diff --git a/tt-train/sources/ttml/core/distributed_mapping.hpp b/tt-train/sources/ttml/core/distributed_mapping.hpp
index 102240e51e2..d40644486da 100644
--- a/tt-train/sources/ttml/core/distributed_mapping.hpp
+++ b/tt-train/sources/ttml/core/distributed_mapping.hpp
@@ -74,7 +74,7 @@ class XTensorToMesh {
     tt::tt_metal::distributed::MeshShape m_mesh_shape;
 
     size_t get_num_devices() const {
-        return m_mesh_shape.first * m_mesh_shape.second;
+        return m_mesh_shape.num_rows * m_mesh_shape.num_cols;
     }
 };
 
@@ -130,8 +130,8 @@ class ShardTensor2dMesh : public XTensorToMesh<ShardTensor2dMesh<T>, T> {
             throw std::invalid_argument("ShardTensor2dMesh requires at least one dimension to shard");
         }
 
-        int rows = Base::m_mesh_shape.first;
-        int cols = Base::m_mesh_shape.second;
+        int rows = Base::m_mesh_shape.num_rows;
+        int cols = Base::m_mesh_shape.num_cols;
         auto row_dim = m_dims.first;
         auto col_dim = m_dims.second;
 
@@ -178,8 +178,8 @@ class ShardTensor2dMesh : public XTensorToMesh<ShardTensor2dMesh<T>, T> {
     std::unordered_map<std::string, std::string> config_impl() const {
         return {
             {"strategy", "shard_2d"},
-            {"mesh_shape_y", std::to_string(Base::m_mesh_shape.first)},
-            {"mesh_shape_x", std::to_string(Base::m_mesh_shape.second)}};
+            {"mesh_shape_y", std::to_string(Base::m_mesh_shape.num_rows)},
+            {"mesh_shape_x", std::to_string(Base::m_mesh_shape.num_cols)}};
     }
 
 private:
@@ -193,16 +193,16 @@ class ConcatMesh2dToTensor : public MeshToXTensor<ConcatMesh2dToTensor<T>, T> {
     ConcatMesh2dToTensor(
         tt::tt_metal::distributed::MeshShape mesh_shape, const tt::tt_metal::distributed::MeshShape& dims) :
         Base(std::move(mesh_shape)), m_dims(dims) {
-        if (m_dims.first == m_dims.second) {
+        if (m_dims.num_rows == m_dims.num_cols) {
             throw std::invalid_argument("Dimensions in 'dims' must be different");
         }
     }
 
     std::vector<xt::xarray<T>> compose_impl(const std::vector<xt::xarray<T>>& tensors) const {
-        int rows = Base::m_mesh_shape.first;
-        int cols = Base::m_mesh_shape.second;
-        size_t row_dim = m_dims.first;
-        size_t col_dim = m_dims.second;
+        int rows = Base::m_mesh_shape.num_rows;
+        int cols = Base::m_mesh_shape.num_cols;
+        size_t row_dim = m_dims.num_rows;
+        size_t col_dim = m_dims.num_cols;
 
         std::vector<xt::xarray<T>> row_concatenated;
         row_concatenated.reserve(static_cast<size_t>(rows));
diff --git a/tt-train/tests/core/distributed_test.cpp b/tt-train/tests/core/distributed_test.cpp
index e273aaa4973..0f304788ca3 100644
--- a/tt-train/tests/core/distributed_test.cpp
+++ b/tt-train/tests/core/distributed_test.cpp
@@ -83,7 +83,7 @@ TYPED_TEST(MeshOpsTest, ShardTensor2dMeshTwoDimSharding) {
 
 TYPED_TEST(MeshOpsTest, ReplicateXTensorToMeshReplication) {
     tt::tt_metal::distributed::MeshShape mesh_shape = {2, 2};
-    int num_devices = mesh_shape.first * mesh_shape.second;  // 4
+    int num_devices = mesh_shape.num_rows * mesh_shape.num_cols;  // 4
 
     auto tensor = xt::arange<TypeParam>(4);  // [0,1,2,3]