1 #ifndef CAFFE_MULTINOMIAL_LOGISTIC_LOSS_LAYER_HPP_ 2 #define CAFFE_MULTINOMIAL_LOGISTIC_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" 43 template <
typename Dtype>
51 virtual inline const char*
type()
const {
return "MultinomialLogisticLoss"; }
87 const vector<bool>& propagate_down,
const vector<
Blob<Dtype>*>& bottom);
92 #endif // CAFFE_MULTINOMIAL_LOGISTIC_LOSS_LAYER_HPP_ virtual void Forward_cpu(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Computes the multinomial logistic loss for a one-of-many classification task, directly taking a predi...
Definition: multinomial_logistic_loss_layer.cpp:20
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: multinomial_logistic_loss_layer.hpp:51
Computes the multinomial logistic loss for a one-of-many classification task, directly taking a predi...
Definition: multinomial_logistic_loss_layer.hpp:44
virtual void Reshape(const vector< Blob< Dtype > *> &bottom, const vector< Blob< Dtype > *> &top)
Adjust the shapes of top blobs and internal buffers to accommodate the shapes of the bottom blobs...
Definition: multinomial_logistic_loss_layer.cpp:11
virtual void Backward_cpu(const vector< Blob< Dtype > *> &top, const vector< bool > &propagate_down, const vector< Blob< Dtype > *> &bottom)
Computes the multinomial logistic loss error gradient w.r.t. the predictions.
Definition: multinomial_logistic_loss_layer.cpp:37
An interface for Layers that take two Blobs as input – usually (1) predictions and (2) ground-truth ...
Definition: loss_layer.hpp:23
A wrapper around SyncedMemory holders serving as the basic computational unit through which Layers...
Definition: blob.hpp:24