88 lines
3.1 KiB
C++
88 lines
3.1 KiB
C++
// #include <torch/torch.h>
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// int main()
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// {
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// torch::Tensor t = torch::rand({ 5, 5 });
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// // Print original tensor
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// std::cout << t << std::endl;
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// // New value
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// torch::Tensor new_val = torch::tensor(10.0f);
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// // Indices for the cell you want to update
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// auto index_i = torch::tensor({ 2 });
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// auto index_j = torch::tensor({ 3 });
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// // Update cell
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// t.index_put_({ index_i, index_j }, new_val);
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// // Print updated tensor
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// std::cout << t << std::endl;
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// }
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#include <torch/torch.h>
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#include <iostream>
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#include <vector>
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#include <string>
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using namespace std;
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int main()
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{
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//int i = 3, j = 1, k = 2; // Indices for the cell you want to update
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// Print original tensor
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// torch::Tensor t = torch::tensor({ {1, 2, 3}, {4, 5, 6} }); // 3D tensor for this example
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auto variables = vector<string>{ "A", "B" };
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auto cardinalities = vector<int>{ 5, 4 };
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torch::Tensor values = torch::rand({ 5, 4 });
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auto candidate = "B";
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vector<string> newVariables;
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vector<int> newCardinalities;
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for (int i = 0; i < variables.size(); i++) {
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if (variables[i] != candidate) {
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newVariables.push_back(variables[i]);
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newCardinalities.push_back(cardinalities[i]);
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}
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}
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torch::Tensor newValues = values.sum(1);
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cout << "original values" << endl;
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cout << values << endl;
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cout << "newValues" << endl;
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cout << newValues << endl;
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cout << "newVariables" << endl;
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for (auto& variable : newVariables) {
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cout << variable << endl;
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}
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cout << "newCardinalities" << endl;
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for (auto& cardinality : newCardinalities) {
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cout << cardinality << endl;
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}
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// std::cout << t << std::endl;
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// std::cout << "sum(0)" << std::endl;
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// std::cout << t.sum(0) << std::endl;
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// std::cout << "sum(1)" << std::endl;
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// std::cout << t.sum(1) << std::endl;
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// std::cout << "Normalized" << std::endl;
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// std::cout << t / t.sum(0) << std::endl;
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// New value
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// torch::Tensor new_val = torch::tensor(10.0f);
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// // Indices for the cell you want to update
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// std::vector<torch::Tensor> indices;
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// indices.push_back(torch::tensor(i)); // Replace i with your index for the 1st dimension
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// indices.push_back(torch::tensor(j)); // Replace j with your index for the 2nd dimension
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// indices.push_back(torch::tensor(k)); // Replace k with your index for the 3rd dimension
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// //torch::ArrayRef<at::indexing::TensorIndex> indices_ref(indices);
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// // Update cell
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// //torch::Tensor result = torch::stack(indices);
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// //torch::List<c10::optional<torch::Tensor>> indices_list = { torch::tensor(i), torch::tensor(j), torch::tensor(k) };
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// torch::List<c10::optional<torch::Tensor>> indices_list;
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// indices_list.push_back(torch::tensor(i));
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// indices_list.push_back(torch::tensor(j));
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// indices_list.push_back(torch::tensor(k));
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// //t.index_put_({ torch::tensor(i), torch::tensor(j), torch::tensor(k) }, new_val);
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// t.index_put_(indices_list, new_val);
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// // Print updated tensor
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// std::cout << t << std::endl;
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}
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