diff --git a/mlir/lib/Conversion/TosaToTensor/TosaToTensor.cpp b/mlir/lib/Conversion/TosaToTensor/TosaToTensor.cpp
index cd6da35582469..89f956a5e7017 100644
--- a/mlir/lib/Conversion/TosaToTensor/TosaToTensor.cpp
+++ b/mlir/lib/Conversion/TosaToTensor/TosaToTensor.cpp
@@ -55,9 +55,8 @@ TensorType inferReshapeExpandedType(TensorType inputType,
   // Check if the input is static, and if so, get its total size
   bool inputIsStatic = inputType.hasStaticShape();
   int64_t totalSize = inputIsStatic ? inputType.getNumElements() : -1;
- 
+
   // Compute result shape
-  bool resultIsStatic = true;
   auto resultShape = llvm::map_to_vector(newShape, [&](int64_t size) -> int64_t {
     // If this is not a placeholder, do not change it
     if (size >= 0)
@@ -65,10 +64,8 @@ TensorType inferReshapeExpandedType(TensorType inputType,
 
     // If we do not know the total size of the tensor, keep this dimension
     // dynamic in the result shape.
-    if (!inputIsStatic) {
-      resultIsStatic = false;
+    if (!inputIsStatic)
       return ShapedType::kDynamic;
-    }
 
     // Calculate the product of all elements in 'newShape' except for the -1
     // placeholder, which we discard by negating the result.
@@ -84,12 +81,14 @@ TensorType inferReshapeExpandedType(TensorType inputType,
     return totalSize / totalSizeNoPlaceholder;
   });
 
+  bool resultIsStatic = !ShapedType::isDynamicShape(resultShape);
+
   // A syntactic restriction in 'tensor.expand_shape' forbids a dynamically
   // shaped input from being reshaped into a statically shaped result. We may
   // simply turn the first result dimension dynamic to address this.
   if (!inputIsStatic && resultIsStatic)
     resultShape[0] = ShapedType::kDynamic;
-  
+
   // The 'tensor.expand_shape' op also forbids a statically shaped input from
   // being reshaped into a dynamically shaped result, but the placeholder
   // inference algorithm above guarantees that this will never be the case.