%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 = func.call @func_2_CPU_FLOAT(%0, %1) {tac.interface_name = "func_2"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32>
    func.return %2 : tensor<2x1xf32>
  }

				c := 5
				func(z int) { // ERROR "can inline main.func28.1.1" "can inline main.func28.main.func28.1.2" "can inline main.main.func28.func35.1" "can inline main.main.func28.main.main.func28.func35.func37"
					a = a * x
					b = b * y
					c = c * z
				}(10) // ERROR "inlining call to main.func28.1.1"
				return a + c

    func.return %2 : tensor<2x100xf32>
  }
  func.func @func_2_CPU_FLOAT(%arg0: tensor<100xf32>, %arg1: tensor<100xf32>) -> tensor<2x100xf32> attributes {tac.cost = 2.000000e+01 : f32, tac.device = "CPU", tac.inference_type = "FLOAT", tac.interface_name = "func_2"} {

  ASSERT_EQ(func_->record->fdef().signature().attr().size(), 2);
  EXPECT_EQ(func_->record->fdef().signature().attr(0).name(), "v1");
  EXPECT_EQ(func_->record->fdef().signature().attr(0).type(), "int");
  EXPECT_EQ(func_->record->fdef().signature().attr(1).name(), "v2");
  EXPECT_EQ(func_->record->fdef().signature().attr(1).type(), "int");
}

void NodeWithAttrHelper(TF_Graph* graph, TF_Status* s, const char* name,

// CHECK:       return %0 : tensor<i32>
// CHECK:     }
// CHECK:     func.func private @func_0_CPU_FLOAT(%arg0: tensor<i32>) -> tensor<i32> attributes {tac.device = "CPU", tac.inference_type = "FLOAT", tac.interface_name = "func_0"} {
// CHECK:       %0 = "tfl.while"(%arg0) ({
// CHECK:       ^bb0(%arg1: tensor<i32>):

// See the example below:
//
// In main:
// %0 = tfl.const...
// %1 = tfl.const...
// %2 = call func_1(..., %0,...)
// %3 = call func_2(..., %0, ..., %1...)
// ...
//
// Then those consts will be copied into each function and replace their usage.
// func_1:
//   %0 = tfl.const...
// func_2:
//   %0 = tfl.const...
//   %1 = tfl.const...
class FoldConstantsToSubgraphPass

	go func() { // func9
		cv.L.Lock()
		cv.Wait()
		cv.L.Unlock()
	}()
	ln, err := net.Listen("tcp", "127.0.0.1:0")
	if err != nil {
		log.Fatalf("failed to listen: %v", err)
	}
	go func() { // func10
		c, err := ln.Accept()
		if err != nil {
			log.Printf("failed to accept: %v", err)
			return
		}
		c.Close()
	}()
	rp, wp, err := os.Pipe()
	if err != nil {

  ASSERT_TRUE(module_op);

  auto func_op = module_op->lookupSymbol<func::FuncOp>("fully_quantized_add");
  ASSERT_THAT(func_op, NotNull());

  auto add_op_itr = func_op.getBody().op_begin<mlir::stablehlo::AddOp>();
  ASSERT_THAT(add_op_itr,
              Ne(func_op.getBody().op_end<mlir::stablehlo::AddOp>()));

  EXPECT_TRUE(IsOpFullyQuantized(*add_op_itr));
}

    func::FuncOp func_op) {
  llvm::StringMap<FunctionMetadata> metadatas;
  WalkResult result = func_op.getBody().walk([&](Operation *op) {
    std::string op_host = GetHost(op);
    FunctionMetadata &func_metadata = metadatas[op_host];
    func_metadata.original_name = func_op.getName();
    func_metadata.insertion_point = ++Block::iterator(func_op);
    func_metadata.ops.push_back(op);

    }
    return failure();
  }
};

namespace {

bool IsShloMainFuncOp(func::FuncOp func_op) {
  if (func_op == nullptr) {
    return false;
  }

  if (!func_op.getSymName().contains(kStablehloModuleDefaultEntryFuncName)) {
    return false;
  }

  if (func_op.getSymVisibility() == "nested" ||
      func_op.getSymVisibility() == "private") {
    return false;
  }

  return true;
}