diff --git a/src/dialect/onnx/onnx_ops.cpp b/src/dialect/onnx/onnx_ops.cpp
index 0aaa87b..0a4fb5e 100644
--- a/src/dialect/onnx/onnx_ops.cpp
+++ b/src/dialect/onnx/onnx_ops.cpp
@@ -350,7 +350,11 @@ void ONNXMatMulOp::inferShapes() {
   SmallVector<int64_t, 2> dims;
   auto lhsShape = lhsTy.getShape();
   auto rhsShape = rhsTy.getShape();
-  if (lhsShape.size() == 1 && rhsShape.size() == 1) {
+
+  if (lhsShape.size() < 1 && rhsShape.size() < 1) {
+    // Multiplication by scalars is not allowed.
+    emitError("Multiplication by scalar arguments not allowed.");
+  } else if (lhsShape.size() == 1 && rhsShape.size() == 1) {
     // Special case when both arrays are 1-dimensional and according to
     // numpy rules the types need to be extended to 1xN and Nx1. Helper sizes
     // need to be removed after the multiplication but cannot be removed if all
@@ -365,12 +369,12 @@ void ONNXMatMulOp::inferShapes() {
     // (s1 x s2 x... x sK x M x P)
 
     // Check legality of matrix multiplication.
-    unsigned leftDims = lhsShape.size();
-    if (lhsShape[leftDims - 1] != -1 && rhsShape[0] != -1 &&
-        lhsShape[leftDims - 1] != rhsShape[0])
+    unsigned lhsRank = lhsShape.size();
+    if (lhsShape[lhsRank - 1] != -1 && rhsShape[0] != -1 &&
+        lhsShape[lhsRank - 1] != rhsShape[0])
       emitError("Attempt to multiply incompatible matrices.");
 
-    for (int i = 0; i < leftDims - 1; ++i)
+    for (int i = 0; i < lhsRank - 1; ++i)
       dims.emplace_back(lhsShape[i]);
     dims.emplace_back(rhsShape[1]);
   } else if (lhsShape.size() == 2 && rhsShape.size() > 2) {
@@ -379,39 +383,39 @@ void ONNXMatMulOp::inferShapes() {
     // (s1 x s2 x... x sK x M x P)
 
     // Check legality of matrix multiplication.
-    unsigned rightDims = rhsShape.size();
-    if (lhsShape[1] != -1 && rhsShape[rightDims - 2] != -1 &&
-        lhsShape[1] != rhsShape[rightDims - 2])
+    unsigned rhsRank = rhsShape.size();
+    if (lhsShape[1] != -1 && rhsShape[rhsRank - 2] != -1 &&
+        lhsShape[1] != rhsShape[rhsRank - 2])
       emitError("Attempt to multiply incompatible matrices.");
 
-    for (int i = 0; i < rightDims - 2; ++i)
+    for (int i = 0; i < rhsRank - 2; ++i)
       dims.emplace_back(rhsShape[i]);
     dims.emplace_back(lhsShape[0]);
-    dims.emplace_back(rhsShape[rightDims - 1]);
+    dims.emplace_back(rhsShape[rhsRank - 1]);
   } else if (lhsShape.size() > 2 && rhsShape.size() > 2) {
     // (s1 x s2 x... x sK x M x N) MATMUL (t1 x t2 x... x tK x N x P)
     // =>
     // (u1 x u2 x... x uK x M x P)
 
     // Check legality of matrix multiplication.
-    unsigned leftDims = lhsShape.size();
-    unsigned rightDims = rhsShape.size();
-    if (lhsShape[leftDims - 1] != -1 && rhsShape[rightDims - 2] != -1 &&
-        lhsShape[leftDims - 1] != rhsShape[rightDims - 2])
+    unsigned lhsRank = lhsShape.size();
+    unsigned rhsRank = rhsShape.size();
+    if (lhsShape[lhsRank - 1] != -1 && rhsShape[rhsRank - 2] != -1 &&
+        lhsShape[lhsRank - 1] != rhsShape[rhsRank - 2])
       emitError("Attempt to multiply incompatible matrices.");
 
     // Check and perform broadcasting for the shapes.
     SmallVector<int64_t, 2> lhsBcastShape;
-    for (int i = 0; i < leftDims - 2; ++i)
+    for (int i = 0; i < lhsRank - 2; ++i)
       lhsBcastShape.emplace_back(lhsShape[i]);
     SmallVector<int64_t, 2> rhsBcastShape;
-    for (int i = 0; i < rightDims - 2; ++i)
+    for (int i = 0; i < rhsRank - 2; ++i)
       rhsBcastShape.emplace_back(rhsShape[i]);
     if (!getBroadcastedShape(lhsBcastShape, rhsBcastShape, dims))
       emitError("Broadcasted dimensions are incompatible.");
 
-    dims.emplace_back(lhsShape[leftDims - 2]);
-    dims.emplace_back(rhsShape[rightDims - 1]);
+    dims.emplace_back(lhsShape[lhsRank - 2]);
+    dims.emplace_back(rhsShape[rhsRank - 1]);
   } else {
     // This case covers all remaining combinations of 1 and 2-D matrices.
     int64_t lhsDim = lhsShape[0];