diff --git a/src/cpp/src/data/samplers/neighbor.cpp b/src/cpp/src/data/samplers/neighbor.cpp
index bce72230..7ed6bf5b 100644
--- a/src/cpp/src/data/samplers/neighbor.cpp
+++ b/src/cpp/src/data/samplers/neighbor.cpp
@@ -496,7 +496,7 @@ DENSEGraph LayeredNeighborSampler::getNeighbors(torch::Tensor node_ids, shared_p
         }
 
         if (outgoing_offsets.defined()) {
-            if (delta_outgoing_edges.size(0) > 0) {
+            if (delta_outgoing_offsets.size(0) > 0) {
                 outgoing_offsets = outgoing_offsets + delta_outgoing_edges.size(0);
                 outgoing_offsets = torch::cat({delta_outgoing_offsets, outgoing_offsets}, 0);
             }
@@ -632,7 +632,7 @@ torch::Tensor LayeredNeighborSampler::computeDeltaIdsHelperMethod1(torch::Tensor
 
     auto device_options = torch::TensorOptions().dtype(torch::kInt64).device(node_ids.device());
     std::vector<torch::Tensor> sub_deltas = std::vector<torch::Tensor>(num_threads);
-    int64_t upper_bound = (int64_t)(delta_incoming_edges.size(0) + delta_outgoing_edges.size(0)) / num_threads;
+    int64_t upper_bound = (int64_t)(delta_incoming_edges.size(0) + delta_outgoing_edges.size(0)) / num_threads + 1;
 
     std::vector<int> sub_counts = std::vector<int>(num_threads, 0);
     std::vector<int> sub_offsets = std::vector<int>(num_threads, 0);
diff --git a/src/cpp/src/nn/layers/gnn/graph_sage_layer.cpp b/src/cpp/src/nn/layers/gnn/graph_sage_layer.cpp
index 8809c59e..08417e1e 100644
--- a/src/cpp/src/nn/layers/gnn/graph_sage_layer.cpp
+++ b/src/cpp/src/nn/layers/gnn/graph_sage_layer.cpp
@@ -81,9 +81,14 @@ torch::Tensor GraphSageLayer::forward(torch::Tensor inputs, DENSEGraph dense_gra
         a_i = a_i / (total_num_neighbors + 1).unsqueeze(-1);
         outputs = torch::matmul(w1_, a_i.transpose(0, -1)).transpose(0, -1);
     } else if (options_->aggregator == GraphSageAggregator::MEAN) {
-        torch::Tensor denominator = torch::where(torch::not_equal(total_num_neighbors, 0), total_num_neighbors, 1).to(a_i.dtype()).unsqueeze(-1);
-        a_i = a_i / denominator;
-        outputs = (torch::matmul(w1_, self_embs.transpose(0, -1)) + torch::matmul(w2_, a_i.transpose(0, -1))).transpose(0, -1);
+        if (total_num_neighbors.defined()) {
+            torch::Tensor denominator = torch::where(torch::not_equal(total_num_neighbors, 0), total_num_neighbors, 1).to(a_i.dtype()).unsqueeze(-1);
+            a_i = a_i / denominator;
+            outputs = (torch::matmul(w1_, self_embs.transpose(0, -1)) + torch::matmul(w2_, a_i.transpose(0, -1))).transpose(0, -1);
+        } else {
+            outputs = torch::matmul(w1_, self_embs.transpose(0, -1)).transpose(0, -1);
+        }
+
     } else {
         throw std::runtime_error("Unrecognized aggregator");
     }