// RUN: tf-opt %s -cse  | FileCheck %s
// Checks that CSE runs without generating invalid IR and doesn't CSE ops like
// NextIteration.Source and NextIteration.Sink.
// CHECK-LABEL: func @main
// CHECK: tf_executor.NextIteration.Source
// CHECK: tf_executor.NextIteration.Source
// CHECK: tf_executor.NextIteration.Sink
// CHECK: tf_executor.NextIteration.Sink
func.func @main() -> (tensor<1xi32>, tensor<1xi32>) {
  %0, %1 = tf_executor.graph {

  // CHECK:  op: "RefMerge"
  // CHECK:  op: "RefSwitch"
  // CHECK:  op: "RefExit"
  // CHECK:  op: "RefNextIteration"
  tf_executor.graph {
    %0:3 = tf_executor.NextIteration.Source : tensor<*x!tf_type.int32ref> {device = "", T = "tfdtype$DT_INT32"} loc("while/NextIteration")

    tf_executor.NextIteration.Sink[%1#1] %1#0 : i32
    tf_executor.fetch %1#0 : i32
  }
  func.return %0 : i32
}

// Check that NextIteration.sink node is deleted when the source does not have
// any user other than the sink.
// CHECK-LABEL: func @nextiteration_deleted(
func.func @nextiteration_deleted(%arg0 : i32) -> i32 {
// CHECK-NOT: tf_executor.NextIteration.Source
// CHECK-NOT: tf_executor.NextIteration.Sink

  // CHECK-NEXT: input: "while/Enter"
  // CHECK-NEXT: input: "while/NextIteration"
  // CHECK:      name: "while/NextIteration"
  // CHECK-NEXT: op: "NextIteration"
  // CHECK-NEXT: input: "while/Add"
  tf_executor.graph {
    %0:3 = tf_executor.NextIteration.Source : tensor<*xi32> {device = "", T = "tfdtype$DT_INT32"} loc("while/NextIteration")

    %NextIteration, %ctl_1 = NextIteration(%Add) name("while/NextIteration") {T = i32} : (tensor<*xi32>) -> (tensor<*xi32>)
    %Merge:2, %ctl_2 = Merge(%Enter, %NextIteration) name("while/Merge") {N = 2 : i64, T = i32} : (tensor<*xi32>, tensor<*xi32>) -> (tensor<*xi32>, tensor<*xi32>)

    %NextIteration, %ctl_1 = NextIteration(%Const) [%arg.ctl] name("while/NextIteration") {T = i32} : (tensor<i32>) -> (tensor<*xi32>)
    %Merge:2, %ctl_2 = Merge(%Enter, %NextIteration) [%arg.ctl] name("while/Merge") {N = 2 : i64, T = i32} : (tensor<*xi32>, tensor<*xi32>) -> (tensor<*xi32>, tensor<i32>)

    result[i] = outputs[i].node();
  }
  return result;
}

// Manually generates the name of the `loop_var_idx`-th NextIteration node of a
// loop being constructed with `scope`. This is used to define the backedge
// before the NextIteration node is created.
string NextIterationName(const Scope& scope, int loop_var_idx) {
  string result;
  const string& prefix = scope.impl()->name();

        });
  }

  VisitOpOperands(graph, op, reachable_ops, ops_to_visit);

  // If op is a `tf_executor.NextIteration.Source`, visit its associated
  // `tf_executor.NextIteration.Sink` op.
  if (auto source_op = llvm::dyn_cast<NextIterationSourceOp>(op)) {
    Operation* sink_op = source_op.GetSink().getOperation();

// with that limited clustering..
//
//
// NB!  The result computed by this analysis assumes that we don't auto-cluster
// back-edges (i.e. the edges from NextIteration to Merge).
//
// NB!  The result computed by this analysis assumes that we don't auto-cluster
// functional control flow nodes containing resource operations.
//

 FloorMod 1
 GreaterEqual 7
 Identity 113
 IsVariableInitialized 1
 IteratorGetNext 1
 IteratorV2 1
 Less 9
 LogicalAnd 3
 LoopCond 8
 Max 4
 Maximum 44
 Merge 145
 Minimum 43
 Mul 8
 NextIteration 136
 RandomUniform 14
 Range 9
 RefSwitch 166
 Reshape 2
 ScatterAdd 4
 Shape 6
 ShapeN 10
 Size 2
 Snapshot 1
 StackPopV2 314
 StackPushV2 314
 StackV2 314
 StridedSlice 12
 Sub 5