#include "tensorflow/compiler/mlir/lite/transforms/passes.h.inc"

struct ConvertTensorListPopBack
    : public OpRewritePattern<TF::TensorListPopBackOp> {
  using OpRewritePattern::OpRewritePattern;

  LogicalResult matchAndRewrite(TF::TensorListPopBackOp op,
                                PatternRewriter& rewriter) const override {
    // It is currently not possible to easily pack the output of a multi-result

  (*buffer_to_size)[new_buffer] = {new_size, /*fixed=*/false};
  push.erase();
  return success();
}

LogicalResult HandleTensorListPopBackOp(
    TF::TensorListPopBackOp pop,
    llvm::SmallDenseMap<Value, SizeInfo>* buffer_to_size) {
  auto buffer = pop.getInputHandle();
  auto it = buffer_to_size->find(buffer);
  if (it == buffer_to_size->end()) {

      GET_OPERATION_NAME(mlir::TF::TensorListReserveOp),
      GET_OPERATION_NAME(mlir::TF::TensorListFromTensorOp),
      GET_OPERATION_NAME(mlir::TF::TensorListPushBackOp),
      GET_OPERATION_NAME(mlir::TF::TensorListPopBackOp),
      GET_OPERATION_NAME(mlir::TF::TensorListGetItemOp),
      GET_OPERATION_NAME(mlir::TF::TensorListSetItemOp),
      GET_OPERATION_NAME(mlir::TF::TensorListLengthOp),

bool ShapeInference::InferShapeForTensorListPopBackOp(TensorListPopBackOp op) {
  // The first Operand is assumed to be a TensorType around a variant with a
  // single subtype (e.g. tensor<!tf_type.variant<tensor<2xi32>>>). We will
  // copy this type to the first result, and copy the singular variant subtype
  // to the second result (tensor<2xi32>).
  DCOMMENT_OP(op, "Inferring shape for TensorListPopBackOp.");

  auto src_list_handle_t =