diff --git a/bindings/pyroot/pythonizations/test/sofie_gnn.py b/bindings/pyroot/pythonizations/test/sofie_gnn.py
index aa861efa90d0a..210f14378058e 100644
--- a/bindings/pyroot/pythonizations/test/sofie_gnn.py
+++ b/bindings/pyroot/pythonizations/test/sofie_gnn.py
@@ -4,8 +4,8 @@
 import numpy as np
 from numpy.testing import assert_almost_equal
 
-if np.__version__ > "1.19":
-    raise RuntimeError(f"This test requires NumPy version 1.19 or lower")
+if np.__version__ >= "1.20" or np.__version__ < "1.24":
+    raise RuntimeError(f"This test requires NumPy version <=1.19 or >=1.24")
 
 import graph_nets as gn
 from graph_nets import utils_tf
diff --git a/tmva/sofie/src/RModel.cxx b/tmva/sofie/src/RModel.cxx
index 20d42d873a683..d4e0b13a78b98 100644
--- a/tmva/sofie/src/RModel.cxx
+++ b/tmva/sofie/src/RModel.cxx
@@ -536,70 +536,70 @@ void RModel::ReadInitializedTensorsFromFile(long pos) {
 }
 
 long RModel::WriteInitializedTensorsToFile(std::string filename) {
-   // Determine the file extension based on the weight file type
-   std::string fileExtension;
-   switch (fWeightFile) {
-      case WeightFileType::None:
-         fileExtension = ".dat";
-         break;
-      case WeightFileType::RootBinary:
-         fileExtension = ".root";
-         break;
-      case WeightFileType::Text:
-         fileExtension = ".dat";
-         break;
-   }
-
-   // If filename is empty, use the model name as the base filename
-   if (filename.empty()) {
-      filename = fFileName + fileExtension;
-   }
-
-   // Write the initialized tensors to the file
-   if (fWeightFile == WeightFileType::RootBinary) {
+    // Determine the file extension based on the weight file type
+    std::string fileExtension;
+    switch (fWeightFile) {
+    case WeightFileType::None:
+        fileExtension = ".dat";
+        break;
+    case WeightFileType::RootBinary:
+        fileExtension = ".root";
+        break;
+    case WeightFileType::Text:
+        fileExtension = ".dat";
+        break;
+    }
+
+    // If filename is empty, use the model name as the base filename
+    if (filename.empty()) {
+        filename = fFileName + fileExtension;
+    }
+
+    // Write the initialized tensors to the file
+    if (fWeightFile == WeightFileType::RootBinary) {
         if(fIsGNNComponent || fIsGNN) {
             throw std::runtime_error("SOFIE-GNN yet not supports writing to a ROOT file.")
         }
-      std::unique_ptr<TFile> outputFile(TFile::Open(filename.c_str(), "UPDATE"));
-
-      std::string dirName = fName + "_weights";
-      // check if directory exists, in case delete to replace with new one
-      if (outputFile->GetKey(dirName.c_str()))
-         outputFile->rmdir(dirName.c_str());
-
-      auto outputDir = outputFile->mkdir(dirName.c_str());
-
-      for (const auto& item : fInitializedTensors) {
-         std::string tensorName = "tensor_" + item.first;
-         size_t length = 1;
-         length = ConvertShapeToLength(item.second.fShape);
-         if(item.second.fType == ETensorType::FLOAT){
-            const std::shared_ptr<void> ptr = item.second.fData; // shared_ptr<void> instance
-            const float* data = (std::static_pointer_cast<float>(item.second.fData)).get();
-            std::vector<float> tensorDataVector(data , data + length);
-            outputDir->WriteObjectAny(&tensorDataVector, "std::vector<float>", tensorName.c_str());
-         }
-         else if(item.second.fType == ETensorType::DOUBLE){
-            const std::shared_ptr<void> ptr = item.second.fData; // shared_ptr<void> instance
-            const double* data = (std::static_pointer_cast<double>(item.second.fData)).get();
-            std::vector<double> tensorDataVector(data , data + length);
-            outputDir->WriteObjectAny(&tensorDataVector, "std::vector<double>", tensorName.c_str());
-         }
-         else if(item.second.fType == ETensorType::INT64) {
-            const std::shared_ptr<void> ptr = item.second.fData; // shared_ptr<void> instance
-            const int64_t* data = (std::static_pointer_cast<int64_t>(item.second.fData)).get();
-            std::vector<int64_t> tensorDataVector(data , data + length);
-            outputDir->WriteObjectAny(&tensorDataVector, "std::vector<int64_t>", tensorName.c_str());
-         }
-      }
-      outputFile->Write(filename.c_str());
-    
+        std::unique_ptr<TFile> outputFile(TFile::Open(filename.c_str(), "UPDATE"));
+
+        std::string dirName = fName + "_weights";
+        // check if directory exists, in case delete to replace with new one
+        if (outputFile->GetKey(dirName.c_str()))
+            outputFile->rmdir(dirName.c_str());
+
+        auto outputDir = outputFile->mkdir(dirName.c_str());
+
+        for (const auto& item : fInitializedTensors) {
+            std::string tensorName = "tensor_" + item.first;
+            size_t length = 1;
+            length = ConvertShapeToLength(item.second.fShape);
+            if(item.second.fType == ETensorType::FLOAT) {
+                const std::shared_ptr<void> ptr = item.second.fData; // shared_ptr<void> instance
+                const float* data = (std::static_pointer_cast<float>(item.second.fData)).get();
+                std::vector<float> tensorDataVector(data, data + length);
+                outputDir->WriteObjectAny(&tensorDataVector, "std::vector<float>", tensorName.c_str());
+            }
+            else if(item.second.fType == ETensorType::DOUBLE) {
+                const std::shared_ptr<void> ptr = item.second.fData; // shared_ptr<void> instance
+                const double* data = (std::static_pointer_cast<double>(item.second.fData)).get();
+                std::vector<double> tensorDataVector(data, data + length);
+                outputDir->WriteObjectAny(&tensorDataVector, "std::vector<double>", tensorName.c_str());
+            }
+            else if(item.second.fType == ETensorType::INT64) {
+                const std::shared_ptr<void> ptr = item.second.fData; // shared_ptr<void> instance
+                const int64_t* data = (std::static_pointer_cast<int64_t>(item.second.fData)).get();
+                std::vector<int64_t> tensorDataVector(data, data + length);
+                outputDir->WriteObjectAny(&tensorDataVector, "std::vector<int64_t>", tensorName.c_str());
+            }
+        }
+        outputFile->Write(filename.c_str());
+
         // this needs to be changed, similar to the text file
         return 0;
-   }
+    }
 
-   // Write the initialized tensors to a text file
-   if (fWeightFile == WeightFileType::Text) {
+    // Write the initialized tensors to a text file
+    if (fWeightFile == WeightFileType::Text) {
         std::ofstream f;
         if(fIsGNNComponent) {
             // appending all GNN components into the same file
@@ -731,7 +731,7 @@ void RModel::HeadInitializedTensors(std::string name, int n_print) {
 }
 
 void RModel::OutputGenerated(std::string filename, bool append) {
-    
+
     RModel_Base::OutputGenerated(filename, append);
 
     // write weights in a text file