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enginex_bi_series-sherpa-onnx/sherpa-onnx/csrc/context-graph.cc
2024-06-19 20:51:57 +08:00

168 lines
5.5 KiB
C++

// sherpa-onnx/csrc/context-graph.cc
//
// Copyright (c) 2023 Xiaomi Corporation
#include "sherpa-onnx/csrc/context-graph.h"
#include <algorithm>
#include <cassert>
#include <queue>
#include <string>
#include <tuple>
#include <utility>
#include "sherpa-onnx/csrc/macros.h"
namespace sherpa_onnx {
void ContextGraph::Build(const std::vector<std::vector<int32_t>> &token_ids,
const std::vector<float> &scores,
const std::vector<std::string> &phrases,
const std::vector<float> &ac_thresholds) const {
if (!scores.empty()) {
SHERPA_ONNX_CHECK_EQ(token_ids.size(), scores.size());
}
if (!phrases.empty()) {
SHERPA_ONNX_CHECK_EQ(token_ids.size(), phrases.size());
}
if (!ac_thresholds.empty()) {
SHERPA_ONNX_CHECK_EQ(token_ids.size(), ac_thresholds.size());
}
for (int32_t i = 0; i < static_cast<int32_t>(token_ids.size()); ++i) {
auto node = root_.get();
float score = scores.empty() ? 0.0f : scores[i];
score = score == 0.0f ? context_score_ : score;
float ac_threshold = ac_thresholds.empty() ? 0.0f : ac_thresholds[i];
ac_threshold = ac_threshold == 0.0f ? ac_threshold_ : ac_threshold;
std::string phrase = phrases.empty() ? std::string() : phrases[i];
for (int32_t j = 0; j < static_cast<int32_t>(token_ids[i].size()); ++j) {
int32_t token = token_ids[i][j];
if (0 == node->next.count(token)) {
bool is_end = j == (static_cast<int32_t>(token_ids[i].size()) - 1);
node->next[token] = std::make_unique<ContextState>(
token, score, node->node_score + score,
is_end ? node->node_score + score : 0, j + 1,
is_end ? ac_threshold : 0.0f, is_end,
is_end ? phrase : std::string());
} else {
float token_score = std::max(score, node->next[token]->token_score);
node->next[token]->token_score = token_score;
float node_score = node->node_score + token_score;
node->next[token]->node_score = node_score;
bool is_end = (j == static_cast<int32_t>(token_ids[i].size()) - 1) ||
node->next[token]->is_end;
node->next[token]->output_score = is_end ? node_score : 0.0f;
node->next[token]->is_end = is_end;
if (j == static_cast<int32_t>(token_ids[i].size()) - 1) {
node->next[token]->phrase = phrase;
node->next[token]->ac_threshold = ac_threshold;
}
}
node = node->next[token].get();
}
}
FillFailOutput();
}
std::tuple<float, const ContextState *, const ContextState *>
ContextGraph::ForwardOneStep(const ContextState *state, int32_t token,
bool strict_mode /*= true*/) const {
const ContextState *node = nullptr;
float score = 0;
if (1 == state->next.count(token)) {
node = state->next.at(token).get();
score = node->token_score;
} else {
node = state->fail;
while (0 == node->next.count(token)) {
node = node->fail;
if (-1 == node->token) break; // root
}
if (1 == node->next.count(token)) {
node = node->next.at(token).get();
}
score = node->node_score - state->node_score;
}
if (!node) {
SHERPA_ONNX_LOGE("Some bad things happened.");
exit(-1);
}
const ContextState *matched_node =
node->is_end ? node : (node->output != nullptr ? node->output : nullptr);
if (!strict_mode && node->output_score != 0) {
SHERPA_ONNX_CHECK(nullptr != matched_node);
float output_score =
node->is_end ? node->node_score
: (node->output != nullptr ? node->output->node_score
: node->node_score);
return std::make_tuple(score + output_score - node->node_score, root_.get(),
matched_node);
}
return std::make_tuple(score + node->output_score, node, matched_node);
}
std::pair<float, const ContextState *> ContextGraph::Finalize(
const ContextState *state) const {
float score = -state->node_score;
return std::make_pair(score, root_.get());
}
std::pair<bool, const ContextState *> ContextGraph::IsMatched(
const ContextState *state) const {
bool status = false;
const ContextState *node = nullptr;
if (state->is_end) {
status = true;
node = state;
} else {
if (state->output != nullptr) {
status = true;
node = state->output;
}
}
return std::make_pair(status, node);
}
void ContextGraph::FillFailOutput() const {
std::queue<const ContextState *> node_queue;
for (auto &kv : root_->next) {
kv.second->fail = root_.get();
node_queue.push(kv.second.get());
}
while (!node_queue.empty()) {
auto current_node = node_queue.front();
node_queue.pop();
for (auto &kv : current_node->next) {
auto fail = current_node->fail;
if (1 == fail->next.count(kv.first)) {
fail = fail->next.at(kv.first).get();
} else {
fail = fail->fail;
while (0 == fail->next.count(kv.first)) {
fail = fail->fail;
if (-1 == fail->token) break;
}
if (1 == fail->next.count(kv.first))
fail = fail->next.at(kv.first).get();
}
kv.second->fail = fail;
// fill the output arc
auto output = fail;
while (!output->is_end) {
output = output->fail;
if (-1 == output->token) {
output = nullptr;
break;
}
}
kv.second->output = output;
kv.second->output_score += output == nullptr ? 0 : output->output_score;
node_queue.push(kv.second.get());
}
}
}
} // namespace sherpa_onnx