// CHECK: %[[INPUT0:.*]] = "tf.Placeholder.input"
  %0 = "tf.Placeholder.input"(%arg0) : (tensor<f32>) -> tensor<f32>
  // CHECK: %[[INPUT1:.*]] = "tf.Placeholder.input"
  %1 = "tf.Placeholder.input"(%arg1) : (tensor<f32>) -> tensor<f32>
  %2 = arith.constant dense<true> : tensor<i1>

  // CHECK: "tf.Multiply"(%[[INPUT1]], %[[INPUT0]])

    }

    private static String customTaskCode(String input1, String input2) {
        """
            ${customTaskImpl()}
            task customTask(type: CustomTask){
                input1 = '$input1'
                input2 = '$input2'
            }
        """
    }

    private static String customTaskImpl() {
        """

		},
		{
			name:         "Success when response contains multiple certs",
			in:           input1,
			extraCerts:   serverCerts,
			statusCode:   http.StatusOK,
			body:         validSpiffeX509BundleWithMultipleCerts,
			wantNumCerts: 2,
		},
		{
			name:        "Bundle endpoint is not trusted",
			in:          input1,
			extraCerts:  nil,
			statusCode:  http.StatusOK,
			body:        validSpiffeX509Bundle,

  EXPECT_EQ("Tensor<type: float shape: [2,3] values: [1 2 3][4 5 6]>",
            output->DebugString(100));
}

REGISTER_OP("DoNothingOp")
    .Input("input1: float")
    .Input("input2: float")
    .Attr("NumInput3: int >= 0")
    .Input("input3: NumInput3 * float")
    .Output("output1: float")
    .Attr("SomeDataTypeAttr: type");

TEST_F(DeviceKernelOpTest, TestGetKernelInfo) {

// CHECK-NEXT:    name: "min_runtime_version",
// CHECK-NEXT:    buffer: 6
// CHECK-NEXT:  } ],
// CHECK-NEXT:  signature_defs: [ {
// CHECK-NEXT:    inputs: [ {
// CHECK-NEXT:      name: "input1",
// CHECK-NEXT:      tensor_index: 1
// CHECK-NEXT:    }, {
// CHECK-NEXT:      name: "input2"
// CHECK-NEXT:    } ],
// CHECK-NEXT:    outputs: [ {
// CHECK-NEXT:      name: "end_logits",
// CHECK-NEXT:      tensor_index: 4

      (BinaryOp (TFL_ReshapeOp:$lhs $input1, (Arith_ConstantOp:$shape1 $s1)),
                (TFL_ReshapeOp:$rhs $input2, (Arith_ConstantOp:$shape2 $s2))),
      (TFL_ReshapeOp (BinaryOp $input1, $input2), $shape1),
      [(IsTailOfShape $rhs, $lhs),
       (IsTailOfShape $lhs, $rhs),
       (IsTailOfShape $input1, $input2),
       (IsTailOfShape $input2, $input1),
       (SameElementType $input1, $input2)]>;

  %10 = "tf.opK"() : () -> tensor<*xi16>
  %11 = "tf.opL"() : () -> tensor<*xi64>
  tf_device.replicate([%0, %1, %2] as %input0: tensor<*xi1>, %9 as %input1: tensor<*xi8>, %10 as %input2: tensor<*xi16>, [%3, %4, %5] as %input3: tensor<*xi32>, [%6, %7, %8] as %input4: tensor<*xf32>, %11 as %input5: tensor<*xi64>) {n = 3 : i32} {
    tf_device.return
  }
  func.return

// CHECK:      %[[OP_A:[a-z0-9]*]] = "tf.opA"

// CHECK-NEXT:    name: "min_runtime_version",
// CHECK-NEXT:    buffer: 8
// CHECK-NEXT:  } ],
// CHECK-NEXT:  signature_defs: [ {
// CHECK-NEXT:    inputs: [ {
// CHECK-NEXT:      name: "input1",
// CHECK-NEXT:      tensor_index: 1
// CHECK-NEXT:    }, {
// CHECK-NEXT:      name: "input2"
// CHECK-NEXT:    } ],
// CHECK-NEXT:    outputs: [ {
// CHECK-NEXT:      name: "end_logits",
// CHECK-NEXT:      tensor_index: 5

// RUN: tac-translate -input-mlir -output-mlir -device-specs=GPU %s -o - 2>&1 | FileCheck %s

module {
func.func @main(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>, %arg2: tensor<1xf32>, %arg3: tensor<1xf32>) -> tensor<2x1xf32> attributes {tf.entry_function = {inputs = "input0,input1,input2,input3", outputs = "output"}} {
  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32>

    }

    def "can increase the quiet period"() {
        given:
        inputDir.createDir("input1")
        inputDir.createDir("input2")
        def inputFile1 = inputDir.file("input1/input.txt")
        def inputFile2 = inputDir.file("input2/input.txt")

        when:
        succeeds("theTask", "-D${StartParameterBuildOptions.ContinuousBuildQuietPeriodOption.PROPERTY_NAME}=5000")