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// Copyright 2016 Google Inc.
//
// 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 TRAINER_INTERFACE_H_
#define TRAINER_INTERFACE_H_
#include <algorithm>
#include <map>
#include <memory>
#include <string>
#include <utility>
#include <vector>
#include "common.h"
#include "filesystem.h"
#include "sentencepiece_model.pb.h"
#include "sentencepiece_processor.h"
#include "sentencepiece_trainer.h"
#include "third_party/absl/container/flat_hash_map.h"
#include "util.h"
namespace sentencepiece {
template <typename K, typename V>
std::vector<std::pair<K, V>> Sorted(const std::vector<std::pair<K, V>> &m) {
std::vector<std::pair<K, V>> v = m;
std::sort(v.begin(), v.end(),
[](const std::pair<K, V> &p1, const std::pair<K, V> &p2) {
return (p1.second > p2.second ||
(p1.second == p2.second && p1.first < p2.first));
});
return v;
}
template <typename K, typename V>
std::vector<std::pair<K, V>> Sorted(const absl::flat_hash_map<K, V> &m) {
std::vector<std::pair<K, V>> v(m.begin(), m.end());
return Sorted(v);
}
class MultiFileSentenceIterator : public SentenceIterator {
public:
explicit MultiFileSentenceIterator(const std::vector<std::string> &files);
~MultiFileSentenceIterator() {}
bool done() const override;
void Next() override;
const std::string &value() const override { return value_; }
util::Status status() const override;
private:
void TryRead();
bool read_done_ = false;
size_t file_index_ = 0;
std::vector<std::string> files_;
std::string value_;
std::unique_ptr<filesystem::ReadableFile> fp_;
};
// Base trainer class
class TrainerInterface {
public:
using Sentence = std::pair<std::string, int64_t>;
using Sentences = std::vector<Sentence>;
static const char32 kWSChar;
static const char32 kUNKChar;
static const char32 kUPPBoundaryChar;
static const char kWSStr[];
static const char kUNKStr[];
static const char kUPPBoundaryStr[];
TrainerInterface(const TrainerSpec &trainer_spec,
const NormalizerSpec &normalizer_spec,
const NormalizerSpec &denormalizer_spec);
virtual ~TrainerInterface();
// Loads sentence from `sentence_iterator` and stores the model
// to `output_model_proto`.
virtual util::Status Train(SentenceIterator *sentence_iterator,
ModelProto *output_model_proto) {
sentence_iterator_ = sentence_iterator;
output_model_proto_ = output_model_proto;
return Train();
}
virtual util::Status Train() { return status(); }
virtual util::Status status() const { return status_; }
FRIEND_TEST(TrainerInterfaceTest, IsValidSentencePieceTest);
FRIEND_TEST(TrainerInterfaceTest, OverrideSpecialPiecesTest);
FRIEND_TEST(TrainerInterfaceTest, BytePiecesTest);
FRIEND_TEST(TrainerInterfaceTest, SerializeTest);
FRIEND_TEST(TrainerInterfaceTest, CharactersTest);
// Loads all sentences from spec.input() or SentenceIterator.
// It loads at most input_sentence_size sentences.
util::Status LoadSentences();
protected:
// Returns true if |piece| is valid sentence piece.
// The result is affected by
// max_sentencepiece_length, split_by_whiespace, split_by_unicode_script.
bool IsValidSentencePiece(const string_util::UnicodeText &piece) const;
// Splits all sentencecs by whitespaces and
// replace the |sentences_| with tokenized string.
// e.g.,
// [ ["hello world ", 1], ["hi world]" ] =>
// [ ["hello", 1], ["hi", 1], ["world", 2] ]
void SplitSentencesByWhitespace();
// Save model files into spec.model_prefix().
util::Status Save() const;
// Set of characters which must be included in the final vocab.
// The value of this map stores the frequency.
absl::flat_hash_map<char32, int64_t> required_chars_;
// Final output pieces
std::vector<std::pair<std::string, float>> final_pieces_;
// All sentences.
Sentences sentences_;
// Trainer spec.
TrainerSpec trainer_spec_;
// Normalizer spec
NormalizerSpec normalizer_spec_;
// Denormalizer spec
NormalizerSpec denormalizer_spec_;
// Reserved control pieces. e.g., <unk>, <s>, </s>.
// key is vocab id.
std::map<int, std::pair<std::string, ModelProto::SentencePiece::Type>>
meta_pieces_;
// Detect errors on initialization.
util::Status status_;
// Loads sentences from SentenceIterator if not null.
SentenceIterator *sentence_iterator_ = nullptr;
// Emits model to this proto instead of file.
ModelProto *output_model_proto_ = nullptr;
private:
// Serialize final_pieces_ to |model_proto|.
util::Status Serialize(ModelProto *model_proto) const;
// Saves the best sentence split with the current model for debugging.
util::Status SaveSplits(absl::string_view filename) const;
// Saves model file.
util::Status SaveModel(absl::string_view filename) const;
// Saves vocabulary file for NMT.
util::Status SaveVocab(absl::string_view filename) const;
// Initializes `meta_pieces_` from TrainerSpec.
util::Status InitMetaPieces();
// Randomly sampled raw sentences for self-testing.
std::vector<std::string> self_test_samples_;
};
} // namespace sentencepiece
#endif // TRAINER_INTERFACE_H_
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