fix: numpy version for sofie-gnn test should be restricted within <=1…

….19 or >=1.24 Because of the changed behavior of np.bool and similar aliases for builtin data types, we need to restrict the numpy version to the stated range for sonnet. For more information, refer here: numpy/numpy#14882 numpy/numpy#22607
sanjibansg · Aug 25, 2023 · 6c99ac3 · 6c99ac3
1 parent 1b8b84c
commit 6c99ac3
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diff --git 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
@@ -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