lppl
v2.0.0
|
Functions | |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | apply_record_effect (pp_t< I, O, Ts... > &f, record_interpretation interp) |
template<typename D , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | block (pp_t< I, O, Ts... > &&f, std::string address) |
template<typename D , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | block (pp_t< I, O, Ts... > &f, std::string address) |
Converts the site at the passed address, if it exists, into untraced randomnes. | |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | block_observe (pp_t< I, O, Ts... > &&f) |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | block_observe (pp_t< I, O, Ts... > &f) |
Blocks all observe sites. This could be useful for converting a probabilistic program into a proposal kernel. | |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | block_sample (pp_t< I, O, Ts... > &&f) |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | block_sample (pp_t< I, O, Ts... > &f) |
Blocks all sample sites. This could be useful for performing a stochastic optimization task. | |
template<typename D , typename V , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | condition (pp_t< I, O, Ts... > &&f, std::string address, V value) |
template<typename D , typename V , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | condition (pp_t< I, O, Ts... > &&f, std::unordered_map< std::string, V > &&map_) |
template<typename D , typename V , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | condition (pp_t< I, O, Ts... > &f, std::string address, V value) |
Conditions the site at the address, if it exists, to be observed at the passed value. | |
template<typename D , typename V , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | condition (pp_t< I, O, Ts... > &f, std::unordered_map< std::string, V > map_) |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | replace (pp_t< I, O, Ts... > &&f) |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | replace (pp_t< I, O, Ts... > &f) |
Replaces probabilistic program-specified distributions with the distributions in any subsequently passed record. | |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | replay (pp_t< I, O, Ts... > &&f) |
template<typename D , typename V , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | replay (pp_t< I, O, Ts... > &&f, std::string address, V value) |
template<typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | replay (pp_t< I, O, Ts... > &f) |
Replays any subsequently passed record through the program. | |
template<typename D , typename V , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | replay (pp_t< I, O, Ts... > &f, std::string address, V value) |
Replays the passed value through the model at the site at the passed address, if it exists. | |
template<typename D , typename V , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | set_in_place_effect (pp_t< I, O, Ts... > f, std::string address, V value, node_interpretation interp) |
template<typename D , typename V , typename I , typename O , typename... Ts> | |
pp_t< I, O, Ts... > | set_in_place_effect (pp_t< I, O, Ts... > f, std::unordered_map< std::string, V > map_, node_interpretation interp) |
This file is part of fmcs. Copyright David Rushing Dewhurst, 2022 - present. Some rights reserved.