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      1 /*
      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 
     29 namespace libtextclassifier3 {
     30 namespace mobile {
     31 
     32 template <class EXTRACTOR, class OBJ, class... ARGS>
     33 class 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_
    116