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// Make sure we include Python.h before any system header
// to avoid _POSIX_C_SOURCE redefinition
#ifdef WITH_PYTHON_LAYER
#include <boost/python.hpp>
#endif
#include <string>
#include "caffe/layer.hpp"
#include "caffe/layer_factory.hpp"
#include "caffe/layers/conv_layer.hpp"
#include "caffe/layers/lrn_layer.hpp"
#include "caffe/layers/pooling_layer.hpp"
#include "caffe/layers/relu_layer.hpp"
#include "caffe/layers/sigmoid_layer.hpp"
#include "caffe/layers/softmax_layer.hpp"
#include "caffe/layers/tanh_layer.hpp"
#include "caffe/proto/caffe.pb.h"
#ifdef USE_CUDNN
#include "caffe/layers/cudnn_conv_layer.hpp"
#include "caffe/layers/cudnn_lcn_layer.hpp"
#include "caffe/layers/cudnn_lrn_layer.hpp"
#include "caffe/layers/cudnn_pooling_layer.hpp"
#include "caffe/layers/cudnn_relu_layer.hpp"
#include "caffe/layers/cudnn_sigmoid_layer.hpp"
#include "caffe/layers/cudnn_softmax_layer.hpp"
#include "caffe/layers/cudnn_tanh_layer.hpp"
#endif
#ifdef WITH_PYTHON_LAYER
#include "caffe/layers/python_layer.hpp"
#endif
namespace caffe {
// Get convolution layer according to engine.
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetConvolutionLayer(
const LayerParameter& param) {
ConvolutionParameter conv_param = param.convolution_param();
ConvolutionParameter_Engine engine = conv_param.engine();
#ifdef USE_CUDNN
bool use_dilation = false;
for (int i = 0; i < conv_param.dilation_size(); ++i) {
if (conv_param.dilation(i) > 1) {
use_dilation = true;
}
}
#endif
if (engine == ConvolutionParameter_Engine_DEFAULT) {
engine = ConvolutionParameter_Engine_CAFFE;
#ifdef USE_CUDNN
if (!use_dilation) {
engine = ConvolutionParameter_Engine_CUDNN;
}
#endif
}
if (engine == ConvolutionParameter_Engine_CAFFE) {
return shared_ptr<Layer<Dtype> >(new ConvolutionLayer<Dtype>(param));
#ifdef USE_CUDNN
} else if (engine == ConvolutionParameter_Engine_CUDNN) {
if (use_dilation) {
LOG(FATAL) << "CuDNN doesn't support the dilated convolution at Layer "
<< param.name();
}
return shared_ptr<Layer<Dtype> >(new CuDNNConvolutionLayer<Dtype>(param));
#endif
} else {
LOG(FATAL) << "Layer " << param.name() << " has unknown engine.";
}
}
REGISTER_LAYER_CREATOR(Convolution, GetConvolutionLayer);
// Get pooling layer according to engine.
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetPoolingLayer(const LayerParameter& param) {
PoolingParameter_Engine engine = param.pooling_param().engine();
if (engine == PoolingParameter_Engine_DEFAULT) {
engine = PoolingParameter_Engine_CAFFE;
#ifdef USE_CUDNN
engine = PoolingParameter_Engine_CUDNN;
#endif
}
if (engine == PoolingParameter_Engine_CAFFE) {
return shared_ptr<Layer<Dtype> >(new PoolingLayer<Dtype>(param));
#ifdef USE_CUDNN
} else if (engine == PoolingParameter_Engine_CUDNN) {
if (param.top_size() > 1) {
LOG(INFO) << "cuDNN does not support multiple tops. "
<< "Using Caffe's own pooling layer.";
return shared_ptr<Layer<Dtype> >(new PoolingLayer<Dtype>(param));
}
// CuDNN assumes layers are not being modified in place, thus
// breaking our index tracking for updates in some cases in Caffe.
// Until there is a workaround in Caffe (index management) or
// cuDNN, use Caffe layer to max pooling, or don't use in place
// layers after max pooling layers
if (param.pooling_param().pool() == PoolingParameter_PoolMethod_MAX) {
return shared_ptr<Layer<Dtype> >(new PoolingLayer<Dtype>(param));
} else {
return shared_ptr<Layer<Dtype> >(new CuDNNPoolingLayer<Dtype>(param));
}
#endif
} else {
LOG(FATAL) << "Layer " << param.name() << " has unknown engine.";
}
}
REGISTER_LAYER_CREATOR(Pooling, GetPoolingLayer);
// Get LRN layer according to engine
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetLRNLayer(const LayerParameter& param) {
LRNParameter_Engine engine = param.lrn_param().engine();
if (engine == LRNParameter_Engine_DEFAULT) {
#ifdef USE_CUDNN
engine = LRNParameter_Engine_CUDNN;
#else
engine = LRNParameter_Engine_CAFFE;
#endif
}
if (engine == LRNParameter_Engine_CAFFE) {
return shared_ptr<Layer<Dtype> >(new LRNLayer<Dtype>(param));
#ifdef USE_CUDNN
} else if (engine == LRNParameter_Engine_CUDNN) {
LRNParameter lrn_param = param.lrn_param();
if (lrn_param.norm_region() ==LRNParameter_NormRegion_WITHIN_CHANNEL) {
return shared_ptr<Layer<Dtype> >(new CuDNNLCNLayer<Dtype>(param));
} else {
// local size is too big to be handled through cuDNN
if (param.lrn_param().local_size() > CUDNN_LRN_MAX_N) {
return shared_ptr<Layer<Dtype> >(new LRNLayer<Dtype>(param));
} else {
return shared_ptr<Layer<Dtype> >(new CuDNNLRNLayer<Dtype>(param));
}
}
#endif
} else {
LOG(FATAL) << "Layer " << param.name() << " has unknown engine.";
}
}
REGISTER_LAYER_CREATOR(LRN, GetLRNLayer);
// Get relu layer according to engine.
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetReLULayer(const LayerParameter& param) {
ReLUParameter_Engine engine = param.relu_param().engine();
if (engine == ReLUParameter_Engine_DEFAULT) {
engine = ReLUParameter_Engine_CAFFE;
#ifdef USE_CUDNN
engine = ReLUParameter_Engine_CUDNN;
#endif
}
if (engine == ReLUParameter_Engine_CAFFE) {
return shared_ptr<Layer<Dtype> >(new ReLULayer<Dtype>(param));
#ifdef USE_CUDNN
} else if (engine == ReLUParameter_Engine_CUDNN) {
return shared_ptr<Layer<Dtype> >(new CuDNNReLULayer<Dtype>(param));
#endif
} else {
LOG(FATAL) << "Layer " << param.name() << " has unknown engine.";
}
}
REGISTER_LAYER_CREATOR(ReLU, GetReLULayer);
// Get sigmoid layer according to engine.
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetSigmoidLayer(const LayerParameter& param) {
SigmoidParameter_Engine engine = param.sigmoid_param().engine();
if (engine == SigmoidParameter_Engine_DEFAULT) {
engine = SigmoidParameter_Engine_CAFFE;
#ifdef USE_CUDNN
engine = SigmoidParameter_Engine_CUDNN;
#endif
}
if (engine == SigmoidParameter_Engine_CAFFE) {
return shared_ptr<Layer<Dtype> >(new SigmoidLayer<Dtype>(param));
#ifdef USE_CUDNN
} else if (engine == SigmoidParameter_Engine_CUDNN) {
return shared_ptr<Layer<Dtype> >(new CuDNNSigmoidLayer<Dtype>(param));
#endif
} else {
LOG(FATAL) << "Layer " << param.name() << " has unknown engine.";
}
}
REGISTER_LAYER_CREATOR(Sigmoid, GetSigmoidLayer);
// Get softmax layer according to engine.
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetSoftmaxLayer(const LayerParameter& param) {
SoftmaxParameter_Engine engine = param.softmax_param().engine();
if (engine == SoftmaxParameter_Engine_DEFAULT) {
engine = SoftmaxParameter_Engine_CAFFE;
#ifdef USE_CUDNN
engine = SoftmaxParameter_Engine_CUDNN;
#endif
}
if (engine == SoftmaxParameter_Engine_CAFFE) {
return shared_ptr<Layer<Dtype> >(new SoftmaxLayer<Dtype>(param));
#ifdef USE_CUDNN
} else if (engine == SoftmaxParameter_Engine_CUDNN) {
return shared_ptr<Layer<Dtype> >(new CuDNNSoftmaxLayer<Dtype>(param));
#endif
} else {
LOG(FATAL) << "Layer " << param.name() << " has unknown engine.";
}
}
REGISTER_LAYER_CREATOR(Softmax, GetSoftmaxLayer);
// Get tanh layer according to engine.
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetTanHLayer(const LayerParameter& param) {
TanHParameter_Engine engine = param.tanh_param().engine();
if (engine == TanHParameter_Engine_DEFAULT) {
engine = TanHParameter_Engine_CAFFE;
#ifdef USE_CUDNN
engine = TanHParameter_Engine_CUDNN;
#endif
}
if (engine == TanHParameter_Engine_CAFFE) {
return shared_ptr<Layer<Dtype> >(new TanHLayer<Dtype>(param));
#ifdef USE_CUDNN
} else if (engine == TanHParameter_Engine_CUDNN) {
return shared_ptr<Layer<Dtype> >(new CuDNNTanHLayer<Dtype>(param));
#endif
} else {
LOG(FATAL) << "Layer " << param.name() << " has unknown engine.";
}
}
REGISTER_LAYER_CREATOR(TanH, GetTanHLayer);
#ifdef WITH_PYTHON_LAYER
template <typename Dtype>
shared_ptr<Layer<Dtype> > GetPythonLayer(const LayerParameter& param) {
Py_Initialize();
try {
bp::object module = bp::import(param.python_param().module().c_str());
bp::object layer = module.attr(param.python_param().layer().c_str())(param);
return bp::extract<shared_ptr<PythonLayer<Dtype> > >(layer)();
} catch (bp::error_already_set) {
PyErr_Print();
throw;
}
}
REGISTER_LAYER_CREATOR(Python, GetPythonLayer);
#endif
// Layers that use their constructor as their default creator should be
// registered in their corresponding cpp files. Do not register them here.
} // namespace caffe