self.assertIn('stablehlo.add %arg0, %cst : tensor<4xf32>', str(module))

  def test_tf_mlir_to_stablehlo(self):
    assembly = """
      module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 268 : i32}} {
        func.func @main(%arg0 : tensor<?xf32>) -> tensor<?xf32> {
          %cst = "tf.Const"() {value = dense<1.0> : tensor<f32>} : () -> tensor<f32>

  }
  if (AttrType content = mlir::dyn_cast<AttrType>(attr)) {
    *out_attr = content;
    return true;
  } else {
    return false;
  }
}

// Changes a DenseIntElementsAttr **containing I64** elements to an I32 Vector.
bool DenseI64AttrToI32Vector(const DenseIntElementsAttr& dense_attr,
                             std::vector<int32_t>* out_vec);

// Gets boolean from composite attrs if it exists.

  %3 = "tfl.pack"(%1, %2) {axis = 0 : i32, per_device_costs = {CPU = 2.0 : f32, GPU = -1.0 : f32}, values_count = 2 : i32, tac.device = "CPU"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<2x1xf32>
  func.return %3 : tensor<2x1xf32>
})";
  const std::string kExpectedFB = CreateRuntimeMetadata();

		//
		// 	(import "gojs" "add" (func (param i32)))
		wi.Params = []obj.WasmField{{Type: obj.WasmI32}}
	} else {
		// All other imported functions use the normal WASM ABI.
		// Example:
		//
		// 	//go:wasmimport a_module add
		// 	func importedAdd(a, b uint) uint
		//
		// will roughly become
		//
		// 	(import "a_module" "add" (func (param i32 i32) (result i32)))
		abiConfig := AbiForBodylessFuncStackMap(f)

namespace mlir {
namespace mhlo {

using func::FuncOp;
using mlir::ModuleOp;

static constexpr char kMlirModuleStr[] = R"(
module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 1442 : i32}} {

    %4 = stablehlo.constant dense<4.000000e-01> : tensor<1x1x1xf32>  // Input 2 inverse scale (1 / s2).
    %5 = stablehlo.constant dense<0> : tensor<1x1x1xi8>  // Input 2 zero point (z2).
    %6 = stablehlo.constant dense<0> : tensor<1x1x1xi32>  // Input 2 zero point (z2) (upcast & folded into i32).

def LegalizeRelu6 : Pat<(TF_Relu6Op $arg), (TFL_Relu6Op $arg)>;
def LegalizeRelu : Pat<(TF_ReluOp $arg), (TFL_ReluOp $arg)>;
// TFL Relu doesn't support I32/I64 type, so legalizes TF Relu to TFL Maximum.
def LegalizeReluI32 :
  Pat<(TF_ReluOp TensorOf<[I32]>:$arg),
      (TFL_MaximumOp $arg,
        (Arith_ConstantOp ConstantAttr<RankedI32ElementsAttr<[]>,"0">))>;
def LegalizeReluI64 :
  Pat<(TF_ReluOp TensorOf<[I64]>:$arg),

DECL_CONVERT_OP(Unpack);
DECL_CONVERT_OP(Conv3D);
DECL_CONVERT_OP(Conv3DBackpropInputV2);

#undef DECL_CONVERT_OP

// Converts any IntegerAttr to an IntegerAttr of an i32 type.
// The value won't change in the new attribute, but if the value is out of
// the bound of i32, the function returns a failure.
LogicalResult ConvertToI32Attr(IntegerAttr attr, IntegerAttr* attr_i32) {
  if (attr.getType().isInteger(/*width=*/32)) {
    *attr_i32 = attr;

	close(f2()) // ERROR "too many arguments"
}

func complex1() {
	var i32 int32
	var f32 float32
	var f64 float64
	var c64 complex64
	var c128 complex128
	_ = complex() // ERROR "not enough arguments"
	_ = complex(1) // ERROR "not enough arguments"
	_ = complex(true /* ERROR "mismatched types" */ , 0)
	_ = complex(i32 /* ERROR "expected floating-point" */ , 0)
	_ = complex("foo" /* ERROR "mismatched types" */ , 0)

  let description = [{
    Cast a Tensor to int32.

    Example:
      %one = tf_mlrt.tensor_to_int32 %src_tenosr
  }];

  let arguments = (ins TFTensorType:$src);
  let results = (outs I32:$result);
  let assemblyFormat = "operands attr-dict";
}

def BoolToTensorOp : TensorflowMlrt_Op<"bool_to_tensor", [Pure]> {
  let summary = "Cast a boolean to a tensor.";
  let description = [{