// CHECK-NOT: Optional
  %0 = builtin.unrealized_conversion_cast to tensor<5xi1>
  %1 = "tf.OptionalNone"() : () -> tensor<!tf_type.variant<tensor<f32>>>
  %2 = "tf.If"(%0, %1) <{else_branch = @false, is_stateless = false, then_branch = @true}>
      : (tensor<5xi1>, tensor<!tf_type.variant<tensor<f32>>>) -> (tensor<!tf_type.variant<tensor<f32>>>)
  return
}

                              /*operands=*/else_returns);

  // Then branch gets the data and calls the reduce_function.
  auto& then_branch = dataset_if.getThenBranch();
  then_branch.push_back(new Block);
  builder.setInsertionPointToEnd(&then_branch.front());
  // Add iterator operational data access inside if.
  auto get_value = builder.create<TF::OptionalGetValueOp>(loc, dataset_types,

  %18 = "tf.Identity"(%17) {device = ""} : (tensor<i1>) -> tensor<i1>

    } else if (auto if_op = llvm::dyn_cast<TF::IfOp>(use.getOwner())) {
      auto then_branch = if_op.then_function();
      auto else_branch = if_op.else_function();
      assert(then_branch && else_branch);
      auto type_from_then = GetElementTypeFromAccess(
          then_branch.getArgument(use.getOperandNumber() - 1), module,
          infer_from_op);

    llvm::StringMap<PartitionedCallDecompositionInfo>*
        decomposed_partitioned_call_callees) {
  // Rewrite the branches.
  Region& then_branch = if_op.getThenBranch();
  Region& else_branch = if_op.getElseBranch();
  if (failed(DecomposeTensorListOpsInternal(
          &then_branch.front(), module, buffer_to_size,
          decomposed_partitioned_call_callees)))
    return failure();
  if (failed(DecomposeTensorListOpsInternal(

    TF_Int32Tensor:$max_num_elements
  );
}

def TF_IfOp : TF_Op<"If", [DeclareOpInterfaceMethods<SymbolUserOpInterface>]> {
  let summary = "output = cond ? then_branch(input) : else_branch(input)";

  let description = [{
output = cond ? then_branch(input) : else_branch(input)

cond: A Tensor. If the tensor is a scalar of non-boolean type, the
    scalar is converted to a boolean according to the

  // CHECK: [[cond_res:%.*]]:2 = tfrt.cond [[cond]]
  // CHECK-SAME: @cond_true @cond_false(%arg0, %arg2) : (!tfrt.chain, !tfrt_fallback.tf_tensor)
  %2 = "tf.If"(%arg0, %arg1) {else_branch = @cond_false, then_branch = @cond_true, is_stateless = true} : (tensor<i1>, tensor<i32>) -> tensor<i32>
  // CHECK: [[out_ch:%.*]] = tfrt.merge.chains [[cond_res]]#0, %arg0 : !tfrt.chain, !tfrt.chain

    } else if (auto if_op = llvm::dyn_cast<TF::IfOp>(&op)) {
      auto then_branch = if_op.then_function();
      auto else_branch = if_op.else_function();
      // Recursively handle the nested control flow.
      (void)HoistForControlFlow(&then_branch.front(), module, vars_initialized,
                                lifted_partitioned_call_callees);

      /*is_stateless=*/false, if_region.get_thenFuncNameAttr(),
      if_region.get_elseFuncNameAttr());

  // Create empty then branch region.
  auto& then_branch = host_side_if.getThenBranch();
  then_branch.push_back(new Block);
  builder.setInsertionPointToEnd(&then_branch.front());
  builder.create<mlir::TF::YieldOp>(if_region.getLoc(),
                                    /*operands=*/ArrayRef<Value>{});

    %1 = "tf.Greater"(%0, %cst_0) {device = ""} : (tensor<f32>, tensor<f32>) -> tensor<i1>
    %2:2 = "tf.If"(%1, %arg0) <{else_branch = @cond_false_80, is_stateless = true, then_branch = @cond_true_70}> {Tcond = i1, Tin = [f32], Tout = [i1, f32], _lower_using_switch_merge = true, _read_only_resource_inputs = [], device = ""} : (tensor<i1>, tensor<1x4xf32>) -> (tensor<i1>, tensor<1x3xf32>)