pytorch

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/**
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 * Copyright (c) 2016-present, Facebook, Inc.
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 *
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 * Licensed under the Apache License, Version 2.0 (the "License");
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 * you may not use this file except in compliance with the License.
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 * You may obtain a copy of the License at
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 *
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 *     http://www.apache.org/licenses/LICENSE-2.0
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 *
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 * Unless required by applicable law or agreed to in writing, software
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 * distributed under the License is distributed on an "AS IS" BASIS,
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 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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 * See the License for the specific language governing permissions and
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 * limitations under the License.
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 */
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#include "caffe2/core/db.h"
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#include "caffe2/core/init.h"
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#include "caffe2/proto/caffe2_pb.h"
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#include "caffe2/proto/caffe2_legacy.pb.h"
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#include "caffe2/core/logging.h"
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C10_DEFINE_string(input_db, "", "The input db.");
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C10_DEFINE_string(input_db_type, "", "The input db type.");
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C10_DEFINE_string(output_db, "", "The output db.");
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C10_DEFINE_string(output_db_type, "", "The output db type.");
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C10_DEFINE_int(batch_size, 1000, "The write batch size.");
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using caffe2::db::Cursor;
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using caffe2::db::DB;
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using caffe2::db::Transaction;
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using caffe2::CaffeDatum;
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using caffe2::TensorProto;
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using caffe2::TensorProtos;
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int main(int argc, char** argv) {
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  caffe2::GlobalInit(&argc, &argv);
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  std::unique_ptr<DB> in_db(caffe2::db::CreateDB(
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      FLAGS_input_db_type, FLAGS_input_db, caffe2::db::READ));
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  std::unique_ptr<DB> out_db(caffe2::db::CreateDB(
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      FLAGS_output_db_type, FLAGS_output_db, caffe2::db::NEW));
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  std::unique_ptr<Cursor> cursor(in_db->NewCursor());
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  std::unique_ptr<Transaction> transaction(out_db->NewTransaction());
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  int count = 0;
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  for (; cursor->Valid(); cursor->Next()) {
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    CaffeDatum datum;
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    CAFFE_ENFORCE(datum.ParseFromString(cursor->value()));
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    TensorProtos protos;
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    TensorProto* data = protos.add_protos();
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    TensorProto* label = protos.add_protos();
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    label->set_data_type(TensorProto::INT32);
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    label->add_dims(1);
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    label->add_int32_data(datum.label());
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    if (datum.encoded()) {
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      // This is an encoded image. we will copy over the data directly.
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      data->set_data_type(TensorProto::STRING);
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      data->add_dims(1);
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      data->add_string_data(datum.data());
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    } else {
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      // float data not supported right now.
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      CAFFE_ENFORCE_EQ(datum.float_data_size(), 0);
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      std::vector<char> buffer_vec(datum.data().size());
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      char* buffer = buffer_vec.data();
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      // swap order from CHW to HWC
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      int channels = datum.channels();
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      int size = datum.height() * datum.width();
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      CAFFE_ENFORCE_EQ(datum.data().size(), channels * size);
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      for (int c = 0; c < channels; ++c) {
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        char* dst = buffer + c;
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        const char* src = datum.data().c_str() + c * size;
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        for (int n = 0; n < size; ++n) {
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          dst[n*channels] = src[n];
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        }
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      }
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      data->set_data_type(TensorProto::BYTE);
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      data->add_dims(datum.height());
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      data->add_dims(datum.width());
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      data->add_dims(datum.channels());
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      data->set_byte_data(buffer, datum.data().size());
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    }
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    transaction->Put(cursor->key(), SerializeAsString_EnforceCheck(protos));
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    if (++count % FLAGS_batch_size == 0) {
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      transaction->Commit();
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      LOG(INFO) << "Converted " << count << " items so far.";
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    }
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  }
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  LOG(INFO) << "A total of " << count << " items processed.";
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  return 0;
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}
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