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Ported mini batch creation methods in Utilities.
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@ -568,6 +568,189 @@ std::tuple<std::vector<std::vector<std::vector<real_t>>>, std::vector<std::vecto
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return { inputMiniBatches, outputMiniBatches };
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}
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Vector<Ref<MLPPMatrix>> MLPPUtilities::create_mini_batchesm(const Ref<MLPPMatrix> &input_set, int n_mini_batch) {
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Size2i size = input_set->size();
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int n = size.y;
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int mini_batch_element_count = n / n_mini_batch;
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Ref<MLPPVector> row_tmp;
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row_tmp.instance();
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row_tmp->resize(size.x);
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Vector<Ref<MLPPMatrix>> input_mini_batches;
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// Creating the mini-batches
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for (int i = 0; i < n_mini_batch; i++) {
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int mini_batch_start_offset = n_mini_batch * i;
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Ref<MLPPMatrix> current_input_set;
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current_input_set.instance();
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current_input_set->resize(Size2i(size.x, mini_batch_element_count));
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for (int j = 0; j < mini_batch_element_count; j++) {
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input_set->get_row_into_mlpp_vector(mini_batch_start_offset + j, row_tmp);
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current_input_set->set_row_mlpp_vector(j, row_tmp);
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}
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input_mini_batches.push_back(current_input_set);
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}
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/* Don't think this can ever happen, todo double check
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if (real_t(n) / real_t(n_mini_batch) - int(n / n_mini_batch) != 0) {
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for (int i = 0; i < n - n / n_mini_batch * n_mini_batch; i++) {
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inputMiniBatches[n_mini_batch - 1].push_back(inputSet[n_mini_batch * n_mini_batch + i]);
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}
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}
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*/
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return input_mini_batches;
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}
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MLPPUtilities::CreateMiniBatchMVBatch MLPPUtilities::create_mini_batchesmv(const Ref<MLPPMatrix> &input_set, const Ref<MLPPVector> &output_set, int n_mini_batch) {
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Size2i size = input_set->size();
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int n = size.y;
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int mini_batch_element_count = n / n_mini_batch;
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Ref<MLPPVector> row_tmp;
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row_tmp.instance();
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row_tmp->resize(size.x);
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CreateMiniBatchMVBatch ret;
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for (int i = 0; i < n_mini_batch; i++) {
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int mini_batch_start_offset = n_mini_batch * i;
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Ref<MLPPMatrix> current_input_set;
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current_input_set.instance();
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current_input_set->resize(Size2i(size.x, mini_batch_element_count));
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Ref<MLPPVector> current_output_set;
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current_output_set.instance();
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current_output_set->resize(mini_batch_element_count);
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for (int j = 0; j < mini_batch_element_count; j++) {
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int main_indx = mini_batch_start_offset + j;
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input_set->get_row_into_mlpp_vector(main_indx, row_tmp);
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current_input_set->set_row_mlpp_vector(j, row_tmp);
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current_output_set->set_element(j, output_set->get_element(j));
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}
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ret.input_sets.push_back(current_input_set);
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ret.output_sets.push_back(current_output_set);
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}
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/* Don't think this can ever happen, todo double check
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if (real_t(n) / real_t(n_mini_batch) - int(n / n_mini_batch) != 0) {
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for (int i = 0; i < n - n / n_mini_batch * n_mini_batch; i++) {
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inputMiniBatches[n_mini_batch - 1].push_back(inputSet[n / n_mini_batch * n_mini_batch + i]);
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outputMiniBatches[n_mini_batch - 1].push_back(outputSet[n / n_mini_batch * n_mini_batch + i]);
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}
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}
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*/
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return ret;
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}
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MLPPUtilities::CreateMiniBatchMMBatch MLPPUtilities::create_mini_batchesmm(const Ref<MLPPMatrix> &input_set, const Ref<MLPPMatrix> &output_set, int n_mini_batch) {
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Size2i input_set_size = input_set->size();
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Size2i output_set_size = output_set->size();
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int n = input_set_size.y;
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int mini_batch_element_count = n / n_mini_batch;
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Ref<MLPPVector> input_row_tmp;
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input_row_tmp.instance();
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input_row_tmp->resize(input_set_size.x);
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Ref<MLPPVector> output_row_tmp;
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output_row_tmp.instance();
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output_row_tmp->resize(output_set_size.x);
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CreateMiniBatchMMBatch ret;
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for (int i = 0; i < n_mini_batch; i++) {
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int mini_batch_start_offset = n_mini_batch * i;
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Ref<MLPPMatrix> current_input_set;
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current_input_set.instance();
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current_input_set->resize(Size2i(input_set_size.x, mini_batch_element_count));
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Ref<MLPPMatrix> current_output_set;
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current_output_set.instance();
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current_output_set->resize(Size2i(output_set_size.x, mini_batch_element_count));
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for (int j = 0; j < mini_batch_element_count; j++) {
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int main_indx = mini_batch_start_offset + j;
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input_set->get_row_into_mlpp_vector(main_indx, input_row_tmp);
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current_input_set->set_row_mlpp_vector(j, input_row_tmp);
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output_set->get_row_into_mlpp_vector(main_indx, output_row_tmp);
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current_output_set->set_row_mlpp_vector(j, output_row_tmp);
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}
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ret.input_sets.push_back(current_input_set);
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ret.output_sets.push_back(current_output_set);
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}
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/* Don't think this can ever happen, todo double check
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if (real_t(n) / real_t(n_mini_batch) - int(n / n_mini_batch) != 0) {
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for (int i = 0; i < n - n / n_mini_batch * n_mini_batch; i++) {
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inputMiniBatches[n_mini_batch - 1].push_back(inputSet[n / n_mini_batch * n_mini_batch + i]);
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}
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}
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*/
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return ret;
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}
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Array MLPPUtilities::create_mini_batchesm_bind(const Ref<MLPPMatrix> &input_set, int n_mini_batch) {
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Vector<Ref<MLPPMatrix>> batches = create_mini_batchesm(input_set, n_mini_batch);
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Array ret;
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for (int i = 0; i < batches.size(); ++i) {
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ret.push_back(batches[i].get_ref_ptr());
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}
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return ret;
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}
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Array MLPPUtilities::create_mini_batchesmv_bind(const Ref<MLPPMatrix> &input_set, const Ref<MLPPVector> &output_set, int n_mini_batch) {
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CreateMiniBatchMVBatch batches = create_mini_batchesmv(input_set, output_set, n_mini_batch);
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Array inputs;
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Array outputs;
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for (int i = 0; i < batches.input_sets.size(); ++i) {
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inputs.push_back(batches.input_sets[i].get_ref_ptr());
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outputs.push_back(batches.output_sets[i].get_ref_ptr());
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}
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Array ret;
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ret.push_back(inputs);
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ret.push_back(outputs);
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return ret;
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}
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Array MLPPUtilities::create_mini_batchesmm_bind(const Ref<MLPPMatrix> &input_set, const Ref<MLPPMatrix> &output_set, int n_mini_batch) {
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CreateMiniBatchMMBatch batches = create_mini_batchesmm(input_set, output_set, n_mini_batch);
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Array inputs;
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Array outputs;
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for (int i = 0; i < batches.input_sets.size(); ++i) {
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inputs.push_back(batches.input_sets[i].get_ref_ptr());
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outputs.push_back(batches.output_sets[i].get_ref_ptr());
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}
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Array ret;
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ret.push_back(inputs);
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ret.push_back(outputs);
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return ret;
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}
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std::tuple<real_t, real_t, real_t, real_t> MLPPUtilities::TF_PN(std::vector<real_t> y_hat, std::vector<real_t> y) {
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real_t TP, FP, TN, FN = 0;
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for (int i = 0; i < y_hat.size(); i++) {
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@ -616,6 +799,10 @@ void MLPPUtilities::_bind_methods() {
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ClassDB::bind_method(D_METHOD("performance_mat", "y_hat", "y"), &MLPPUtilities::performance_mat);
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ClassDB::bind_method(D_METHOD("performance_pool_int_array_vec", "y_hat", "output_set"), &MLPPUtilities::performance_pool_int_array_vec);
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ClassDB::bind_method(D_METHOD("create_mini_batchesm", "input_set", "n_mini_batch"), &MLPPUtilities::create_mini_batchesm_bind);
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ClassDB::bind_method(D_METHOD("create_mini_batchesmv", "input_set", "output_set", "n_mini_batch"), &MLPPUtilities::create_mini_batchesmv_bind);
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ClassDB::bind_method(D_METHOD("create_mini_batchesmm", "input_set", "output_set", "n_mini_batch"), &MLPPUtilities::create_mini_batchesmm_bind);
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BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_DEFAULT);
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BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_XAVIER_NORMAL);
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BIND_ENUM_CONSTANT(WEIGHT_DISTRIBUTION_TYPE_XAVIER_UNIFORM);
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@ -73,6 +73,24 @@ public:
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static std::tuple<std::vector<std::vector<std::vector<real_t>>>, std::vector<std::vector<real_t>>> createMiniBatches(std::vector<std::vector<real_t>> inputSet, std::vector<real_t> outputSet, int n_mini_batch);
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static std::tuple<std::vector<std::vector<std::vector<real_t>>>, std::vector<std::vector<std::vector<real_t>>>> createMiniBatches(std::vector<std::vector<real_t>> inputSet, std::vector<std::vector<real_t>> outputSet, int n_mini_batch);
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struct CreateMiniBatchMVBatch {
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Vector<Ref<MLPPMatrix>> input_sets;
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Vector<Ref<MLPPVector>> output_sets;
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};
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struct CreateMiniBatchMMBatch {
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Vector<Ref<MLPPMatrix>> input_sets;
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Vector<Ref<MLPPMatrix>> output_sets;
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};
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static Vector<Ref<MLPPMatrix>> create_mini_batchesm(const Ref<MLPPMatrix> &input_set, int n_mini_batch);
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static CreateMiniBatchMVBatch create_mini_batchesmv(const Ref<MLPPMatrix> &input_set, const Ref<MLPPVector> &output_set, int n_mini_batch);
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static CreateMiniBatchMMBatch create_mini_batchesmm(const Ref<MLPPMatrix> &input_set, const Ref<MLPPMatrix> &output_set, int n_mini_batch);
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Array create_mini_batchesm_bind(const Ref<MLPPMatrix> &input_set, int n_mini_batch);
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Array create_mini_batchesmv_bind(const Ref<MLPPMatrix> &input_set, const Ref<MLPPVector> &output_set, int n_mini_batch);
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Array create_mini_batchesmm_bind(const Ref<MLPPMatrix> &input_set, const Ref<MLPPMatrix> &output_set, int n_mini_batch);
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// F1 score, Precision/Recall, TP, FP, TN, FN, etc.
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std::tuple<real_t, real_t, real_t, real_t> TF_PN(std::vector<real_t> y_hat, std::vector<real_t> y); //TF_PN = "True", "False", "Positive", "Negative"
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real_t recall(std::vector<real_t> y_hat, std::vector<real_t> y);
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