From 38cc0c15023f280babd29530f46a222cd474eac9 Mon Sep 17 00:00:00 2001
From: novak_99 <cooljohn312@gmail.com>
Date: Tue, 23 Nov 2021 23:45:20 -0800
Subject: [PATCH] added lecun weight init methods

---
 MLPP/Utilities/Utilities.cpp | 16 ++++++++++++++++
 1 file changed, 16 insertions(+)

diff --git a/MLPP/Utilities/Utilities.cpp b/MLPP/Utilities/Utilities.cpp
index 2dbb179..53b5962 100644
--- a/MLPP/Utilities/Utilities.cpp
+++ b/MLPP/Utilities/Utilities.cpp
@@ -34,6 +34,14 @@ namespace MLPP{
                 std::uniform_real_distribution<double> distribution(-sqrt(6 / n), sqrt(6 / n));
                 weights.push_back(distribution(generator));
             }
+            else if(type == "LeCunNormal"){
+                std::normal_distribution<double> distribution(0, sqrt(1 / n));
+                weights.push_back(distribution(generator));
+            }
+            else if(type == "LeCunUniform"){
+                std::uniform_real_distribution<double> distribution(-sqrt(3/n), sqrt(3/n));
+                weights.push_back(distribution(generator));
+            }
             else if(type == "Uniform"){
                 std::uniform_real_distribution<double> distribution(-1/sqrt(n), 1/sqrt(n));
                 weights.push_back(distribution(generator));
@@ -79,6 +87,14 @@ namespace MLPP{
                     std::uniform_real_distribution<double> distribution(-sqrt(6 / n), sqrt(6 / n));
                     weights[i].push_back(distribution(generator));
                 }
+                else if(type == "LeCunNormal"){
+                    std::normal_distribution<double> distribution(0, sqrt(1 / n));
+                    weights[i].push_back(distribution(generator));
+                }
+                else if(type == "LeCunUniform"){
+                    std::uniform_real_distribution<double> distribution(-sqrt(3/n), sqrt(3/n));
+                    weights[i].push_back(distribution(generator));
+                }
                 else if(type == "Uniform"){
                     std::uniform_real_distribution<double> distribution(-1/sqrt(n), 1/sqrt(n));
                     weights[i].push_back(distribution(generator));