54 lines
1.5 KiB
C++
54 lines
1.5 KiB
C++
/* Copyright 2026 The xLLM Authors. All Rights Reserved.
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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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https://github.com/jd-opensource/xllm/blob/main/LICENSE
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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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==============================================================================*/
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#pragma once
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#include <torch/torch.h>
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#include "framework/model/model_args.h"
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#include "framework/quant_args.h"
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#include "framework/state_dict/state_dict.h"
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#include "framework/state_dict/utils.h"
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namespace xllm {
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namespace layer {
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class MoEFusedTopkImpl : public torch::nn::Module {
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public:
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MoEFusedTopkImpl(const ModelArgs& model_args,
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const QuantArgs& quant_args,
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const torch::TensorOptions& options);
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std::tuple<torch::Tensor, torch::Tensor> forward(
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torch::Tensor& router_logits);
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void load_state_dict(const StateDict& state_dict);
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private:
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int64_t topk_;
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int64_t num_expert_group_;
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int64_t topk_group_;
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double route_scale_;
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int64_t hidden_size_;
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bool renormalize_;
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std::string scoring_func_;
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DEFINE_WEIGHT(e_score_correction_bias);
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};
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TORCH_MODULE(MoEFusedTopk);
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} // namespace layer
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} // namespace xllm
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