func.func @init_func_restore_op() -> () attributes {tf_saved_model.exported_names = ["init"], tf_saved_model.initializer_type = "restore_op"} {
        %cst = "tf.Const"() {device = "", value = dense<[1.0, 2.0]> : tensor<2xf32>} : () -> tensor<2xf32>
        %add = "tf.AddV2"(%cst, %cst) : (tensor<2xf32>, tensor<2xf32>) -> tensor<2xf32>

func.func @decompose_batch_norm(%arg0: tensor<*xf32>) -> (tensor<*xf32>) {
  %cst = "tf.Const"() {value = dense<1.000000e+00> : tensor<2xf32>} : () -> tensor<2xf32>
  %cst_0 = "tf.Const"() {value = dense<0.500000e+00> : tensor<2xf32>} : () -> tensor<2xf32>

	continuec := make(chan struct{})
	cst := newClientServerTest(t, mode, HandlerFunc(func(w ResponseWriter, r *Request) {
		ctl := NewResponseController(w)
		w.Write([]byte("one"))
		if err := ctl.Flush(); err != nil {
			t.Errorf("ctl.Flush() = %v, want nil", err)
			return
		}
		<-continuec
		w.Write([]byte("two"))
	}))

	res, err := cst.c.Get(cst.ts.URL)
	if err != nil {

  "tf.InitializeTableFromTextFileV2"(%0, %cst) {delimiter = " ", device = "", key_index = -2 : i64, value_index = -1 : i64, vocab_size = -1 : i64} : (tensor<!tf_type.resource>, tensor<!tf_type.string>) -> ()
  func.return
}

// -----

// Tests that the tf.InitializeTableFromTextFileV2 op is not converted since
// unsupported key_index, -1.

func.func @init_all_tables() {

  [(IsNotInLiftedFunc $res), (FloatValueEquals<"0"> $cst)], [], (addBenefit 10)>;

def LiftDotGeneralWithRelu : Pat<
  (StableHLO_MaxOp:$res
    (StableHLO_DotGeneralOp
        $lhs, $rhs, $dot_dimension_numbers, $precision_config),
    (StableHLO_ConstantOp $cst)),
  (LiftAsTFXlaCallModule<"composite_dot_general_with_relu_fn">
    (ArgumentList $lhs, $rhs),

func.func @merge_requantization_followed_by_dequantization(%arg0: tensor<1x3x4x3xf32>) -> tensor<1x3x4x2xf32> {
  // CHECK: %[[CST:.*]] = stablehlo.constant dense<4.000000e-01> : tensor<2x3x3x2xf32>
  // CHECK: %[[QUANT_CST:.*]] = stablehlo.uniform_quantize %[[CST]]
  // CHECK: %[[QUANT_ARG_0:.*]] = stablehlo.uniform_quantize %[[ARG_0]]
  // CHECK: %[[CONV:.*]] = stablehlo.convolution(%[[QUANT_ARG_0]], %[[QUANT_CST]])

    %cst = arith.constant dense<"f"> : tensor<!tf_type.string>
    %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = i64, shared_name = "hash_table_dba2ccaa-f1b1-46d6-b276-98008f69da71", use_node_name_sharing = false, value_dtype = !tf_type.string} : () -> tensor<!tf_type.resource>

func.func @init_all_tables() {
  %cst = arith.constant dense<"tokens.txt"> : tensor<!tf_type.string>
  %0 = "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_/tmp/vocab.txt_-2_-1", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>

    %cst = "tf.Const"() {value = dense<1024> : tensor<i32>} : () -> tensor<i32>
    %0:2 = "tf_device.launch"() ({
	  %1 = "tf.Cast"(%arg0) {Truncate = false} : (tensor<2048xi64>) -> tensor<2048xi32>
	  %2 = "tf.Cast"(%arg1) {Truncate = false} : (tensor<2048xi64>) -> tensor<2048xi32>

func.func @remove_volatile_qdq() -> tensor<3x2xf32> {
  // CHECK: %[[CST:.*]] = stablehlo.constant
  // CHECK-NOT: "quantfork.qcast"
  // CHECK-NOT: "quantfork.dcast"
  // CHECK: return %[[CST]]
  %cst = stablehlo.constant dense<[[-0.960978984, -0.390246302], [-0.790828585, -0.601039409], [-1.0280807, -1.02731466]]> : tensor<3x2xf32>