2 #ifndef BLACKCAT_NEURALNETWORK_UNARYFUNCTION_H_     3 #define BLACKCAT_NEURALNETWORK_UNARYFUNCTION_H_    18         Function<SystemTag, ValueType, Functor, InputDimension>,
    19         Tensor_Descriptor<ValueType, SystemTag, InputDimension>>
    39     template<
class Matrix>
    44     template<
class X, 
class Delta>
    46         return function.dx(x) % dy;
    51 template<
class ValueType, 
class SystemTag, 
class Functor>
    56 template<
class SystemTag, 
class Functor>
    57 auto function(SystemTag 
system_tag, 
int inputs, Functor 
function=Functor()) {
    62 template<
class ValueType, 
class SystemTag, 
class Functor, 
int X>
    67 template<
class SystemTag, 
class Functor, 
int X>
 
bc::Dim< input_tensor_dim::value > shape_type
Definition: layer_base.h:95
SystemTag system_tag
Definition: unaryfunction.h:21
const char * bc_get_classname_of(const T &arg)
Definition: common.h:330
Definition: constexpr_int.h:14
Definition: layer_base.h:86
auto forward_propagation(const Matrix &x)
Definition: unaryfunction.h:40
ValueType value_type
Definition: unaryfunction.h:22
Function(shape_type inputs, Functor function=Functor())
Definition: unaryfunction.h:35
InputDimension input_tensor_dim
Definition: unaryfunction.h:28
Functor function
Definition: unaryfunction.h:33
BCINLINE auto shape(Integers... ints)
Definition: shape.h:264
InputDimension output_tensor_dim
Definition: unaryfunction.h:29
Definition: unaryfunction.h:16
auto back_propagation(const X &x, const Delta &dy)
Definition: unaryfunction.h:45
The Evaluator determines if an expression needs to be greedily optimized. 
Definition: algorithms.h:22
Definition: recycle_allocator.h:57