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https://github.com/PaddlePaddle/FastDeploy.git
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* implement PredictUIEInput * remove batch size * Add GetCandidateIdx * add GetCandidateIdx GetSpan GetSpanIdxAndProbs * Add Predict of UIEModel * Add relation schema * Fix uie unicode bug * rename information_extraction/ernie -> uie * Add more uie task * Add cross task extraction * use CharToBytesOffsetConverter * Add faster_tokenizer dir * Add RuntimeOption args * Add todo comments * Add some readme * fix readme * Fix readme Co-authored-by: Jason <jiangjiajun@baidu.com>
157 lines
6.1 KiB
C++
157 lines
6.1 KiB
C++
// Copyright (c) 2022 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 <ostream>
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#include <set>
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#include <string>
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#include <unordered_map>
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#include <vector>
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#include "fastdeploy/fastdeploy_model.h"
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#include "fastdeploy/utils/unique_ptr.h"
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#include "faster_tokenizer/tokenizers/ernie_faster_tokenizer.h"
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using namespace paddlenlp;
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struct UIEResult {
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size_t start_;
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size_t end_;
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double probability_;
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std::string text_;
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std::unordered_map<std::string, std::vector<UIEResult>> relation_;
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UIEResult() = default;
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UIEResult(size_t start, size_t end, double probability, std::string text)
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: start_(start), end_(end), probability_(probability), text_(text) {}
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};
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std::ostream& operator<<(std::ostream& os, const UIEResult& result);
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std::ostream& operator<<(
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std::ostream& os,
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const std::vector<std::unordered_map<std::string, std::vector<UIEResult>>>&
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results);
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struct SchemaNode {
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std::string name_;
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std::vector<std::vector<std::string>> prefix_;
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std::vector<std::vector<UIEResult*>> relations_;
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std::vector<SchemaNode> children_;
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explicit SchemaNode(const std::string& name,
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const std::vector<SchemaNode>& children = {})
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: name_(name), children_(children) {}
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void AddChild(const std::string& schema) { children_.emplace_back(schema); }
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void AddChild(const SchemaNode& schema) { children_.push_back(schema); }
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void AddChild(const std::string& schema,
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const std::vector<std::string>& children) {
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SchemaNode schema_node(schema);
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for (auto& child : children) {
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schema_node.children_.emplace_back(child);
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}
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children_.emplace_back(schema_node);
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}
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void AddChild(const std::string& schema,
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const std::vector<SchemaNode>& children) {
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SchemaNode schema_node(schema);
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schema_node.children_ = children;
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children_.emplace_back(schema_node);
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}
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};
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struct Schema {
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explicit Schema(const std::string& schema, const std::string& name = "root");
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explicit Schema(const std::vector<std::string>& schema_list,
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const std::string& name = "root");
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explicit Schema(const std::unordered_map<std::string,
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std::vector<SchemaNode>>& schema_map,
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const std::string& name = "root");
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private:
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void CreateRoot(const std::string& name);
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std::unique_ptr<SchemaNode> root_;
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friend class UIEModel;
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};
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struct UIEModel {
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public:
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UIEModel(
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const std::string& model_file, const std::string& params_file,
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const std::string& vocab_file, float position_prob, size_t max_length,
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const std::vector<std::string>& schema,
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const fastdeploy::RuntimeOption& custom_option =
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fastdeploy::RuntimeOption(),
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const fastdeploy::Frontend& model_format = fastdeploy::Frontend::PADDLE);
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UIEModel(
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const std::string& model_file, const std::string& params_file,
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const std::string& vocab_file, float position_prob, size_t max_length,
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const std::unordered_map<std::string, std::vector<SchemaNode>>& schema,
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const fastdeploy::RuntimeOption& custom_option =
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fastdeploy::RuntimeOption(),
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const fastdeploy::Frontend& model_format = fastdeploy::Frontend::PADDLE);
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void SetSchema(const std::vector<std::string>& schema);
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void SetSchema(
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const std::unordered_map<std::string, std::vector<SchemaNode>>& schema);
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void PredictUIEInput(const std::vector<std::string>& input_texts,
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const std::vector<std::string>& prompts,
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std::vector<std::vector<UIEResult>>* results);
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void Predict(
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const std::vector<std::string>& texts,
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std::vector<std::unordered_map<std::string, std::vector<UIEResult>>>*
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results);
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private:
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using IDX_PROB = std::pair<int64_t, float>;
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struct IdxProbCmp {
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bool operator()(const std::pair<IDX_PROB, IDX_PROB>& lhs,
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const std::pair<IDX_PROB, IDX_PROB>& rhs) const;
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};
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using SPAN_SET = std::set<std::pair<IDX_PROB, IDX_PROB>, IdxProbCmp>;
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struct SpanIdx {
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faster_tokenizer::core::Offset offset_;
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bool is_prompt_;
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};
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void AutoSplitter(
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const std::vector<std::string>& texts, size_t max_length,
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std::vector<std::string>* short_texts,
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std::unordered_map<size_t, std::vector<size_t>>* input_mapping);
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void AutoJoiner(
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const std::vector<std::string>& short_texts,
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const std::unordered_map<size_t, std::vector<size_t>>& input_mapping,
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std::vector<std::vector<UIEResult>>* results);
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// Get idx of the last dimension in probability arrays, which is greater than
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// a limitation.
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void GetCandidateIdx(const float* probs, int64_t batch_size, int64_t seq_len,
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std::vector<std::vector<IDX_PROB>>* candidate_idx_prob,
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float threshold = 0.5) const;
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void GetSpan(const std::vector<IDX_PROB>& start_idx_prob,
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const std::vector<IDX_PROB>& end_idx_prob,
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SPAN_SET* span_set) const;
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void GetSpanIdxAndProbs(
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const SPAN_SET& span_set,
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const std::vector<faster_tokenizer::core::Offset>& offset_mapping,
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std::vector<SpanIdx>* span_idxs, std::vector<float>* probs) const;
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void ConvertSpanToUIEResult(
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const std::vector<std::string>& texts,
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const std::vector<std::string>& prompts,
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const std::vector<std::vector<SpanIdx>>& span_idxs,
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const std::vector<std::vector<float>>& probs,
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std::vector<std::vector<UIEResult>>* results) const;
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fastdeploy::RuntimeOption runtime_option_;
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fastdeploy::Runtime runtime_;
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std::unique_ptr<Schema> schema_;
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size_t max_length_;
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float position_prob_;
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faster_tokenizer::tokenizers_impl::ErnieFasterTokenizer tokenizer_;
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};
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