diff --git a/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp b/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp
--- a/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp
+++ b/mlir/lib/Conversion/TosaToLinalg/TosaToLinalg.cpp
@@ -558,9 +558,9 @@
   SmallVector<Value> filteredDims = condenseValues(dynDims);
 
   for (auto result : results) {
-    auto resultTy = cast<ShapedType>(result.getType());
-    emptyTensors.push_back(rewriter.create<tensor::EmptyOp>(
-        loc, resultTy.getShape(), resultTy.getElementType(), filteredDims));
+    RankedTensorType rankedType = result.getType().dyn_cast<RankedTensorType>();
+    emptyTensors.push_back(
+        rewriter.create<tensor::EmptyOp>(loc, rankedType, filteredDims));
     opResultTypes.push_back(result.getType());
   }
 
diff --git a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
--- a/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
+++ b/mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
@@ -85,8 +85,21 @@
   %0 = "tosa.abs"(%arg0) : (tensor<2x?xf32>) -> tensor<2x?xf32>
   return %0 : tensor<2x?xf32>
 }
+
 // -----
 
+#SparseVector = #sparse_tensor.encoding<{ lvlTypes = [ "compressed" ] }>
+
+// CHECK-LABEL: @test_encoding_passthrough
+func.func @test_encoding_passthrough() -> tensor<8xi32, #SparseVector> {
+  %0 = tensor.empty() : tensor<8xi32, #SparseVector>
+  // CHECK: linalg.generic
+  // CHECK: sparse_tensor
+  %1 = "tosa.abs"(%0) : (tensor<8xi32, #SparseVector>) -> tensor<8xi32, #SparseVector>
+  return %1 : tensor<8xi32, #SparseVector>
+}
+
+// -----
 
 // CHECK: #[[$MAP0:.*]] = affine_map<(d0) -> ()>
 // CHECK: #[[$MAP1:.*]] = affine_map<(d0) -> (d0)>