diff --git a/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp b/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
--- a/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
+++ b/mlir/lib/Dialect/SparseTensor/IR/SparseTensorDialect.cpp
@@ -171,6 +171,8 @@
   // Check integrity with tensor type specifics. Dimension ordering is optional,
   // but we always should have dimension level types for the full rank.
   unsigned size = shape.size();
+  if (size == 0)
+    return emitError() << "expected non-scalar sparse tensor";
   if (getDimOrdering() && getDimOrdering().getNumResults() != size)
     return emitError() << "expected an affine map of size " << size
                        << " for dimension ordering";
diff --git a/mlir/test/Dialect/SparseTensor/invalid_encoding.mlir b/mlir/test/Dialect/SparseTensor/invalid_encoding.mlir
--- a/mlir/test/Dialect/SparseTensor/invalid_encoding.mlir
+++ b/mlir/test/Dialect/SparseTensor/invalid_encoding.mlir
@@ -1,5 +1,8 @@
 // RUN: mlir-opt %s -split-input-file -verify-diagnostics
 
+#a = #sparse_tensor.encoding<{dimLevelType = []}>
+func private @scalar(%arg0: tensor<f64, #a>) -> () // expected-error {{expected non-scalar sparse tensor}}
+
 // -----
 
 #a = #sparse_tensor.encoding<{dimLevelType = ["dense", "compressed"]}>
diff --git a/mlir/test/Dialect/SparseTensor/sparse_vector_peeled.mlir b/mlir/test/Dialect/SparseTensor/sparse_vector_peeled.mlir
--- a/mlir/test/Dialect/SparseTensor/sparse_vector_peeled.mlir
+++ b/mlir/test/Dialect/SparseTensor/sparse_vector_peeled.mlir
@@ -1,4 +1,4 @@
-// RUN: mlir-opt %s -sparsification="vectorization-strategy=2 vl=16" -for-loop-peeling -canonicalize -split-input-file | \
+// RUN: mlir-opt %s -sparsification="vectorization-strategy=2 vl=16" -for-loop-peeling -canonicalize | \
 // RUN:   FileCheck %s
 
 #SparseVector = #sparse_tensor.encoding<{