From 7a8e0391dc8501a540181499f8f977c0737c8ba0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ricardo=20Monta=C3=B1ana=20G=C3=B3mez?=
 <rmontanana@gmail.com>
Date: Mon, 10 Mar 2025 12:18:10 +0100
Subject: [PATCH] continue fixing xspode

---
 bayesnet/classifiers/XSPODE.cc                | 57 +++++++------------
 bayesnet/classifiers/XSPODE.h                 |  1 -
 bayesnet/ensembles/XBAODE.cc                  |  2 +-
 .../utils/{TensorUtils.hpp => TensorUtils.h}  |  6 +-
 4 files changed, 26 insertions(+), 40 deletions(-)
 rename bayesnet/utils/{TensorUtils.hpp => TensorUtils.h} (95%)

diff --git a/bayesnet/classifiers/XSPODE.cc b/bayesnet/classifiers/XSPODE.cc
index a139747..4449849 100644
--- a/bayesnet/classifiers/XSPODE.cc
+++ b/bayesnet/classifiers/XSPODE.cc
@@ -10,6 +10,7 @@
 #include <stdexcept>
 #include <sstream>
 #include "XSPODE.h"
+#include "bayesnet/utils/TensorUtils.h"
 
 
 namespace bayesnet {
@@ -299,30 +300,6 @@ namespace bayesnet {
         return probabilities;
     }
 
-    // --------------------------------------
-    // predict
-    // --------------------------------------
-    //
-    // Return the class argmax( P(c|x) ).
-    // --------------------------------------
-    int XSpode::predict(const std::vector<int>& instance) const
-    {
-        auto p = predict_proba(instance);
-        return static_cast<int>(std::distance(p.begin(),
-            std::max_element(p.begin(), p.end())));
-    }
-    std::vector<int> XSpode::predict(std::vector<std::vector<int>>& test_data)
-    {
-        auto probabilities = predict_proba(test_data);
-        std::vector<int> predictions(probabilities.size(), 0);
-
-        for (size_t i = 0; i < probabilities.size(); i++) {
-            predictions[i] = std::distance(probabilities[i].begin(), std::max_element(probabilities[i].begin(), probabilities[i].end()));
-        }
-
-        return predictions;
-    }
-
     // --------------------------------------
     // Utility: normalize
     // --------------------------------------
@@ -393,26 +370,36 @@ namespace bayesnet {
     // ------------------------------------------------------
     // Predict overrides (classifier interface)
     // ------------------------------------------------------
-    torch::Tensor predict(torch::Tensor& X)
+    int XSpode::predict(const std::vector<int>& instance) const
     {
-        auto X_ = TensorUtils::to_matrix(X);
-        return predict(X_);
+        auto p = predict_proba(instance);
+        return static_cast<int>(std::distance(p.begin(),
+            std::max_element(p.begin(), p.end())));
     }
-    std::vector<int> predict(std::vector<std::vector<int>>& X) 
+    std::vector<int> XSpode::predict(std::vector<std::vector<int>>& test_data)
     {
-        auto proba = predict_proba(X);
-        std::vector<int> predictions(proba.size(), 0);
-        for (size_t i = 0; i < proba.size(); i++) {
-            predictions[i] = std::distance(proba[i].begin(), std::max_element(proba[i].begin(), proba[i].end()));
+        auto probabilities = predict_proba(test_data);
+        std::vector<int> predictions(probabilities.size(), 0);
+
+        for (size_t i = 0; i < probabilities.size(); i++) {
+            predictions[i] = std::distance(probabilities[i].begin(), std::max_element(probabilities[i].begin(), probabilities[i].end()));
         }
+
         return predictions;
     }
-    torch::Tensor predict_proba(torch::Tensor& X) 
+    torch::Tensor XSpode::predict(torch::Tensor& X)
+    {
+        auto X_ = TensorUtils::to_matrix(X);
+        auto result = predict(X_);
+        return TensorUtils::to_tensor(result);
+    }
+    torch::Tensor XSpode::predict_proba(torch::Tensor& X) 
     {
        auto X_ = TensorUtils::to_matrix(X);
-       return predict_proba(X_); 
+       auto result = predict_proba(X_);
+       return TensorUtils::to_tensor<double>(result);
     }
-    torch::Tensor Classifier::predict(torch::Tensor& X)
+    torch::Tensor XSpode::predict(torch::Tensor& X)
     {
         auto X_ = TensorUtils::to_matrix(X);
         auto predict = predict(X_);
diff --git a/bayesnet/classifiers/XSPODE.h b/bayesnet/classifiers/XSPODE.h
index 03848de..7f57b22 100644
--- a/bayesnet/classifiers/XSPODE.h
+++ b/bayesnet/classifiers/XSPODE.h
@@ -20,7 +20,6 @@ namespace bayesnet {
         std::vector<double> predict_proba(const std::vector<int>& instance) const;
         std::vector<std::vector<double>> predict_proba(const std::vector<std::vector<int>>& test_data);
         int predict(const std::vector<int>& instance) const;
-        std::vector<int> predict(std::vector<std::vector<int>>& test_data);
         void normalize(std::vector<double>& v) const;
         std::string to_string() const;
         int getNFeatures() const;
diff --git a/bayesnet/ensembles/XBAODE.cc b/bayesnet/ensembles/XBAODE.cc
index bc8f657..982dbff 100644
--- a/bayesnet/ensembles/XBAODE.cc
+++ b/bayesnet/ensembles/XBAODE.cc
@@ -10,7 +10,7 @@
 #include <tuple>
 #include "XBAODE.h"
 #include "bayesnet/classifiers/XSPODE.h"
-#include "bayesnet/utils/TensorUtils.hpp"
+#include "bayesnet/utils/TensorUtils.h"
 
 namespace bayesnet {
     XBAODE::XBAODE()
diff --git a/bayesnet/utils/TensorUtils.hpp b/bayesnet/utils/TensorUtils.h
similarity index 95%
rename from bayesnet/utils/TensorUtils.hpp
rename to bayesnet/utils/TensorUtils.h
index dffd879..1834051 100644
--- a/bayesnet/utils/TensorUtils.hpp
+++ b/bayesnet/utils/TensorUtils.h
@@ -1,5 +1,5 @@
-#ifndef TENSORUTILS_HPP
-#define TENSORUTILS_HPP
+#ifndef TENSORUTILS_H
+#define TENSORUTILS_H
 #include <torch/torch.h>
 #include <vector>
 namespace bayesnet {
@@ -48,4 +48,4 @@ namespace bayesnet {
     };
 }
 
-#endif // TENSORUTILS_HPP
\ No newline at end of file
+#endif // TENSORUTILS_H
\ No newline at end of file