var_desc.h 3.5 KB
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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. */

#pragma once

#include <vector>
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#include "glog/logging.h"
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#include "paddle/fluid/framework/framework.pb.h"
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namespace paddle {
namespace framework {

// convert between std::vector and protobuf repeated.
template <typename T>
inline std::vector<T> RepeatedToVector(
    const google::protobuf::RepeatedField<T> &repeated_field) {
  std::vector<T> ret;
  ret.reserve(repeated_field.size());
  std::copy(repeated_field.begin(), repeated_field.end(),
            std::back_inserter(ret));
  return ret;
}

template <typename T, typename RepeatedField>
inline void VectorToRepeated(const std::vector<T> &vec,
                             RepeatedField *repeated_field) {
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  repeated_field->Clear();
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  repeated_field->Reserve(vec.size());
  for (const auto &elem : vec) {
    *repeated_field->Add() = elem;
  }
}

// Specialize vector<bool>.
template <typename RepeatedField>
inline void VectorToRepeated(const std::vector<bool> &vec,
                             RepeatedField *repeated_field) {
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  repeated_field->Clear();
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  repeated_field->Reserve(vec.size());
  for (auto elem : vec) {
    *repeated_field->Add() = elem;
  }
}

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class VarDesc {
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 public:
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  explicit VarDesc(const std::string &name) {
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    desc_.set_name(name);
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    desc_.mutable_type()->set_type(proto::VarType::LOD_TENSOR);
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  }
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  explicit VarDesc(const proto::VarDesc &desc) : desc_(desc) {}
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  proto::VarDesc *Proto() { return &desc_; }
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  std::string Name() const { return desc_.name(); }

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  void SetName(std::string name) { desc_.set_name(name); }

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  void SetTensorDescNum(size_t num);

  size_t GetTensorDescNum() const;

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  void SetShape(const std::vector<int64_t> &dims);

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  void SetShapes(const std::vector<std::vector<int64_t>> &multiple_dims);
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  std::vector<int64_t> GetShape() const;

  std::vector<std::vector<int64_t>> GetShapes() const;

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  void SetDataType(proto::VarType::Type data_type);
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  void SetDataTypes(
      const std::vector<proto::VarType::Type> &multiple_data_type);
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  void SetCapacity(int64_t capacity);

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  proto::VarType::Type GetDataType() const;
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  std::vector<proto::VarType::Type> GetDataTypes() const;
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  void SetLoDLevel(int32_t lod_level);

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  void SetLoDLevels(const std::vector<int32_t> &multiple_lod_level);

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  int32_t GetLoDLevel() const;
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  std::vector<int32_t> GetLoDLevels() const;

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  proto::VarType::Type GetType() const;
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  void SetType(proto::VarType::Type type);
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  bool Persistable() const { return desc_.persistable(); }

  void SetPersistable(bool persistable) { desc_.set_persistable(persistable); }

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 private:
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  const proto::VarType::ChannelDesc &channel_desc() const;
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  const proto::VarType::TensorDesc &tensor_desc() const;
  std::vector<proto::VarType::TensorDesc> tensor_descs() const;
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  proto::VarType::ChannelDesc *mutable_channel_desc();
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  proto::VarType::TensorDesc *mutable_tensor_desc();
  std::vector<proto::VarType::TensorDesc *> mutable_tensor_descs();
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  proto::VarDesc desc_;
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};
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}  // namespace framework
}  // namespace paddle