Export libtextclassifier to Android (generated by the export script)

Test: Compile and boot

Change-Id: I0433e6fb549ba0b32bc55933b3c11562e61a0b4d
diff --git a/lang_id/common/embedding-feature-interface.h b/lang_id/common/embedding-feature-interface.h
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+/*
+ * Copyright (C) 2018 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef NLP_SAFT_COMPONENTS_COMMON_MOBILE_EMBEDDING_FEATURE_INTERFACE_H_
+#define NLP_SAFT_COMPONENTS_COMMON_MOBILE_EMBEDDING_FEATURE_INTERFACE_H_
+
+#include <string>
+#include <vector>
+
+#include "lang_id/common/embedding-feature-extractor.h"
+#include "lang_id/common/fel/feature-extractor.h"
+#include "lang_id/common/fel/task-context.h"
+#include "lang_id/common/fel/workspace.h"
+#include "lang_id/common/lite_base/attributes.h"
+
+namespace libtextclassifier3 {
+namespace mobile {
+
+template <class EXTRACTOR, class OBJ, class... ARGS>
+class EmbeddingFeatureInterface {
+ public:
+  // Constructs this EmbeddingFeatureInterface.
+  //
+  // |arg_prefix| is a string prefix for the TaskContext parameters, passed to
+  // |the underlying EmbeddingFeatureExtractor.
+  explicit EmbeddingFeatureInterface(const string &arg_prefix)
+      : feature_extractor_(arg_prefix) {}
+
+  // Sets up feature extractors and flags for processing (inference).
+  SAFTM_MUST_USE_RESULT bool SetupForProcessing(TaskContext *context) {
+    return feature_extractor_.Setup(context);
+  }
+
+  // Initializes feature extractor resources for processing (inference)
+  // including requesting a workspace for caching extracted features.
+  SAFTM_MUST_USE_RESULT bool InitForProcessing(TaskContext *context) {
+    if (!feature_extractor_.Init(context)) return false;
+    feature_extractor_.RequestWorkspaces(&workspace_registry_);
+    return true;
+  }
+
+  // Preprocesses *obj using the internal workspace registry.
+  void Preprocess(WorkspaceSet *workspace, OBJ *obj) const {
+    workspace->Reset(workspace_registry_);
+    feature_extractor_.Preprocess(workspace, obj);
+  }
+
+  // Extract features from |obj|.  On return, FeatureVector features[i]
+  // contains the features for the embedding space #i.
+  //
+  // This function uses the precomputed info from |workspace|.  Usage pattern:
+  //
+  //   EmbeddingFeatureInterface<...> feature_interface;
+  //   ...
+  //   OBJ obj;
+  //   WorkspaceSet workspace;
+  //   feature_interface.Preprocess(&workspace, &obj);
+  //
+  //   // For the same obj, but with different args:
+  //   std::vector<FeatureVector> features;
+  //   feature_interface.GetFeatures(obj, args, workspace, &features);
+  //
+  // This pattern is useful (more efficient) if you can pre-compute some info
+  // for the entire |obj|, which is reused by the feature extraction performed
+  // for different args.  If that is not the case, you can use the simpler
+  // version GetFeaturesNoCaching below.
+  void GetFeatures(const OBJ &obj, ARGS... args, const WorkspaceSet &workspace,
+                   std::vector<FeatureVector> *features) const {
+    feature_extractor_.ExtractFeatures(workspace, obj, args..., features);
+  }
+
+  // Simpler version of GetFeatures(), for cases when there is no opportunity to
+  // reuse computation between feature extractions for the same |obj|, but with
+  // different |args|.  Returns the extracted features.  For more info, see the
+  // doc for GetFeatures().
+  std::vector<FeatureVector> GetFeaturesNoCaching(OBJ *obj,
+                                                  ARGS... args) const {
+    // Technically, we still use a workspace, because
+    // feature_extractor_.ExtractFeatures requires one.  But there is no real
+    // caching here, as we start from scratch for each call to ExtractFeatures.
+    WorkspaceSet workspace;
+    Preprocess(&workspace, obj);
+    std::vector<FeatureVector> features(NumEmbeddings());
+    GetFeatures(*obj, args..., workspace, &features);
+    return features;
+  }
+
+  // Returns number of embedding spaces.
+  int NumEmbeddings() const { return feature_extractor_.NumEmbeddings(); }
+
+ private:
+  // Typed feature extractor for embeddings.
+  EmbeddingFeatureExtractor<EXTRACTOR, OBJ, ARGS...> feature_extractor_;
+
+  // The registry of shared workspaces in the feature extractor.
+  WorkspaceRegistry workspace_registry_;
+};
+
+}  // namespace mobile
+}  // namespace nlp_saft
+
+#endif  // NLP_SAFT_COMPONENTS_COMMON_MOBILE_EMBEDDING_FEATURE_INTERFACE_H_