From a3e665eed6a2d6afd6d9957cc4895aa6a0cd281d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Ricardo=20Montan=CC=83ana?= <rmontanana@gmail.com>
Date: Wed, 16 Aug 2023 12:46:09 +0200
Subject: [PATCH] make weights double

---
 src/BayesNet/Classifier.cc | 6 +++---
 src/BayesNet/Proposal.cc   | 3 +--
 2 files changed, 4 insertions(+), 5 deletions(-)

diff --git a/src/BayesNet/Classifier.cc b/src/BayesNet/Classifier.cc
index 4d4ab08..ff25657 100644
--- a/src/BayesNet/Classifier.cc
+++ b/src/BayesNet/Classifier.cc
@@ -43,7 +43,7 @@ namespace bayesnet {
     {
         dataset = X;
         buildDataset(y);
-        const torch::Tensor weights = torch::full({ dataset.size(1) }, 1.0 / dataset.size(1), torch::kFloat);
+        const torch::Tensor weights = torch::full({ dataset.size(1) }, 1.0 / dataset.size(1), torch::kDouble);
         return build(features, className, states, weights);
     }
     // X is nxm where n is the number of features and m the number of samples
@@ -55,13 +55,13 @@ namespace bayesnet {
         }
         auto ytmp = torch::tensor(y, kInt32);
         buildDataset(ytmp);
-        const torch::Tensor weights = torch::full({ dataset.size(1) }, 1.0 / dataset.size(1), torch::kFloat);
+        const torch::Tensor weights = torch::full({ dataset.size(1) }, 1.0 / dataset.size(1), torch::kDouble);
         return build(features, className, states, weights);
     }
     Classifier& Classifier::fit(torch::Tensor& dataset, vector<string>& features, string className, map<string, vector<int>>& states)
     {
         this->dataset = dataset;
-        const torch::Tensor weights = torch::full({ dataset.size(1) }, 1.0 / dataset.size(1), torch::kFloat);
+        const torch::Tensor weights = torch::full({ dataset.size(1) }, 1.0 / dataset.size(1), torch::kDouble);
         return build(features, className, states, weights);
     }
     Classifier& Classifier::fit(torch::Tensor& dataset, vector<string>& features, string className, map<string, vector<int>>& states, const torch::Tensor& weights)
diff --git a/src/BayesNet/Proposal.cc b/src/BayesNet/Proposal.cc
index 87767b5..c410289 100644
--- a/src/BayesNet/Proposal.cc
+++ b/src/BayesNet/Proposal.cc
@@ -65,8 +65,7 @@ namespace bayesnet {
                 //Update new states of the feature/node
                 states[pFeatures[index]] = xStates;
             }
-            // TODO weights can't be ones
-            const torch::Tensor weights = torch::ones({ pDataset.size(1) }, torch::kFloat);
+            const torch::Tensor weights = torch::full({ pDataset.size(1) }, 1.0 / pDataset.size(1), torch::kDouble);
             model.fit(pDataset, weights, pFeatures, pClassName, states);
         }
         return states;