ALP User Documentation
0.8.preview
Algebraic Programming User Documentation
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Implements (non-batched) sparse neural network inference. More...
Go to the source code of this file.
Namespaces | |
grb | |
The ALP/GraphBLAS namespace. | |
grb::algorithms | |
The namespace for ALP/GraphBLAS algorithms. | |
Functions | |
template<Descriptor descr = descriptors::no_operation, typename IOType , typename WeightType , typename BiasType , class ReluMonoid = Monoid< grb::operators::relu< IOType >, grb::identities::negative_infinity >, class Ring = Semiring< grb::operators::add< IOType >, grb::operators::mul< IOType >, grb::identities::zero, grb::identities::one >> | |
grb::RC | sparse_nn_single_inference (grb::Vector< IOType > &out, const grb::Vector< IOType > &in, const std::vector< grb::Matrix< WeightType > > &layers, const std::vector< BiasType > &biases, grb::Vector< IOType > &temp, const ReluMonoid &relu=ReluMonoid(), const Ring &ring=Ring()) |
Performs an inference step of a single data element through a Sparse Neural Network defined by num_layers sparse weight matrices and num_layers biases. More... | |
template<Descriptor descr = descriptors::no_operation, typename IOType , typename WeightType , typename BiasType , typename ThresholdType = IOType, class MinMonoid = Monoid< grb::operators::min< IOType >, grb::identities::infinity >, class ReluMonoid = Monoid< grb::operators::relu< IOType >, grb::identities::negative_infinity >, class Ring = Semiring< grb::operators::add< IOType >, grb::operators::mul< IOType >, grb::identities::zero, grb::identities::one >> | |
grb::RC | sparse_nn_single_inference (grb::Vector< IOType > &out, const grb::Vector< IOType > &in, const std::vector< grb::Matrix< WeightType > > &layers, const std::vector< BiasType > &biases, const ThresholdType threshold, grb::Vector< IOType > &temp, const ReluMonoid &relu=ReluMonoid(), const MinMonoid &min=MinMonoid(), const Ring &ring=Ring()) |
Performs an inference step of a single data element through a Sparse Neural Network defined by num_layers sparse weight matrices and num_layers biases. More... | |
Implements (non-batched) sparse neural network inference.