///////////////////////////////////////////////////////////////////////

// File:        par_control.cpp

// Description: Control code for parallel implementation.

// Author:      Ray Smith

//

// (C) Copyright 2013, 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.

//

///////////////////////////////////////////////////////////////////////

#include "tesseractclass.h"

#ifdef _OPENMP

#  include <omp.h>

#endif // _OPENMP

namespace tesseract {

struct BlobData {

  BlobData() = default;

  BlobData(int index, Tesseract *tess, const WERD_RES &word)

      : blob(word.chopped_word->blobs[index])

      , tesseract(tess)

      , choices(&(*word.ratings)(index, index)) {}

  TBLOB *blob = nullptr;

  Tesseract *tesseract = nullptr;

  BLOB_CHOICE_LIST **choices = nullptr;

};

void Tesseract::PrerecAllWordsPar(const std::vector<WordData> &words) {

  // Prepare all the blobs.

  std::vector<BlobData> blobs;

  for (const auto &w : words) {

    if (w.word->ratings != nullptr && w.word->ratings->get(0, 0) == nullptr) {

      for (size_t s = 0; s < w.lang_words.size(); ++s) {

        Tesseract *sub = s < sub_langs_.size() ? sub_langs_[s] : this;

        const WERD_RES &word = *w.lang_words[s];

        for (unsigned b = 0; b < word.chopped_word->NumBlobs(); ++b) {

          blobs.emplace_back(b, sub, word);

        }

      }

    }

  }

  // Pre-classify all the blobs.

  if (tessedit_parallelize > 1) {

#ifdef _OPENMP

#  pragma omp parallel for num_threads(10)

#endif // _OPENMP

    // NOLINTNEXTLINE(modernize-loop-convert)

    for (size_t b = 0; b < blobs.size(); ++b) {

      *blobs[b].choices =

          blobs[b].tesseract->classify_blob(blobs[b].blob, "par", ScrollView::WHITE, nullptr);

    }

  } else {

    // TODO(AMD) parallelize this.

    for (auto &blob : blobs) {

      *blob.choices = blob.tesseract->classify_blob(blob.blob, "par", ScrollView::WHITE, nullptr);

    }

  }

}

} // namespace tesseract.