[tmva] Fix Clang 21 compiler warnings in RBatchLoader

Follow up on root-project#20071.

Fix the following compiler warnings:
```txt
/home/rembserj/code/root/root_src/tmva/tmva/inc/TMVA/BatchGenerator/RBatchLoader.hxx:46:16: warning: private field 'fChunkSize' is not used [-Wunused-private-field]
   46 |    std::size_t fChunkSize;
      |                ^
/home/rembserj/code/root/root_src/tmva/tmva/inc/TMVA/BatchGenerator/RBatchLoader.hxx:49:16: warning: private field 'fMaxBatches' is not used [-Wunused-private-field]
   49 |    std::size_t fMaxBatches;
      |                ^
/home/rembserj/code/root/root_src/tmva/tmva/inc/TMVA/BatchGenerator/RBatchLoader.hxx:50:16: warning: private field 'fTrainingRemainderRow' is not used [-Wunused-private-field]
   50 |    std::size_t fTrainingRemainderRow = 0;
      |                ^
/home/rembserj/code/root/root_src/tmva/tmva/inc/TMVA/BatchGenerator/RBatchLoader.hxx:51:16: warning: private field 'fValidationRemainderRow' is not used [-Wunused-private-field]
   51 |    std::size_t fValidationRemainderRow = 0;
      |                ^
```

Also, use inline namespaces for code brevity and remove some comments
that trigger clang-format to not run on the doc string, although it only
suggests harmless line breaks that don't change how the rendered doxygen
looks like.

Author: guitargeek

tmva/tmva/inc/TMVA/BatchGenerator/RBatchGenerator.hxx

@@ -144,7 +144,7 @@ public:
       fChunkLoader =
          std::make_unique<RChunkLoader<Args...>>(f_rdf, fNumEntries, fEntries, fChunkSize, fBlockSize, fValidationSplit,
                                                  fCols, vecSizes, vecPadding, fShuffle, fSetSeed);
-      fBatchLoader = std::make_unique<RBatchLoader>(fChunkSize, fBatchSize, fNumChunkCols);
+      fBatchLoader = std::make_unique<RBatchLoader>(fBatchSize, fNumChunkCols);
 
       // split the dataset into training and validation sets
       fChunkLoader->SplitDataset();

tmva/tmva/inc/TMVA/BatchGenerator/RBatchLoader.hxx

@@ -27,28 +27,21 @@
 #include "TMVA/RTensor.hxx"
 #include "TMVA/Tools.h"
 
-namespace TMVA {
-namespace Experimental {
-namespace Internal {
+namespace TMVA::Experimental::Internal {
 
-// clang-format off
 /**
 \class ROOT::TMVA::Experimental::Internal::RBatchLoader
 \ingroup tmva
 \brief Building and loading the batches from loaded chunks in RChunkLoader
 
-In this class the chunks that are loaded into memory (see RChunkLoader) are split into batches used in the ML training which are loaded into a queue. This is done for both the training and validation chunks separatly.
+In this class the chunks that are loaded into memory (see RChunkLoader) are split into batches used in the ML training
+which are loaded into a queue. This is done for both the training and validation chunks separately.
 */
 
 class RBatchLoader {
 private:
-   // clang-format on      
-   std::size_t fChunkSize;
    std::size_t fBatchSize;
    std::size_t fNumColumns;
-   std::size_t fMaxBatches;
-   std::size_t fTrainingRemainderRow = 0;
-   std::size_t fValidationRemainderRow = 0;
 
    bool fIsActive = false;
 
@@ -63,7 +56,7 @@ private:
    std::size_t fNumTrainingBatchQueue;
    std::size_t fNumValidationBatchQueue;
 
-   // current batch that is loaded into memeory
+   // current batch that is loaded into memory
    std::unique_ptr<TMVA::Experimental::RTensor<float>> fCurrentBatch;
 
    // primary and secondary batches used to create batches from a chunk
@@ -74,8 +67,7 @@ private:
    std::unique_ptr<TMVA::Experimental::RTensor<float>> fSecondaryLeftoverValidationBatch;
 
 public:
-   RBatchLoader(std::size_t chunkSize, std::size_t batchSize, std::size_t numColumns)
-      : fChunkSize(chunkSize), fBatchSize(batchSize), fNumColumns(numColumns)
+   RBatchLoader(std::size_t batchSize, std::size_t numColumns) : fBatchSize(batchSize), fNumColumns(numColumns)
    {
 
       fPrimaryLeftoverTrainingBatch =
@@ -95,9 +87,6 @@ public:
 public:
    void Activate()
    {
-      // fTrainingRemainderRow = 0;
-      // fValidationRemainderRow = 0;
-
       {
          std::lock_guard<std::mutex> lock(fBatchLock);
          fIsActive = true;
@@ -132,7 +121,6 @@ public:
       return batch;
    }
 
-   
    /// \brief Loading the training batch from the queue
    /// \return Training batch
    TMVA::Experimental::RTensor<float> GetTrainBatch()
@@ -220,7 +208,7 @@ public:
 
       // copy LeftoverBatch to both fPrimaryLeftoverTrainingBatch and fSecondaryLeftoverTrainingBatch
       else if (emptySlots < LeftoverBatchSize) {
-         // copy the first part of LeftoverBatch to end of fPrimaryLeftoverTrainingBatch 
+         // copy the first part of LeftoverBatch to end of fPrimaryLeftoverTrainingBatch
          (*fPrimaryLeftoverTrainingBatch) = (*fPrimaryLeftoverTrainingBatch).Resize({fBatchSize, fNumColumns});
          std::copy(LeftoverBatch.GetData(), LeftoverBatch.GetData() + (emptySlots * fNumColumns),
                    fPrimaryLeftoverTrainingBatch->GetData() + (PrimaryLeftoverSize * fNumColumns));
@@ -231,18 +219,18 @@ public:
          std::copy(LeftoverBatch.GetData() + (emptySlots * fNumColumns),
                    LeftoverBatch.GetData() + (LeftoverBatchSize * fNumColumns),
                    fSecondaryLeftoverTrainingBatch->GetData());
-         
+
          // add fPrimaryLeftoverTrainingBatch to the batch vector
          auto copy =
             std::make_unique<TMVA::Experimental::RTensor<float>>(std::vector<std::size_t>{fBatchSize, fNumColumns});
          std::copy(fPrimaryLeftoverTrainingBatch->GetData(),
                    fPrimaryLeftoverTrainingBatch->GetData() + (fBatchSize * fNumColumns), copy->GetData());
          batches.emplace_back(std::move(copy));
-         
+
          // exchange fPrimaryLeftoverTrainingBatch and fSecondaryLeftoverValidationBatch
          *fPrimaryLeftoverTrainingBatch = *fSecondaryLeftoverTrainingBatch;
-         
-         // restet fSecondaryLeftoverValidationBatch
+
+         // reset fSecondaryLeftoverValidationBatch
          fSecondaryLeftoverValidationBatch =
             std::make_unique<TMVA::Experimental::RTensor<float>>(std::vector<std::size_t>{0, fNumColumns});
       }
@@ -269,7 +257,7 @@ public:
          fTrainingBatchQueue.push(std::move(batches[i]));
       }
    }
-   
+
    /// \brief Creating the validation batches from a chunk and adding them to the queue
    /// \param[in] chunkTensor RTensor with the data from the chunk
    /// \param[in] lastbatch Check if the batch in the chunk is the last one
@@ -359,8 +347,6 @@ public:
    std::size_t GetNumValidationBatchQueue() { return fValidationBatchQueue.size(); }
 };
 
-} // namespace Internal
-} // namespace Experimental
-} // namespace TMVA
+} // namespace TMVA::Experimental::Internal
 
 #endif // TMVA_RBATCHLOADER