diff --git a/orttraining/orttraining/training_ops/cpu/nn/layer_norm.cc b/orttraining/orttraining/training_ops/cpu/nn/layer_norm.cc
index 30e1cfc405..8f131c80d3 100644
--- a/orttraining/orttraining/training_ops/cpu/nn/layer_norm.cc
+++ b/orttraining/orttraining/training_ops/cpu/nn/layer_norm.cc
@@ -58,8 +58,10 @@ Status LayerNormGrad<T, simplified>::Compute(OpKernelContext* op_kernel_context)
   const Tensor* X = op_kernel_context->Input<Tensor>(input_index++);
   const auto& X_shape = X->Shape();
   const auto axis = HandleNegativeAxis(axis_, X_shape.NumDimensions());
-  const auto N = X_shape.SizeToDimension(axis);
-  const auto M = X_shape.SizeFromDimension(axis);
+  ORT_ENFORCE(X_shape.SizeToDimension(axis) <= std::numeric_limits<Eigen::Index>::max());
+  ORT_ENFORCE(X_shape.SizeFromDimension(axis) <= std::numeric_limits<Eigen::Index>::max());
+  const auto N = static_cast<Eigen::Index>(X_shape.SizeToDimension(axis));
+  const auto M = static_cast<Eigen::Index>(X_shape.SizeFromDimension(axis));
   ORT_ENFORCE(M != 1);
   
   const Tensor* scale = op_kernel_context->Input<Tensor>(input_index++);
@@ -146,8 +148,10 @@ Status InvertibleLayerNormGrad<T>::Compute(OpKernelContext* op_kernel_context) c
   const auto& Y_shape = Y_grad->Shape();
   const auto& X_shape = Y_shape;
   const auto axis = HandleNegativeAxis(axis_, X_shape.NumDimensions());
-  const auto N = X_shape.SizeToDimension(axis);
-  const auto M = X_shape.SizeFromDimension(axis);
+  ORT_ENFORCE(X_shape.SizeToDimension(axis) <= std::numeric_limits<Eigen::Index>::max());
+  ORT_ENFORCE(X_shape.SizeFromDimension(axis) <= std::numeric_limits<Eigen::Index>::max());
+  const auto N = static_cast<Eigen::Index>(X_shape.SizeToDimension(axis));
+  const auto M = static_cast<Eigen::Index>(X_shape.SizeFromDimension(axis));
   ORT_ENFORCE(M != 1);
   const auto& scale_shape = scale->Shape();