++
// Copyright (c) 2025 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/backends/xpu/enforce_xpu.h"
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#include "paddle/phi/backends/xpu/xpu_context.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 ExpandModalityExpertIDKernel(const Context& dev_ctx,
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const DenseTensor& expert_id,
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int64_t num_expert_per_modality,
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int64_t group_size,
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int64_t modality_offset,
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bool is_group_expert,
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DenseTensor* expert_id_out) {
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dev_ctx.template Alloc<T>(expert_id_out);
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auto expert_id_shape = expert_id.dims();
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int64_t seqlen = expert_id_shape[0];
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int64_t k = expert_id_shape[1];
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int r = xpu::expand_modality_expert_id(dev_ctx.x_context(),
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expert_id.data<T>(),
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expert_id_out->data<T>(),
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seqlen,
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k,
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num_expert_per_modality,
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group_size,
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modality_offset,
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is_group_expert);
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PADDLE_ENFORCE_XDNN_SUCCESS(r, "expand_modality_expert_id");
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}
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} // namespace phi
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PD_REGISTER_KERNEL(expand_modality_expert_id,
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XPU,
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ALL_LAYOUT,
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phi::ExpandModalityExpertIDKernel,
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int,
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int64_t) {}
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