tfr.func @tf__risc_same_(!tfr.tensor<T>) -> !tfr.tensor<T> attributes {T}
tfr.func @tf__risc_concat_(!tfr.tensor_list<N, T>) -> !tfr.tensor<T> attributes {T, N}
tfr.func @tf__risc_split_(!tfr.tensor<T>, i32 {tfr.name="N"}) -> !tfr.tensor_list<N, T> attributes {T, N}
tfr.func @tf__risc_cast_(!tfr.tensor, !tfr.attr {tfr.name="K"}) -> !tfr.tensor<K> attributes {T, K}

// Replicates the TensorList initialization ops for all the uses.
// No need to delete the original TensorList as it might be used elsewhere.
template <typename T>
void ReplicateTensorListForUses(T tensor_list_op) {
  Value tensor_list = tensor_list_op.getResult();
  std::vector<OpOperand*> uses;
  for (auto& use : tensor_list.getUses()) {
    uses.emplace_back(&use);
  }

// OpDefs.

tfr.func @tf__my_add_n(%values: !tfr.tensor_list,
                       %n: i64 {tfr.name="N"}) -> !tfr.tensor {
  %index = arith.constant 0 : index
  %cst = arith.constant 1 : i64
  %eq = arith.cmpi eq, %n, %cst : i64
  %v1 = tfr.get_element %values[%index] : (!tfr.tensor_list, index) -> !tfr.tensor
  %res = scf.if %eq -> !tfr.tensor {
    scf.yield %v1 : !tfr.tensor
  } else {

constexpr char tfr_raw_text[] = R"(

tfr.func @tf__my_add_n(%values: !tfr.tensor_list,
                       %n: i64 {tfr.name="N"}) -> !tfr.tensor {
  %index = arith.constant 0 : index
  %cst = arith.constant 1 : i64
  %eq = arith.cmpi "eq", %n, %cst : i64
  %v1 = tfr.get_element %values[%index] : (!tfr.tensor_list, index) -> !tfr.tensor
  %res = scf.if %eq -> !tfr.tensor {
    scf.yield %v1 : !tfr.tensor
  } else {

tfr.func @tf__my_pack(%values: !tfr.tensor_list,
                      %n: i32 {tfr.name="N"},
                      %axis: i32 {tfr.name="axis"}) -> !tfr.tensor {
  %index = arith.constant 0 : index
  %cst = arith.constant 1 : i32
  %eq = arith.cmpi eq, %n, %cst : i32
  %v1 = tfr.get_element %values[%index] : (!tfr.tensor_list, index) -> !tfr.tensor

};

class TFRTensorListType : public detail::TFRTypeImpl<TFRTensorListType> {
 public:
  using TFRBase::TFRBase;
  static constexpr StringLiteral name = "tfr.tensor_list";
  static std::string getTypeName() { return "TFRTensorListType"; }
};

class TFRAttrType : public Type::TypeBase<TFRAttrType, TFRType, TypeStorage> {
 public:
  using Base::Base;

// RUN: tf-opt -tfl-legalize-tensorlist -canonicalize -split-input-file %s | FileCheck %s

// CHECK-LABEL: listReserveScalarShapeI32
func.func @listReserveScalarShapeI32(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>> {
  %0 = "tf.TensorListReserve"(%arg0, %arg1) : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>>

A. Unique TensorFlower <******@****.***> 1684532433 -0700

A. Unique TensorFlower <******@****.***> 1712999357 -0700

//===----------------------------------------------------------------------===//
// TensorList transformation patterns.
// Note that the pattern below rewrites `TensorList` tensors  (which has type DT_VARIANT)
// into regular tensors. We also assume that each element in the `TensorList` has
// a same constant shape.
//===----------------------------------------------------------------------===//