rmontanana/BayesNet
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Change cpt table type to float

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This commit is contained in:
Ricardo Montañana Gómez 2024-07-08 13:27:55 +02:00
parent 35ca862eca
commit 0bbc8328a9
Signed by: rmontanana
GPG Key ID: 46064262FD9A7ADE
2 changed files with 5 additions and 5 deletions
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8
bayesnet/network/Node.cc
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@ -97,7 +97,7 @@ namespace bayesnet {
dimensions.push_back(numStates); dimensions.push_back(numStates);
transform(parents.begin(), parents.end(), back_inserter(dimensions), [](const auto& parent) { return parent->getNumStates(); }); transform(parents.begin(), parents.end(), back_inserter(dimensions), [](const auto& parent) { return parent->getNumStates(); });
// Create a tensor of zeros with the dimensions of the CPT // Create a tensor of zeros with the dimensions of the CPT
cpTable = torch::zeros(dimensions, torch::kFloat) + smoothing; cpTable = torch::zeros(dimensions, torch::kDouble) + smoothing;
// Fill table with counts // Fill table with counts
auto pos = find(features.begin(), features.end(), name); auto pos = find(features.begin(), features.end(), name);
if (pos == features.end()) { if (pos == features.end()) {
@ -118,19 +118,19 @@ namespace bayesnet {
coordinates.push_back(sample[parent_index]); coordinates.push_back(sample[parent_index]);
} }
// Increment the count of the corresponding coordinate // Increment the count of the corresponding coordinate
cpTable.index_put_({ coordinates }, cpTable.index({ coordinates }) + weights.index({ n_sample }).item<double>()); cpTable.index_put_({ coordinates }, weights.index({ n_sample }), true);
} }
// Normalize the counts // Normalize the counts
// Divide each row by the sum of the row // Divide each row by the sum of the row
cpTable = cpTable / cpTable.sum(0); cpTable = cpTable / cpTable.sum(0);
} }
float Node::getFactorValue(std::map<std::string, int>& evidence) double Node::getFactorValue(std::map<std::string, int>& evidence)
{ {
c10::List<c10::optional<at::Tensor>> coordinates; c10::List<c10::optional<at::Tensor>> coordinates;
// following predetermined order of indices in the cpTable (see Node.h) // following predetermined order of indices in the cpTable (see Node.h)
coordinates.push_back(at::tensor(evidence[name])); coordinates.push_back(at::tensor(evidence[name]));
transform(parents.begin(), parents.end(), std::back_inserter(coordinates), [&evidence](const auto& parent) { return at::tensor(evidence[parent->getName()]); }); transform(parents.begin(), parents.end(), std::back_inserter(coordinates), [&evidence](const auto& parent) { return at::tensor(evidence[parent->getName()]); });
return cpTable.index({ coordinates }).item<float>(); return cpTable.index({ coordinates }).item<double>();
} }
std::vector<std::string> Node::graph(const std::string& className) std::vector<std::string> Node::graph(const std::string& className)
{ {

2
bayesnet/network/Node.h
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@ -28,7 +28,7 @@ namespace bayesnet {
void setNumStates(int); void setNumStates(int);
unsigned minFill(); unsigned minFill();
std::vector<std::string> graph(const std::string& clasName); // Returns a std::vector of std::strings representing the graph in graphviz format std::vector<std::string> graph(const std::string& clasName); // Returns a std::vector of std::strings representing the graph in graphviz format
float getFactorValue(std::map<std::string, int>&); double getFactorValue(std::map<std::string, int>&);
private: private:
std::string name; std::string name;
std::vector<Node*> parents; std::vector<Node*> parents;