Sync of lib2 to AOSP.
Model comes from experiment: 2524_BoundsEnglishv5_R1
Bug: 68239358
Test: Builds & tested on device.
Change-Id: I65cb7f0b067b68e3e1c22ee87232555887446089
diff --git a/cached-features.h b/cached-features.h
new file mode 100644
index 0000000..5ffb9a9
--- /dev/null
+++ b/cached-features.h
@@ -0,0 +1,74 @@
+/*
+ * Copyright (C) 2017 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 KNOWLEDGE_CEREBRA_SENSE_TEXT_CLASSIFIER_LIB2_CACHED_FEATURES_H_
+#define KNOWLEDGE_CEREBRA_SENSE_TEXT_CLASSIFIER_LIB2_CACHED_FEATURES_H_
+
+#include <memory>
+#include <vector>
+
+#include "model-executor.h"
+#include "model_generated.h"
+#include "types.h"
+
+namespace libtextclassifier2 {
+
+// Holds state for extracting features across multiple calls and reusing them.
+// Assumes that features for each Token are independent.
+class CachedFeatures {
+ public:
+ CachedFeatures(
+ const TokenSpan& extraction_span,
+ const std::vector<std::vector<int>>& sparse_features,
+ const std::vector<std::vector<float>>& dense_features,
+ const std::vector<int>& padding_sparse_features,
+ const std::vector<float>& padding_dense_features,
+ const FeatureProcessorOptions_::BoundsSensitiveFeatures* config,
+ EmbeddingExecutor* embedding_executor, int feature_vector_size);
+
+ // Gets a vector of features for the given token span.
+ std::vector<float> Get(TokenSpan selected_span) const;
+
+ private:
+ // Appends token features to the output. The intended_span specifies which
+ // tokens' features should be used in principle. The read_mask_span restricts
+ // which tokens are actually read. For tokens outside of the read_mask_span,
+ // padding tokens are used instead.
+ void AppendFeatures(const TokenSpan& intended_span,
+ const TokenSpan& read_mask_span,
+ std::vector<float>* output_features) const;
+
+ // Appends features of one padding token to the output.
+ void AppendPaddingFeatures(std::vector<float>* output_features) const;
+
+ // Appends the features of tokens from the given span to the output. The
+ // features are summed so that the appended features have the size
+ // corresponding to one token.
+ void AppendSummedFeatures(const TokenSpan& summing_span,
+ std::vector<float>* output_features) const;
+
+ int NumFeaturesPerToken() const;
+
+ const TokenSpan extraction_span_;
+ const FeatureProcessorOptions_::BoundsSensitiveFeatures* config_;
+ int output_features_size_;
+ std::vector<float> features_;
+ std::vector<float> padding_features_;
+};
+
+} // namespace libtextclassifier2
+
+#endif // KNOWLEDGE_CEREBRA_SENSE_TEXT_CLASSIFIER_LIB2_CACHED_FEATURES_H_