cf1b701afe
唯一改动: computility-run.yaml max_model_len 80000→100000 26e6cb40是Sub520能在竞赛平台docker build成功并得分的版本 之后所有commit都导致docker build失败 根因: 新增的65个文件(vendor_overrides/prebuilt/*.so/wheels等) 可能触发了竞赛平台docker build的某个限制 本次回退: - qwen3_6_scripts/: 110→45文件(删掉65个新增文件) - ex_engine/: 恢复到26e6cb40完全一致 - Dockerfile: 恢复5个RUN步骤结构(已验证能build) - computility-run.yaml: max_model_len=100000(避免replay 400拒绝)
83 lines
2.6 KiB
C++
83 lines
2.6 KiB
C++
/* Copyright 2025 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 <tuple>
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#include "framework/kv_cache/kv_cache.h"
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#include "framework/model/model_input_params.h"
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#include "layers/common/attention_metadata.h"
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namespace xllm {
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namespace layer {
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class AttentionImpl : public torch::nn::Module {
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public:
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AttentionImpl() = default;
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AttentionImpl(int64_t num_heads,
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int64_t head_size,
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float scale,
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int64_t num_kv_heads,
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int64_t sliding_window);
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AttentionImpl(int64_t num_heads,
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int64_t head_size,
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int64_t num_kv_heads,
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int64_t v_head_dim,
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int64_t sliding_window,
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float scale,
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bool use_fused_mla_qkv,
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bool enable_lighting_indexer,
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bool enable_mla);
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std::tuple<torch::Tensor, std::optional<torch::Tensor>> forward(
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const AttentionMetadata& attn_metadata,
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torch::Tensor& query,
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torch::Tensor& key,
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torch::Tensor& value,
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KVCache& kv_cache);
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void prefill_forward(torch::Tensor& query,
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torch::Tensor& key,
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torch::Tensor& value,
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torch::Tensor& output,
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const torch::Tensor& k_cache,
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const std::optional<torch::Tensor>& v_cache,
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const AttentionMetadata& attn_metadata);
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void decoder_forward(torch::Tensor& query,
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torch::Tensor& output,
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const torch::Tensor& k_cache,
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const std::optional<torch::Tensor>& v_cache,
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const AttentionMetadata& attn_metadata);
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private:
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int64_t num_heads_;
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int64_t head_size_;
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float scale_;
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int64_t num_kv_heads_;
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int64_t v_head_dim_;
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bool use_fused_mla_qkv_;
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bool enable_lighting_indexer_;
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bool enable_mla_;
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int64_t sliding_window_;
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};
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TORCH_MODULE(Attention);
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} // namespace layer
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} // namespace xllm
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