b := 3
			return func(y int) int { // ERROR "can inline main.func27.1" "can inline main.main.func27.func34"
				c := 5
				return func(z int) int { // ERROR "can inline main.func27.1.1" "can inline main.main.func27.func34.1" "can inline main.func27.main.func27.1.2" "can inline main.main.func27.main.main.func27.func34.func36"
					return a*x + b*y + c*z
				}(10) // ERROR "inlining call to main.func27.1.1"

    %2 = func.call @func_2_CPU_FLOAT(%0, %1) {tac.device = "CPU", tac.inference_type = "FLOAT", tac.interface_name = "func_2"} : (tensor<100xf32>, tensor<100xf32>) -> tensor<2x100xf32>
    func.return %2 : tensor<2x100xf32>
  }

  func.return %0 : tensor<i32>
}
}

// CHECK:     func.func @simpleWhile(%arg0: tensor<i32>) -> tensor<i32> {
// CHECK:       %0 = call @func_0_CPU_FLOAT(%arg0) {tac.device = "CPU", tac.inference_type = "FLOAT", tac.interface_name = "func_0"} : (tensor<i32>) -> tensor<i32>
// CHECK:       return %0 : tensor<i32>
// CHECK:     }

module {
  func.func @simpleTest(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>, %arg2: tensor<1xf32>, %arg3: tensor<1xf32>) -> tensor<2x1xf32> {
    %0 = func.call @func_0_GPU_FLOAT(%arg0, %arg1, %arg2) {tac.interface_name = "func_0"} : (tensor<1xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>
    %1 = func.call @func_1_GPU_FLOAT(%arg0, %arg3) {tac.interface_name = "func_1"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

    %2:2 = tf_executor.island(%1#1) {
      %4 = "tf.opB"() : () -> tensor<f32>
      tf_executor.yield %4 : tensor<f32>
    }
    tf_executor.fetch %2#0 : tensor<f32>
  }
  func.return %0 : tensor<f32>
}

// CHECK-LABEL: @func2
func.func @func2(%arg0 : tensor<i1>) -> tensor<i1> {
  %0 = tf_executor.graph {
    %1:2 = tf_executor.island {
      %4 = "tf.opB"() : () -> tensor<f32>
      tf_executor.yield %4 : tensor<f32>
    }

	// the rest of the test, they will block.
	go func() { // func1
		select {}
	}()
	go func() { // func2
		var c chan int
		c <- 0
	}()
	go func() { // func3
		var c chan int
		<-c
	}()
	done1 := make(chan bool)
	go func() { // func4
		<-done1
	}()
	done2 := make(chan bool)
	go func() { // func5
		done2 <- true
	}()
	c1 := make(chan int)
	c2 := make(chan int)

            argument_index = i;
            break;
          }
        }

        // Copy the const into the consumer func and replace their usages.
        func::FuncOp func = module.lookupSymbol<func::FuncOp>(function_name);

        CopyConstantIntoFunc(argument_index, op, func);
      }
    });
  }
}

}  // namespace

std::unique_ptr<OperationPass<ModuleOp>> CreateFoldConstantsToSubgraphPass(

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_COMMON_FUNC_H_

#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

namespace mlir::quant {

// Returns a public `func::FuncOp` in `module_op` whose name matches either
// `main` or `serving_default`. If `func::FuncOps` with both names exist, the
// function with name "main" takes precedence. Returns null if no such a

func add(x, y int) int {
	return x + y
}

func fn() func(int, int) int {
	return f
}

var fc func(int, int, chan int)

func addc(x, y int, c chan int) {
	c <- x+y
}

func fnc() func(int, int, chan int) {
	return fc
}

func three(x int) {
	if x != 3 {
		println("wrong val", x)
		panic("fail")
	}
}

var notmain func()

func emptyresults() {}
func noresults()    {}

// Verify that illegal function signatures are detected.
// Does not compile.

package main

type t1 int
type t2 int
type t3 int

func f1(*t2, x t3)	// ERROR "named"
func f2(t1, *t2, x t3)	// ERROR "named"
func f3() (x int, *string)	// ERROR "named"