pytorch/binaries/make_mnist_db.cc

/**
 * Copyright (c) 2016-present, Facebook, 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.
 */

// This script converts the MNIST dataset to leveldb.
// The MNIST dataset could be downloaded at
//    http://yann.lecun.com/exdb/mnist/

#include <fstream>  // NOLINT(readability/streams)
#include <string>

#include "caffe2/core/common.h"
#include "caffe2/core/db.h"
#include "caffe2/core/init.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/core/logging.h"

C10_DEFINE_string(image_file, "", "The input image file name.");
C10_DEFINE_string(label_file, "", "The label file name.");
C10_DEFINE_string(output_file, "", "The output db name.");
C10_DEFINE_string(db, "leveldb", "The db type.");
C10_DEFINE_int(
    data_limit,
    -1,
    "If set, only output this number of data points.");
C10_DEFINE_bool(
    channel_first,
    false,
    "If set, write the data as channel-first (CHW order) as the old "
    "Caffe does.");

namespace caffe2 {
uint32_t swap_endian(uint32_t val) {
    val = ((val << 8) & 0xFF00FF00) | ((val >> 8) & 0xFF00FF);
    return (val << 16) | (val >> 16);
}

void convert_dataset(const char* image_filename, const char* label_filename,
        const char* db_path, const int data_limit) {
  // Open files
  std::ifstream image_file(image_filename, std::ios::in | std::ios::binary);
  std::ifstream label_file(label_filename, std::ios::in | std::ios::binary);
  CAFFE_ENFORCE(image_file, "Unable to open file ", image_filename);
  CAFFE_ENFORCE(label_file, "Unable to open file ", label_filename);
  // Read the magic and the meta data
  uint32_t magic;
  uint32_t num_items;
  uint32_t num_labels;
  uint32_t rows;
  uint32_t cols;

  image_file.read(reinterpret_cast<char*>(&magic), 4);
  magic = swap_endian(magic);
  if (magic == 529205256) {
    LOG(FATAL) <<
        "It seems that you forgot to unzip the mnist dataset. You should "
        "first unzip them using e.g. gunzip on Linux.";
  }
  CAFFE_ENFORCE_EQ(magic, 2051, "Incorrect image file magic.");
  label_file.read(reinterpret_cast<char*>(&magic), 4);
  magic = swap_endian(magic);
  CAFFE_ENFORCE_EQ(magic, 2049, "Incorrect label file magic.");
  image_file.read(reinterpret_cast<char*>(&num_items), 4);
  num_items = swap_endian(num_items);
  label_file.read(reinterpret_cast<char*>(&num_labels), 4);
  num_labels = swap_endian(num_labels);
  CAFFE_ENFORCE_EQ(num_items, num_labels);
  image_file.read(reinterpret_cast<char*>(&rows), 4);
  rows = swap_endian(rows);
  image_file.read(reinterpret_cast<char*>(&cols), 4);
  cols = swap_endian(cols);

  // leveldb
  std::unique_ptr<db::DB> mnist_db(db::CreateDB(FLAGS_db, db_path, db::NEW));
  std::unique_ptr<db::Transaction> transaction(mnist_db->NewTransaction());
  // Storing to db
  char label_value;
  std::vector<char> pixels(rows * cols);
  int count = 0;
  const int kMaxKeyLength = 11;
  char key_cstr[kMaxKeyLength];

  TensorProtos protos;
  TensorProto* data = protos.add_protos();
  TensorProto* label = protos.add_protos();
  data->set_data_type(TensorProto::BYTE);
  if (FLAGS_channel_first) {
    data->add_dims(1);
    data->add_dims(rows);
    data->add_dims(cols);
  } else {
    data->add_dims(rows);
    data->add_dims(cols);
    data->add_dims(1);
  }
  label->set_data_type(TensorProto::INT32);
  label->add_int32_data(0);

  LOG(INFO) << "A total of " << num_items << " items.";
  LOG(INFO) << "Rows: " << rows << " Cols: " << cols;
  for (int item_id = 0; item_id < num_items; ++item_id) {
    image_file.read(pixels.data(), rows * cols);
    label_file.read(&label_value, 1);
    for (int i = 0; i < rows * cols; ++i) {
      data->set_byte_data(pixels.data(), rows * cols);
    }
    label->set_int32_data(0, static_cast<int>(label_value));
    snprintf(key_cstr, kMaxKeyLength, "%08d", item_id);
    string keystr(key_cstr);

    // Put in db
    transaction->Put(keystr, protos.SerializeAsString());
    if (++count % 1000 == 0) {
      transaction->Commit();
    }
    if (data_limit > 0 && count == data_limit) {
      LOG(INFO) << "Reached data limit of " << data_limit << ", stop.";
      break;
    }
  }
}
}  // namespace caffe2

int main(int argc, char** argv) {
  caffe2::GlobalInit(&argc, &argv);
  caffe2::convert_dataset(
      FLAGS_image_file.c_str(),
      FLAGS_label_file.c_str(),
      FLAGS_output_file.c_str(),
      FLAGS_data_limit);
  return 0;
}