diff --git a/mlir/lib/ExecutionEngine/SparseTensorUtils.cpp b/mlir/lib/ExecutionEngine/SparseTensorUtils.cpp
--- a/mlir/lib/ExecutionEngine/SparseTensorUtils.cpp
+++ b/mlir/lib/ExecutionEngine/SparseTensorUtils.cpp
@@ -378,6 +378,19 @@
     assert(tensor->getElements().size() == values.size());
     return tensor;
   }
+  /// Variant for when the permutation is known to be the identity/iota.
+  SparseTensorCOO<V> *toCOO() {
+    uint64_t rank = getRank();
+    // The new coordinate scheme's sizes array.
+    std::vector<uint64_t> permsz(rank);
+    for (uint64_t r = 0; r < rank; r++)
+      permsz[rev[r]] = sizes[r];
+    SparseTensorCOO<V> *tensor = new SparseTensorCOO<V>(permsz, values.size());
+    // Populate the coordinate scheme.
+    toCOO(*tensor, rev, 0, 0);
+    assert(tensor->getElements().size() == values.size());
+    return tensor;
+  }
 
   /// Factory method. Constructs a sparse tensor storage scheme with the given
   /// dimensions, permutation, and per-dimension dense/sparse annotations,
@@ -1108,9 +1121,7 @@
   SparseTensorStorage<uint64_t, uint64_t, double> *sparseTensor =
       static_cast<SparseTensorStorage<uint64_t, uint64_t, double> *>(tensor);
   uint64_t rank = sparseTensor->getRank();
-  std::vector<uint64_t> perm(rank);
-  std::iota(perm.begin(), perm.end(), 0);
-  SparseTensorCOO<double> *coo = sparseTensor->toCOO(perm.data());
+  SparseTensorCOO<double> *coo = sparseTensor->toCOO();
 
   const std::vector<Element<double>> &elements = coo->getElements();
   uint64_t nse = elements.size();