blob: 87576c6d5ff8fd495be48280e5859f7e6c90959c [file] [log] [blame]
Tony Mak51a9e542018-11-02 13:36:22 +00001/*
2 * Copyright (C) 2018 The Android Open Source Project
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17#ifndef NLP_SAFT_COMPONENTS_COMMON_MOBILE_EMBEDDING_FEATURE_INTERFACE_H_
18#define NLP_SAFT_COMPONENTS_COMMON_MOBILE_EMBEDDING_FEATURE_INTERFACE_H_
19
20#include <string>
21#include <vector>
22
23#include "lang_id/common/embedding-feature-extractor.h"
24#include "lang_id/common/fel/feature-extractor.h"
25#include "lang_id/common/fel/task-context.h"
26#include "lang_id/common/fel/workspace.h"
27#include "lang_id/common/lite_base/attributes.h"
28
29namespace libtextclassifier3 {
30namespace mobile {
31
32template <class EXTRACTOR, class OBJ, class... ARGS>
33class EmbeddingFeatureInterface {
34 public:
35 // Constructs this EmbeddingFeatureInterface.
36 //
37 // |arg_prefix| is a string prefix for the TaskContext parameters, passed to
38 // |the underlying EmbeddingFeatureExtractor.
39 explicit EmbeddingFeatureInterface(const string &arg_prefix)
40 : feature_extractor_(arg_prefix) {}
41
42 // Sets up feature extractors and flags for processing (inference).
43 SAFTM_MUST_USE_RESULT bool SetupForProcessing(TaskContext *context) {
44 return feature_extractor_.Setup(context);
45 }
46
47 // Initializes feature extractor resources for processing (inference)
48 // including requesting a workspace for caching extracted features.
49 SAFTM_MUST_USE_RESULT bool InitForProcessing(TaskContext *context) {
50 if (!feature_extractor_.Init(context)) return false;
51 feature_extractor_.RequestWorkspaces(&workspace_registry_);
52 return true;
53 }
54
55 // Preprocesses *obj using the internal workspace registry.
56 void Preprocess(WorkspaceSet *workspace, OBJ *obj) const {
57 workspace->Reset(workspace_registry_);
58 feature_extractor_.Preprocess(workspace, obj);
59 }
60
61 // Extract features from |obj|. On return, FeatureVector features[i]
62 // contains the features for the embedding space #i.
63 //
64 // This function uses the precomputed info from |workspace|. Usage pattern:
65 //
66 // EmbeddingFeatureInterface<...> feature_interface;
67 // ...
68 // OBJ obj;
69 // WorkspaceSet workspace;
70 // feature_interface.Preprocess(&workspace, &obj);
71 //
72 // // For the same obj, but with different args:
73 // std::vector<FeatureVector> features;
74 // feature_interface.GetFeatures(obj, args, workspace, &features);
75 //
76 // This pattern is useful (more efficient) if you can pre-compute some info
77 // for the entire |obj|, which is reused by the feature extraction performed
78 // for different args. If that is not the case, you can use the simpler
79 // version GetFeaturesNoCaching below.
80 void GetFeatures(const OBJ &obj, ARGS... args, const WorkspaceSet &workspace,
81 std::vector<FeatureVector> *features) const {
82 feature_extractor_.ExtractFeatures(workspace, obj, args..., features);
83 }
84
85 // Simpler version of GetFeatures(), for cases when there is no opportunity to
86 // reuse computation between feature extractions for the same |obj|, but with
87 // different |args|. Returns the extracted features. For more info, see the
88 // doc for GetFeatures().
89 std::vector<FeatureVector> GetFeaturesNoCaching(OBJ *obj,
90 ARGS... args) const {
91 // Technically, we still use a workspace, because
92 // feature_extractor_.ExtractFeatures requires one. But there is no real
93 // caching here, as we start from scratch for each call to ExtractFeatures.
94 WorkspaceSet workspace;
95 Preprocess(&workspace, obj);
96 std::vector<FeatureVector> features(NumEmbeddings());
97 GetFeatures(*obj, args..., workspace, &features);
98 return features;
99 }
100
101 // Returns number of embedding spaces.
102 int NumEmbeddings() const { return feature_extractor_.NumEmbeddings(); }
103
104 private:
105 // Typed feature extractor for embeddings.
106 EmbeddingFeatureExtractor<EXTRACTOR, OBJ, ARGS...> feature_extractor_;
107
108 // The registry of shared workspaces in the feature extractor.
109 WorkspaceRegistry workspace_registry_;
110};
111
112} // namespace mobile
113} // namespace nlp_saft
114
115#endif // NLP_SAFT_COMPONENTS_COMMON_MOBILE_EMBEDDING_FEATURE_INTERFACE_H_