mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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243 lines
11 KiB
Plaintext
243 lines
11 KiB
Plaintext
// 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 "helper.h"
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// 根据上一步计算出的可以复原的query_id进行状态恢复
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__global__ void recover_block_system_cache(int *recover_block_list, // [bsz]
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int *recover_len,
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bool *stop_flags,
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int *seq_lens_this_time,
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int *ori_seq_lens_encoder,
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int *ori_seq_lens_decoder,
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int *seq_lens_encoder,
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int *seq_lens_decoder,
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int *block_tables,
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int *free_list,
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int *free_list_len,
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int64_t *input_ids,
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int64_t *pre_ids,
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int64_t *step_idx,
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int *encoder_block_lens,
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int *used_list_len,
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const int64_t *next_tokens,
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const int64_t *first_token_ids,
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const int bsz,
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const int block_num_per_seq,
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const int length,
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const int pre_id_length) {
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const int bid = blockIdx.x;
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const int tid = threadIdx.x;
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__shared__ int ori_free_list_len;
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if (bid < recover_len[0]) {
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const int recover_id = recover_block_list[bid];
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const int ori_seq_len_encoder = ori_seq_lens_encoder[recover_id];
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const int step_idx_now = step_idx[recover_id];
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const int seq_len = ori_seq_len_encoder + step_idx_now;
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const int encoder_block_len = encoder_block_lens[recover_id];
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const int decoder_used_len = used_list_len[recover_id];
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int *block_table_now = block_tables + recover_id * block_num_per_seq;
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int64_t *input_ids_now = input_ids + recover_id * length;
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int64_t *pre_ids_now = pre_ids + recover_id * pre_id_length;
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if (tid == 0) {
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seq_lens_this_time[recover_id] = seq_len;
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seq_lens_encoder[recover_id] = seq_len;
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seq_lens_decoder[recover_id] = ori_seq_lens_decoder[recover_id];
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stop_flags[recover_id] = false;
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input_ids_now[ori_seq_len_encoder + step_idx_now - 1] = next_tokens[recover_id]; // next tokens
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input_ids_now[0] = first_token_ids[recover_id]; // set first prompt token
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const int ori_free_list_len_tid0 = atomicSub(free_list_len, decoder_used_len);
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ori_free_list_len = ori_free_list_len_tid0;
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#ifdef DEBUG_STEP
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printf("seq_id: %d, ori_seq_len_encoder: %d, step_idx_now: %d, seq_len: %d, ori_free_list_len_tid0: %d, ori_free_list_len: %d\n",
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recover_id, ori_seq_len_encoder, step_idx_now, seq_len, ori_free_list_len_tid0, ori_free_list_len);
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#endif
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}
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__syncthreads();
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// 恢复block table
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for (int i = tid; i < decoder_used_len; i += blockDim.x) {
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block_table_now[encoder_block_len + i] = free_list[ori_free_list_len - i - 1];
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}
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// 恢复input_ids
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for (int i = tid; i < step_idx_now - 1; i += blockDim.x) {
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input_ids_now[ori_seq_len_encoder + i] = pre_ids_now[i + 1];
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}
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}
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if (bid == 0 && tid == 0) {
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recover_len[0] = 0;
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}
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}
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void StepSystemCache(const paddle::Tensor& stop_flags,
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const paddle::Tensor& seq_lens_this_time,
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const paddle::Tensor& ori_seq_lens_encoder,
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const paddle::Tensor& ori_seq_lens_decoder,
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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& block_tables, // [bsz, block_num_per_seq]
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const paddle::Tensor& encoder_block_lens,
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const paddle::Tensor& is_block_step,
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const paddle::Tensor& step_block_list,
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const paddle::Tensor& step_lens,
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const paddle::Tensor& recover_block_list,
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const paddle::Tensor& recover_lens,
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const paddle::Tensor& need_block_list,
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const paddle::Tensor& need_block_len,
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const paddle::Tensor& used_list_len,
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const paddle::Tensor& free_list,
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const paddle::Tensor& free_list_len,
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const paddle::Tensor& input_ids,
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const paddle::Tensor& pre_ids,
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const paddle::Tensor& step_idx,
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const paddle::Tensor& next_tokens,
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const paddle::Tensor& first_token_ids,
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const int block_size,
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const int encoder_decoder_block_num) {
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auto cu_stream = seq_lens_this_time.stream();
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const int bsz = seq_lens_this_time.shape()[0];
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const int block_num_per_seq = block_tables.shape()[1];
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const int length = input_ids.shape()[1];
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const int pre_id_length = pre_ids.shape()[1];
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constexpr int BlockSize = 256; // bsz <= 256
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const int max_decoder_block_num = length / block_size;
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// const int max_decoder_block_num = 2048 / block_size - encoder_decoder_block_num;
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#ifdef DEBUG_STEP
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printf("bsz: %d, block_num_per_seq: %d, length: %d, max_decoder_block_num: %d\n", bsz, block_num_per_seq, length, max_decoder_block_num);
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#endif
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free_and_dispatch_block<<<1, BlockSize, 0, cu_stream>>>(
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const_cast<bool*>(stop_flags.data<bool>()),
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const_cast<int*>(seq_lens_this_time.data<int>()),
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const_cast<int*>(seq_lens_decoder.data<int>()),
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const_cast<int*>(block_tables.data<int>()),
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const_cast<int*>(encoder_block_lens.data<int>()),
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const_cast<bool*>(is_block_step.data<bool>()),
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const_cast<int*>(step_block_list.data<int>()),
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const_cast<int*>(step_lens.data<int>()),
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const_cast<int*>(recover_block_list.data<int>()),
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const_cast<int*>(recover_lens.data<int>()),
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const_cast<int*>(need_block_list.data<int>()),
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const_cast<int*>(need_block_len.data<int>()),
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const_cast<int*>(used_list_len.data<int>()),
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const_cast<int*>(free_list.data<int>()),
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const_cast<int*>(free_list_len.data<int>()),
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const_cast<int64_t*>(first_token_ids.data<int64_t>()),
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bsz,
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block_size,
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block_num_per_seq,
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max_decoder_block_num
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);
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#ifdef DEBUG_STEP
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cudaDeviceSynchronize();
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#endif
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auto cpu_recover_lens = recover_lens.copy_to(paddle::CPUPlace(), false);
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const int grid_size = cpu_recover_lens.data<int>()[0];
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#ifdef DEBUG_STEP
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printf("grid_size2 %d\n", grid_size);
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#endif
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if (grid_size > 0) {
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recover_block_system_cache<<<grid_size, BlockSize, 0, cu_stream>>>(
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const_cast<int*>(recover_block_list.data<int>()),
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const_cast<int*>(recover_lens.data<int>()),
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const_cast<bool*>(stop_flags.data<bool>()),
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const_cast<int*>(seq_lens_this_time.data<int>()),
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const_cast<int*>(ori_seq_lens_encoder.data<int>()),
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const_cast<int*>(ori_seq_lens_decoder.data<int>()),
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const_cast<int*>(seq_lens_encoder.data<int>()),
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const_cast<int*>(seq_lens_decoder.data<int>()),
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const_cast<int*>(block_tables.data<int>()),
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const_cast<int*>(free_list.data<int>()),
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const_cast<int*>(free_list_len.data<int>()),
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const_cast<int64_t*>(input_ids.data<int64_t>()),
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const_cast<int64_t*>(pre_ids.data<int64_t>()),
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const_cast<int64_t*>(step_idx.data<int64_t>()),
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const_cast<int*>(encoder_block_lens.data<int>()),
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const_cast<int*>(used_list_len.data<int>()),
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next_tokens.data<int64_t>(),
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first_token_ids.data<int64_t>(),
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bsz,
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block_num_per_seq,
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length,
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pre_id_length
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);
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#ifdef DEBUG_STEP
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cudaDeviceSynchronize();
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#endif
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}
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}
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PD_BUILD_STATIC_OP(step_system_cache)
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.Inputs({"stop_flags",
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"seq_lens_this_time",
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"ori_seq_lens_encoder",
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"ori_seq_lens_decoder",
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"seq_lens_encoder",
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"seq_lens_decoder",
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"block_tables",
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"encoder_block_lens",
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"is_block_step",
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"step_block_list",
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"step_lens",
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"recover_block_list",
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"recover_lens",
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"need_block_list",
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"need_block_len",
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"used_list_len",
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"free_list",
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"free_list_len",
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"input_ids",
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"pre_ids",
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"step_idx",
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"next_tokens",
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"first_token_ids"})
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.Attrs({"block_size: int",
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"encoder_decoder_block_num: int"})
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.Outputs({"stop_flags_out",
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"seq_lens_this_time_out",
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"seq_lens_encoder_out",
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"seq_lens_decoder_out",
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"block_tables_out",
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"encoder_block_lens_out",
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"is_block_step_out",
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"step_block_list_out",
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"step_lens_out",
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"recover_block_list_out",
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"recover_lens_out",
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"need_block_list_out",
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"need_block_len_out",
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"used_list_len_out",
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"free_list_out",
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"free_list_len_out",
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"input_ids_out",
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"first_token_ids_out"})
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.SetInplaceMap({{"stop_flags", "stop_flags_out"},
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{"seq_lens_this_time", "seq_lens_this_time_out"},
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{"seq_lens_encoder", "seq_lens_encoder_out"},
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{"seq_lens_decoder", "seq_lens_decoder_out"},
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{"block_tables", "block_tables_out"},
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{"encoder_block_lens", "encoder_block_lens_out"},
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{"is_block_step", "is_block_step_out"},
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{"step_block_list", "step_block_list_out"},
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{"step_lens", "step_lens_out"},
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{"recover_block_list", "recover_block_list_out"},
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{"recover_lens", "recover_lens_out"},
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{"need_block_list", "need_block_list_out"},
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{"need_block_len", "need_block_len_out"},
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{"used_list_len", "used_list_len_out"},
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{"free_list", "free_list_out"},
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{"free_list_len", "free_list_len_out"},
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{"input_ids", "input_ids_out"},
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{"first_token_ids", "first_token_ids_out"}})
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.SetKernelFn(PD_KERNEL(StepSystemCache));
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