1 #ifndef CAFFE_CONTRASTIVE_LOSS_LAYER_HPP_ 2 #define CAFFE_CONTRASTIVE_LOSS_LAYER_HPP_ 6 #include "caffe/blob.hpp" 7 #include "caffe/layer.hpp" 8 #include "caffe/proto/caffe.pb.h" 10 #include "caffe/layers/loss_layer.hpp" 38 template <
typename Dtype>
47 virtual inline const char*
type()
const {
return "ContrastiveLoss"; }
53 return bottom_index != 2;
89 const vector<bool>& propagate_down,
const vector<
Blob<Dtype>*>& bottom);
91 const vector<bool>& propagate_down,
const vector<
Blob<Dtype>*>& bottom);
101 #endif // CAFFE_CONTRASTIVE_LOSS_LAYER_HPP_ A layer factory that allows one to register layers. During runtime, registered layers can be called b...
Definition: blob.hpp:14
virtual const char * type() const
Returns the layer type.
Definition: contrastive_loss_layer.hpp:47
virtual int ExactNumBottomBlobs() const
Returns the exact number of bottom blobs required by the layer, or -1 if no exact number is required...
Definition: contrastive_loss_layer.hpp:46
virtual void Forward_gpu(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Using the GPU device, compute the layer output. Fall back to Forward_cpu() if unavailable.
virtual bool AllowForceBackward(const int bottom_index) const
Definition: contrastive_loss_layer.hpp:52
virtual void Forward_cpu(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Computes the contrastive loss where . This can be used to train siamese networks.
Definition: contrastive_loss_layer.cpp:31
virtual void Backward_gpu(const vector< Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > *> &bottom)
Using the GPU device, compute the gradients for any parameters and for the bottom blobs if propagate_...
An interface for Layers that take two Blobs as input – usually (1) predictions and (2) ground-truth ...
Definition: loss_layer.hpp:23
Computes the contrastive loss where . This can be used to train siamese networks.
Definition: contrastive_loss_layer.hpp:39
virtual void LayerSetUp(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Does layer-specific setup: your layer should implement this function as well as Reshape.
Definition: contrastive_loss_layer.cpp:10
virtual void Backward_cpu(const vector< Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > *> &bottom)
Computes the Contrastive error gradient w.r.t. the inputs.
Definition: contrastive_loss_layer.cpp:65
A wrapper around SyncedMemory holders serving as the basic computational unit through which Layers...
Definition: blob.hpp:24