src/python/swig/model_layer.i

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/*interface file for swig */

%module model_layer
%include "std_vector.i"
%include "std_string.i"
%include "std_pair.i"
%include "std_shared_ptr.i"


%{
#include "singa/model/layer.h"
#include "../src/model/layer/rnn.h"
#include "../src/model/layer/cudnn_rnn.h"
#include "singa/core/tensor.h"
#include "singa/proto/model.pb.h"
#include "singa/singa_config.h"
using singa::Tensor;
using singa::ParamSpec;
using singa::DataType;
using singa::Device;
using singa::LayerConf;
%}

%shared_ptr(singa::Layer)
%shared_ptr(singa::RNN)
#if USE_CUDNN
%shared_ptr(singa::CudnnRNN)
#endif

namespace std {
  %template(strVector) vector<string>;
  %template(paramVector) vector<singa::ParamSpec>;
  %template(tensorVector) vector<singa::Tensor>;
  %template(ttvecPair) pair<singa::Tensor, vector<singa::Tensor>>;
  %template(tvecPair) pair<vector<singa::Tensor>, vector<singa::Tensor>>;
}


namespace singa {

class Layer {
  public:
    Layer();
//      virtual void Setup(const std::vector<vector<size_t>>&, const string&);
    void Setup(const std::vector<size_t>& in_sample_shape,
                        const std::string& proto_str);
    virtual const std::vector<Tensor> param_values();
    virtual const std::vector<size_t> GetOutputSampleShape() const;
    virtual void ToDevice(std::shared_ptr<Device> device);
    virtual void AsType(DataType dtype);
    virtual const Tensor Forward(int flag, const Tensor& input);
    virtual const std::vector<Tensor> Forward(
        int flag, const std::vector<Tensor>& inputs);
    virtual const std::pair<Tensor, std::vector<Tensor>> Backward(
        int flag, const Tensor& grad);
    virtual const std::pair<std::vector<Tensor>, std::vector<Tensor>>
    Backward(int flag, const vector<Tensor>& grads);
};

std::shared_ptr<Layer> CreateLayer(const std::string& type);
const std::vector<std::string> GetRegisteredLayers();
class RNN : public Layer {
};

#if USE_CUDA && USE_CUDNN
#if CUDNN_VERSION_SWIG >= 5005
class CudnnRNN : public RNN {
 public:
 // note: Must use std::vector instead of vector.
  const std::vector<Tensor> Forward(int flag, const std::vector<Tensor>& inputs) override;
  const std::pair<std::vector<Tensor>, std::vector<Tensor>> Backward(
      int flag, const std::vector<Tensor>& grads) override;
  void ToDevice(std::shared_ptr<Device> device) override;
    const std::vector<Tensor> param_values() override;
    const std::vector<size_t> GetOutputSampleShape() const override;
};

#endif  // CUDNN_VERSION_SWIG >= 5005
#endif  // USE_CUDA && USE_CUDNN
}