diff --git a/tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc b/tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc
index 95440316294..d9c93d16bd4 100644
--- a/tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc
+++ b/tensorflow/compiler/mlir/tensorflow/ir/tf_ops.cc
@@ -2621,9 +2621,8 @@ constexpr void CopyBit(const T &src, unsigned src_index, T &dst,
 // dimensions. For example, sparse spec for foo[..., 3:10] for foo of shape (2,
 // 4, 8) would have dims = 2.
 struct SparseSliceSpec {
-  const int64_t dims;
-  const int32_t begin_mask, end_mask, ellipsis_mask, new_axis_mask,
-      shrink_axis_mask;
+  int64_t dims;
+  int32_t begin_mask, end_mask, ellipsis_mask, new_axis_mask, shrink_axis_mask;
   const ArrayRef<int64_t> &begin;
   const ArrayRef<int64_t> &end;
   const ArrayRef<int64_t> &strides;
@@ -2783,6 +2782,14 @@ static void CalculateSlicedShapeFromSparseIndices(
                             ellipsis_mask,      new_axis_mask, shrink_axis_mask,
                             sparse_begin,       sparse_end,    sparse_strides};
 
+  // If no ellipsis_mask exists then an implicit ellipsis_mask at the end is
+  // inserted. This handles cases where foo[2:4] (foo.shape() = [4, 8]) yields
+  // a tensor of shape [2, 8], i.e., foo[2:4] is same as foo[2:4, ...].
+  if (sparse.ellipsis_mask == 0) {
+    Set(sparse.ellipsis_mask, sparse.dims);
+    sparse.dims++;
+  }
+
   int64_t dims = input_shape.size();
   DenseSliceSpec dense = {dims,
                           /*begin_mask = */ 0,
diff --git a/tensorflow/compiler/mlir/xla/tests/legalize-tf.mlir b/tensorflow/compiler/mlir/xla/tests/legalize-tf.mlir
index 03277ff7c37..fa0be85d2fe 100644
--- a/tensorflow/compiler/mlir/xla/tests/legalize-tf.mlir
+++ b/tensorflow/compiler/mlir/xla/tests/legalize-tf.mlir
@@ -2415,6 +2415,25 @@ func @strided_slice_new_axis_mask(%input: tensor<2x4x8x16x32x64xf32>) {
   return
 }
 
+// CHECK-LABEL: strided_slice_implicit_ellipsis_mask(
+// CHECK-SAME: [[INPUT:%.*]]: tensor<10x16x2xf32>
+func @strided_slice_implicit_ellipsis_mask(%input: tensor<10x16x2xf32>) -> tensor<2x16x2xf32> {
+  // StridedSlice gets input[8:10], which is same as input[8:10, ...]
+  // The start_indices, limit_indices, and strides attribute of xla_hlo.slice
+  // reflect the canonicalized slice.
+  %begin = "tf.Const"() {value = dense<8> : tensor<1xi32>} : () -> tensor<1xi32>
+  %end = "tf.Const"() {value = dense<10> : tensor<1xi32>} : () -> tensor<1xi32>
+  %strides = "tf.Const"() {value = dense<1> : tensor<1xi32>} : () -> tensor<1xi32>
+  // CHECK: [[SLICE:%.*]] = "xla_hlo.slice"([[INPUT]])
+  // CHECK-DAG-SAME: limit_indices = dense<[10, 16, 2]> : tensor<3xi64>
+  // CHECK-DAG-SAME: start_indices = dense<[8, 0, 0]> : tensor<3xi64>
+  // CHECK-DAG-SAME: strides = dense<1> : tensor<3xi64>
+  // CHECK: [[RESHAPE:%.*]] = "xla_hlo.reshape"([[SLICE]]) : (tensor<2x16x2xf32>) -> tensor<2x16x2xf32>
+  %0 = "tf.StridedSlice"(%input, %begin, %end, %strides) {Index = i32, T = f32} : (tensor<10x16x2xf32>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<2x16x2xf32>
+  // CHECK: return [[RESHAPE]] : tensor<2x16x2xf32>
+  return %0 : tensor<2x16x2xf32>
+}
+
 
 //===----------------------------------------------------------------------===//
 // Reduction op legalizations.