/usr/include/torch/ClassNLLCriterion.h is in libtorch3-dev 3.1-2.1build1.
This file is owned by root:root, with mode 0o644.
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//
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#ifndef CLASS_NLL_CRITERION_INC
#define CLASS_NLL_CRITERION_INC
#include "Criterion.h"
#include "ClassFormat.h"
namespace Torch {
/** This criterion can be used to train *in classification* a #GradientMachine#
object using the #StochasticGradient# trainer. It then maximizes the log
likelihood of the data.
If we write $o_i$ for the output $i$ of the #GradientMachine#, it supposes that
\begin{itemize}
\item the outputs $o_i$ are log-probabilities.
\item $exp(o_i)$ is the probability for the class $i$
\item the predicted class follows a multinomial distribution with parameters
$(exp(o_1), exp(o_2), exp(o_3)...)$
\end{itemize}
The number of target frames in #DataSet# must
correspond to the number of input frames given
to this criterion.
@author Ronan Collobert (collober@idiap.ch)
*/
class ClassNLLCriterion : public Criterion
{
public:
ClassFormat *class_format;
/// The ClassFormat is needed just to know how the targets are encoded in the dataset.
ClassNLLCriterion(ClassFormat *class_format);
virtual void frameForward(int t, real *f_inputs, real *f_outputs);
virtual void frameBackward(int t, real *f_inputs, real *beta_, real *f_outputs, real *alpha_);
virtual ~ClassNLLCriterion();
};
}
#endif
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