%cst = stablehlo.constant dense<0.000000e+00>: tensor<10x1024x3xf32>

    %0:2 = tf_executor.graph {

  func.func @serving_default(%arg0: tensor<1x10xf32> {tf_saved_model.index_path = ["x"]}) ->
    (tensor<1x10xf32> {tf_saved_model.index_path = ["output_0"]}, tensor<1x10xi64> {tf_saved_model.index_path = ["output_1"]}) attributes {tf.entry_function = {control_outputs = "", inputs = "serving_default_x:0", outputs = "StatefulPartitionedCall:0"}, tf_saved_model.exported_names = ["serving_default"]} {

  %0 = tf_executor.graph {
    %outputs, %control = tf_executor.island wraps "tf.HashTableV2"() {container = "", device = "", key_dtype = !tf_type.string, shared_name = "hash_table_ce3dfbfc-7367-4d62-9d48-d13bf8125391", use_node_name_sharing = false, value_dtype = i64} : () -> tensor<!tf_type.resource>
    %outputs_0, %control_1 = tf_executor.island wraps "tf.LookupTableSizeV2"(%outputs) {device = ""} : (tensor<!tf_type.resource>) -> tensor<i64>

    %outputs_3, %control_3 = tf_executor.island wraps "tf.TPUReplicatedOutput"(%outputs_2) {T = "tfdtype$DT_FLOAT", device = "", name = "output0", num_replicas = 1 : i64} : (tensor<0xf32>) -> tensor<0xf32>
    %outputs_4, %control_4 = tf_executor.island wraps "tf.Identity"(%outputs_3) {T = "tfdtype$DT_FLOAT", device = "", name = "output_0_shard_0"} : (tensor<0xf32>) -> tensor<0xf32>

Xiaopeng Han <******@****.***> 1686064488 +0800

        def operation = signing.sign(input1, input2)
        
        then:
        output1.exists() && output2.exists()
        [input1, input2] == operation.filesToSign.files.toList()[0..1]
        [output1, output2] == operation.signatureFiles.files.toList()[0..1]
        [output1, output2] == operation.signatures*.file.toList()
    }

    def "sign multiple artifacts with defaults"() {
        when:

  %output_1 = "tf.TensorArrayGatherV3"(%handle_3, %indices, %res_1#3) {device = "/job:localhost/replica:0/task:0/device:CPU:0", element_shape = #tf_type.shape<?x512>} : (tensor<2x!tf_type.resource<tensor<?x512xf32>>>, tensor<?xi32>, tensor<f32>) -> tensor<?x?x512xf32>
  func.return %output_0, %output_1 : tensor<?x?x512xf32>, tensor<?x?x512xf32>
}

        }
    }

    private void onlyTestClass1In(String output) {
        assert output.contains('TestClass1.testMethod')
        assert !output.contains('TestClass2.testMethod')
    }

    private void onlyTestClass2In(String output) {
        assert output.contains('TestClass2.testMethod')
        assert !output.contains('TestClass1.testMethod')
    }

        then:
        output1.toString().contains(ARG_1)
        output1.toString().contains(ARG_2)

        when:
        String output2 = runBuild { launcher -> launcher.addArguments(["-P$ARG_1" as String]).addArguments(["-P$ARG_2" as String]) }

        then:
        output2.toString().contains(ARG_1)