// CHECK-NEXT: return [[result]]
    %0 = tf_executor.graph {
      %outputs, %control = tf_executor.island wraps "tf.Const"() {device = "", value = dense<1> : tensor<i32>} : () -> tensor<i32>
      %outputs_0, %control_1 = tf_executor.island wraps "tf.Const"() {device = "", value = dense<20> : tensor<i32>} : () -> tensor<i32>
      %outputs_2, %control_3 = tf_executor.island wraps "tf.Const"() {device = "", value = dense<0> : tensor<i32>} : () -> tensor<i32>

        tf_executor.graph {
          %control_0 = tf_executor.island wraps "tf.PartitionedCall"() <{config = "", config_proto = "", executor_type = "", f = @function_1}> : () -> ()
          %control_1 = tf_executor.island wraps "tf.PartitionedCall"() <{config = "", config_proto = "", executor_type = "", f = @function_2}> : () -> ()
          tf_executor.fetch %control_0, %control_1 : !tf_executor.control, !tf_executor.control
        }
        return

    %0 = tf_executor.graph {
      %outputs_0, %control_0 = tf_executor.island wraps "tf.VarHandleOp"() {container = "", shared_name = ""} : () -> tensor<!tf_type.resource<tensor<501000x128xf32>>>
      %outputs_1, %control_1 = tf_executor.island wraps "tf.Cast"(%outputs_0) {Truncate = false} : (tensor<!tf_type.resource<tensor<501000x128xf32>>>) -> tensor<*x!tf_type.resource>

	v.Uses++
}

// ResetControls sets the number of controls for the block to 0.
func (b *Block) ResetControls() {
	if b.Controls[0] != nil {
		b.Controls[0].Uses--
	}
	if b.Controls[1] != nil {
		b.Controls[1].Uses--
	}
	b.Controls = [2]*Value{} // reset both controls to nil
}

// AddControl appends a control value to the existing list of control values.
func (b *Block) AddControl(v *Value) {

  %1,%control_1 = tfl.control_node controls "tfl.sub" (%arg0, %0) {fused_activation_function = "RELU6"} : (tensor<3x2xi32>, tensor<3x2xi32>) -> tensor<3x2xi32> loc("sub")
  %2 = "arith.constant" () {value = dense<10> : tensor<i32>} : () -> tensor<i32> loc("SameNameAsOutput")

// RUN: tf-opt %s -pass-pipeline='builtin.module(tf-functional-control-flow-to-regions{allow-passthrough-args})' -split-input-file -verify-diagnostics | FileCheck %s

// Simple If
// CHECK: func private @testIf1Then{{.+}}
// CHECK: func private @testIf1Else{{.+}}
func.func private @testIf1Then(tensor<*xf32>) -> tensor<*xf32>
func.func private @testIf1Else(tensor<*xf32>) -> tensor<*xf32>

// CHECK-LABEL: func @testIf1Result(%arg0: tensor<i1>, %arg1: tensor<*xf32>)

}
// CHECK-NEXT: %[[VAR:.*]], %[[CONTROL:.*]] = tfl.control_node controls "tfl.var_handle"
// CHECK-NEXT: return %[[VAR]]


// CHECK-LABEL: @tfl_call_once_gets_control_node
func.func @tfl_call_once_gets_control_node() -> () {
  "tfl.call_once"() { session_init_function = "noop" } : () -> ()
  func.return
}
// CHECK-NEXT: control_node controls "tfl.call_once"
// CHECK-NEXT: return

  %1,%control_1 = tfl.control_node controls "tfl.sub" (%arg0, %0) {fused_activation_function = "RELU6"} : (tensor<3x2xi32>, tensor<3x2xi32>) -> tensor<3x2xi32> loc("sub")
  %2 = "arith.constant" () {value = dense<10> : tensor<i32>} : () -> tensor<i32> loc("SameNameAsOutput")

$(document).ready(function () {

    // Attach controls for column groups in tables
    var controls = $("div#controls");
    var groups = [];
    var slices = [];
    $("tr.control-groups").closest("table").find("tr").each(function() {
        var row = $(this);
        if (row.hasClass('control-groups')) {
            var currentCol = 0;
            slices = [];
            row.find("th").each(function(){
                var e = $(this);

		return false
	}

	// Don't merge control values if b is likely to be bypassed anyway.
	if p.Likely == BranchLikely && p.Succs[0].Block() != b {
		return false
	}
	if p.Likely == BranchUnlikely && p.Succs[1].Block() != b {
		return false
	}

	// Check if the control values combine to make an integer inequality that
	// can be further optimized later.
	bc := b.Controls[0]
	pc := p.Controls[0]