const ArrayRef<int64_t> begin_shape = begin_type.getShape();
    const int begin_dim = begin_shape.size();

    if (begin_dim != 1) return failure();

    // The ellipsis fill might exceed the current output shape because we are
    // also taking account of any to-be-inserted new axes.
    const int ellipsis_filled_dim_size =
        input_size - begin_shape[0] + 1 + absl::popcount(new_axis_mask);

ArrayRef<int64_t> GetRankedTensorShape(Value value) {
  return mlir::cast<RankedTensorType>(value.getType()).getShape();
}

Value SliceRankedTensor(OpBuilder* builder, Value input,
                        ArrayRef<int64_t> begin_shape,
                        ArrayRef<int64_t> begin_values,
                        ArrayRef<int64_t> size_shape,
                        ArrayRef<int64_t> size_values,
                        mlir::Location location) {

          rewriter.create<TFL::MinimumOp>(op->getLoc(), cast, upper_limit_cst);
    }

    Value concatenated = start_indices[0];
    if (rank > 1) {
      SmallVector<int64_t> begin_shape{rank};
      Type begin_type = operand_type.cloneWith(begin_shape, i64_type);
      concatenated = rewriter.create<TFL::ConcatenationOp>(
          op->getLoc(), begin_type, start_indices, /*axis=*/0,