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107 lines
4.0 KiB
Plaintext
107 lines
4.0 KiB
Plaintext
// 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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#include <fcntl.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include <sys/mman.h>
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#include <sys/stat.h>
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#include <sys/types.h>
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#include <unistd.h>
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#include "helper.h"
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#include "paddle/extension.h"
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__global__ void set_value_by_flags(bool *stop_flags,
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int64_t *topk_ids,
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int64_t *next_tokens,
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const int64_t *end_ids,
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const int *seq_lens,
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const int bs,
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const int end_length,
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bool beam_search,
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bool prefill_one_step_stop) {
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int tid = threadIdx.x;
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if (tid < bs) {
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if (prefill_one_step_stop) {
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stop_flags[tid] = true;
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if (seq_lens[tid] == 0) {
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topk_ids[tid] = -1;
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}
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next_tokens[tid] = topk_ids[tid];
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} else {
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if (stop_flags[tid]) {
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if (seq_lens[tid] == 0) {
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topk_ids[tid] = -1;
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} else {
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topk_ids[tid] = end_ids[0];
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next_tokens[tid] = end_ids[0];
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}
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} else {
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next_tokens[tid] = topk_ids[tid];
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}
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}
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if (!beam_search && is_in_end(topk_ids[tid], end_ids, end_length)) {
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stop_flags[tid] = true;
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}
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}
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}
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void GetStopFlagsMulti(const paddle::Tensor &topk_ids,
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const paddle::Tensor &stop_flags,
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const paddle::Tensor &seq_lens,
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const paddle::Tensor &end_ids,
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const paddle::Tensor &next_tokens,
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const bool beam_search) {
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PD_CHECK(topk_ids.dtype() == paddle::DataType::INT64);
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PD_CHECK(stop_flags.dtype() == paddle::DataType::BOOL);
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bool prefill_one_step_stop = false;
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if (const char *env_p = std::getenv("PREFILL_NODE_ONE_STEP_STOP")) {
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// std::cout << "Your PATH is: " << env_p << '\n';
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if (env_p[0] == '1') {
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prefill_one_step_stop = true;
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}
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}
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#ifdef PADDLE_WITH_CUSTOM_DEVICE
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auto dev_ctx = static_cast<const phi::CustomContext*>(paddle::experimental::DeviceContextPool::Instance().Get(topk_ids.place()));
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auto cu_stream = dev_ctx->stream();
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#else
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auto cu_stream = topk_ids.stream();
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#endif
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std::vector<int64_t> shape = topk_ids.shape();
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int64_t bs_now = shape[0];
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int64_t end_length = end_ids.shape()[0];
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int block_size = (bs_now + WARP_SIZE - 1) / WARP_SIZE * WARP_SIZE;
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set_value_by_flags<<<1, block_size, 0, cu_stream>>>(
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const_cast<bool *>(stop_flags.data<bool>()),
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const_cast<int64_t *>(topk_ids.data<int64_t>()),
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const_cast<int64_t *>(next_tokens.data<int64_t>()),
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end_ids.data<int64_t>(),
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seq_lens.data<int>(),
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bs_now,
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end_length,
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beam_search,
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prefill_one_step_stop);
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}
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PD_BUILD_STATIC_OP(set_stop_value_multi_ends)
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.Inputs({"topk_ids", "stop_flags", "seq_lens", "end_ids", "next_tokens"})
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.Attrs({"beam_search: bool"})
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.Outputs({"topk_ids_out", "stop_flags_out", "next_tokens_out"})
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.SetInplaceMap({{"topk_ids", "topk_ids_out"},
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{"stop_flags", "stop_flags_out"},
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{"next_tokens", "next_tokens_out"}})
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.SetKernelFn(PD_KERNEL(GetStopFlagsMulti));
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