%26 = "tf.AddV2"(%25, %13) {device = ""} : (tensor<1xi64>, tensor<i64>) -> tensor<1xi64>

  // CHECK:  %1 = "tfl.strided_slice"(%arg0, %arg1, %[[cst]], %[[c0]]) <{begin_mask = 0 : i32, ellipsis_mask = 0 : i32, end_mask = 0 : i32, new_axis_mask = 0 : i32, offset = true, shrink_axis_mask = 0 : i32}> : (tensor<4xi32>, tensor<1xi32>, tensor<1xi32>, tensor<1xi32>) -> tensor<4xi32>

  %cst_0 = "tfl.pseudo_const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>

func.func @strided_slice_new_axis_mask(%input: tensor<2x4x8x16x32x64xf32>) {
  // For StridedSlice input[1, tf.new_axis, ..., 8:, :10, 2:6:2, tf.new_axis]
  // New axis mask is at index 1 and 6 of sparse spec, so
  // new_axis_mask = 2^1 + 2^6 = 66
  // The ellipsis mask is applied to dim #1, #2 of input i.e, we get
  // canonicalized slice input[1, :, :, 8:, :10, 2:6:2]
  // This is then reshaped to add the new axes.

// CHECK:           %[[VAL_4:.*]] = "tf.StridedSlice"(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]], %[[VAL_3]])
// CHECK-SAME:          <{begin_mask = 0 : i64, ellipsis_mask = 0 : i64, end_mask = 0 : i64, new_axis_mask = 0 : i64, shrink_axis_mask = 0 : i64}>
// CHECK-SAME:          (tensor<1x4672xf32>, tensor<2xi64>, tensor<2xi64>, tensor<2xi64>) -> tensor<1x519xf32>
// CHECK:           return %[[VAL_4]] : tensor<1x519xf32>

        GetI64ElementsAttr(hlo_end_indices, &rewriter),
        GetI64ElementsAttr(hlo_strides, &rewriter));

    // Reshape slice result so that the shape is updated depending on
    // 'new_axis_mask' or 'shrink_axis_mask' attributes.
    rewriter.replaceOpWithNewOp<ReshapeOp>(op, op.getType(), sliced);
    return success();
  }

  LogicalResult rewriteWithUnknownBegin(TF::StridedSliceOp op,