mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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3754a9906d
* 支持稀疏attn * fix bug * code style * fix moba attn get kv shape * 修复a100编译 * codestyle * code style * code style * code style * fix conflict * 增加单侧 * code style * 增加eblite 加载时间 * fix bug * for ci * for ci * for ci * for ci * 支持mlp block size 128 * 增加小算子单测 * fix 单测 mlp * 将环境变量加入到config里面 * fix rollout config * 修复显存 * add test server * add test server * fix mlp 最后一层使用full attn
205 lines
7.2 KiB
C++
205 lines
7.2 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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#pragma once
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#include "paddle/extension.h"
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void MobaDecoderAttnWriteCacheKv(
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const paddle::Tensor& qkv_out,
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const paddle::Tensor& q_input,
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const paddle::Tensor& cu_seq_q,
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const paddle::Tensor& cu_seq_k,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const paddle::Tensor& cache_k,
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const paddle::Tensor& cache_v,
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const paddle::Tensor& block_tables,
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const paddle::Tensor& rope_sin_cos,
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const paddle::Tensor& k_block_means,
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const paddle::optional<paddle::Tensor>& qkv_bias,
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const paddle::optional<paddle::Tensor>& cache_k_quant_scale,
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const paddle::optional<paddle::Tensor>& cache_v_quant_scale,
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const paddle::optional<paddle::Tensor>& cache_k_dequant_scale,
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const paddle::optional<paddle::Tensor>& cache_v_dequant_scale,
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const paddle::optional<paddle::Tensor>& cache_k_zero_points,
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const paddle::optional<paddle::Tensor>& cache_v_zero_points,
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const int head_num,
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const int kv_head_num,
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const int head_dim,
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const int max_input_length,
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const std::string &cache_quant_type_str);
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void MobaEncoderAttnWriteCacheKv(
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const paddle::Tensor& k_input,
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const paddle::Tensor& v_input,
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const paddle::Tensor& cu_seq_k,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const paddle::Tensor& cache_k,
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const paddle::Tensor& cache_v,
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const paddle::Tensor& block_tables,
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const paddle::optional<paddle::Tensor>& cache_k_quant_scale,
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const paddle::optional<paddle::Tensor>& cache_v_quant_scale,
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const paddle::optional<paddle::Tensor>& cache_k_dequant_scale,
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const paddle::optional<paddle::Tensor>& cache_v_dequant_scale,
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const paddle::optional<paddle::Tensor>& cache_k_zero_points,
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const paddle::optional<paddle::Tensor>& cache_v_zero_points,
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const int head_num,
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const int kv_head_num,
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const int head_dim,
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const int max_seq_q,
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const std::string &cache_quant_type_str);
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void MobaDecoderAttn(
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const paddle::Tensor& q_input,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const paddle::Tensor& cu_seq_q,
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const paddle::Tensor& cache_k,
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const paddle::Tensor& cache_v,
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const paddle::Tensor& block_tables,
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const paddle::Tensor& k_block_means,
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const paddle::Tensor& out,
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const paddle::Tensor& qk_gate_topk_idx,
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const paddle::optional<paddle::Tensor>& cache_k_quant_scale,
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const paddle::optional<paddle::Tensor>& cache_v_quant_scale,
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const paddle::optional<paddle::Tensor>& cache_k_dequant_scale,
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const paddle::optional<paddle::Tensor>& cache_v_dequant_scale,
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const paddle::optional<paddle::Tensor>& cache_k_zero_points,
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const paddle::optional<paddle::Tensor>& cache_v_zero_points,
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const int head_num,
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const int kv_head_num,
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const int head_dim,
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const int max_input_length,
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const int use_moba_seq_limit,
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const int max_seq_q,
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const int max_seq_k,
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const std::string &cache_quant_type_str);
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void FusedBlockMeanAndRope(
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const paddle::Tensor& qkv_out,
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const paddle::Tensor& k_block_means,
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const paddle::Tensor& q_input,
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const paddle::Tensor& k_input,
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const paddle::Tensor& v_input,
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const paddle::Tensor& rotary_embs,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const paddle::Tensor& cu_seq_q,
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const paddle::Tensor& cu_seq_k,
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const paddle::optional<paddle::Tensor>& qkv_bias,
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const int head_num,
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const int kv_head_num,
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const int head_dim,
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const int max_input_length,
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const int max_seq_q,
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const int max_seq_k,
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const std::string &cache_quant_type_str);
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std::vector<paddle::Tensor> GetCurCuSeqLenk(
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const paddle::Tensor& seq_lens_encoder,
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const paddle::Tensor& seq_lens_decoder,
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const paddle::Tensor& seq_lens_this_time,
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const int pack_size);
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std::vector<paddle::Tensor> MobaQKGemm(
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const paddle::Tensor& q_input,
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const paddle::Tensor& k_block_means,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const paddle::Tensor& cu_seq_q,
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const paddle::Tensor& cu_seq_k,
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const int max_seq_q,
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const int max_seq_k,
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const int head_num,
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const int kv_head_num,
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const bool is_split_kv,
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const int use_moba_seq_limit);
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std::vector<paddle::Tensor> QkSortDecoder(
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const paddle::Tensor& qk_gate_weight,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const int head_num,
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const int kv_head_num,
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const int top_k_left,
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const int top_k_right,
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const int use_moba_seq_limit);
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void GetKVFromCache(
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const paddle::Tensor& k_input,
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const paddle::Tensor& v_input,
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const paddle::Tensor& cu_seq_k,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const paddle::Tensor& cache_k,
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const paddle::Tensor& cache_v,
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const paddle::Tensor& block_tables,
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const paddle::optional<paddle::Tensor>& cache_k_dequant_scale,
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const paddle::optional<paddle::Tensor>& cache_v_dequant_scale,
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const paddle::optional<paddle::Tensor>& cache_k_zero_points,
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const paddle::optional<paddle::Tensor>& cache_v_zero_points,
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const int head_num,
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const int kv_head_num,
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const int head_dim,
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const int max_input_length,
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const int max_seq_k,
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const std::string &cache_quant_type_str);
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void MobaEncoderAttn(
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const paddle::Tensor& q_input,
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const paddle::Tensor& k_input,
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const paddle::Tensor& v_input,
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const paddle::Tensor& qk_gate_topk_idx,
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const paddle::Tensor& cu_seq_q,
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const paddle::Tensor& cu_seq_k,
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const paddle::Tensor& cu_seq_q_pack,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const paddle::Tensor& out,
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const int max_seq_q,
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const int max_seq_k,
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const int head_num,
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const int kv_head_num,
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const int head_dim,
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const int max_input_length);
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std::vector<paddle::Tensor> QkSortEncoder(
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const paddle::Tensor& qk_gate_weight,
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const paddle::Tensor& seq_len_encoder,
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const paddle::Tensor& seq_len_decoder,
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const paddle::Tensor& cu_seq_q,
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const paddle::Tensor& cu_seq_k,
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const paddle::Tensor& cu_seq_q_pack,
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const paddle::Tensor& q_pack_tokens,
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const int max_seq_q,
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const int max_seq_k,
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const int head_num,
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const int kv_head_num,
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const int top_k_left,
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const int top_k_right,
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const int use_moba_seq_limit);
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std::vector<paddle::Tensor> MobaMlpEinsum(
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const paddle::Tensor& k_input,
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const paddle::Tensor& attn_gate_weight,
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const paddle::Tensor& seq_lens_encoder,
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const paddle::Tensor& seq_lens_decoder,
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const paddle::Tensor& cu_seq_k,
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const int max_seq_len,
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const int kv_head_num);
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