func.return %arg0 : tensor<*xi1>
  }
  func.func @"tpu_subgraph"(%arg0: tensor<*xi64>) -> tensor<*xi1> {
    %cst = "tf.Const"() {value = dense<0> : tensor<i64>} : () -> tensor<i64>
    %cst_0 = "tf.Const"() {value = dense<0> : tensor<i32>} : () -> tensor<i32>
    %cst_1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>

// CHECK: "tfl.fully_connected"(%arg0, %arg1, [[NONE]])
// CHECK-SAME: (tensor<40x37xf32>, tensor<40x37xf32>, none) -> (tensor<40x40xf32>, tensor<40x40xf32>)
  %cst = "tfl.no_value"() {value = unit} : () -> none
  %0:2 = "tfl.fully_connected"(%arg0, %arg1, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<40x37xf32>, tensor<40x37xf32>, none) -> (tensor<40x40xf32>, tensor<40x40xf32>)

  func.return %7 : tensor<1x3x2x2xf32>
}

// CHECK: func @tpu_conv(%[[ARG0:.*]]: tensor<1x3x4x3xf32>)
// CHECK-DAG: %[[cst:.*]] = "tf.Const"() <{value = dense_resource<__elided__> : tensor<2x3x3x2xbf16>}> {device = ""} : () -> tensor<2x3x3x2xbf16>
// CHECK: %[[cast:.*]] = "tf.Cast"(%[[cst]]) <{Truncate = false}> : (tensor<2x3x3x2xbf16>) -> tensor<2x3x3x2xf32>
// CHECK: %[[conv:.*]] = "tf.Conv2D"(%[[ARG0]], %[[cast]])

		t.Run(tt.name, func(t *testing.T) {
			cst := NewUnstartedServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
				w.Header().Set("X-Proto", r.Proto)
			}))

			switch tt.name {
			case "http2":
				cst.EnableHTTP2 = true
				cst.StartTLS()
			default:
				cst.Start()
			}

			defer cst.Close()

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

      %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 @mean_4d_keepdim(%arg0: tensor<1x48x48x512xf32>) -> tensor<1x1x1x512xf32> {
  %cst = arith.constant dense<[1, 2]> : tensor<2xi32>
  %0 = "tfl.mean"(%arg0, %cst) {keep_dims = true} : (tensor<1x48x48x512xf32>, tensor<2xi32>) -> tensor<1x1x1x512xf32>
  func.return %0 : tensor<1x1x1x512xf32>
}

// CHECK-NEXT:  return 
//
module {
  func.func @serving_default() -> tensor<*xi32> {
    %cst = "tf.Const"() <{value = dense<"some_test.txt"> : tensor<!tf_type.string>}> : () -> tensor<!tf_type.string>
    %0 = "tf.VarHandleOp"() <{container = "", shared_name = "Variable"}> : () -> tensor<!tf_type.resource<tensor<!tf_type.string>>>

// If the tfl.dequantize op wasn't fused, we shouldn't quantize the floating
// point constant.
def : Pat<(TFL_DequantizeOp
             (TFL_QuantizeOp (Arith_ConstantOp F32ElementsAttr:$cst), $qt)),
          (TFL_ConstOp $cst)>;

// Transpose conv supports hybrid computation with quantized weights.
def FoldQuantWeightsIntoTposeConv : Pat<
  (TFL_TransposeConvOp
    $output_shape,
    (TFL_DequantizeOp $quant_weights),

    return %0 : tensor<*xf32>
  }

// CHECK: %[[cst:.*]] = "arith.constant"() <{value = dense<0.000000e+00> : tensor<2x1024xf32>}> : () -> tensor<2x1024xf32>
// CHECK: %[[q_cst:.*]] = "quantfork.qcast"(%[[cst]]) : (tensor<2x1024xf32>) -> tensor<2x1024x!quant.uniform<i8<-127:127>:f32, 3.9370078740157481E-9>>

    "Is not a constant.">;

def : Pat<(StableHLO_DivOp $l,
            (StableHLO_ConstantOp:$divisor FloatElementsAttr<32>:$cst)),
          (StableHLO_MulOp $l,
            (StableHLO_DivOp
              (StableHLO_ConstantOp (CloneF32ElementsAttrWithOnes $cst)),
              $divisor)),