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:

        outputContains(output3)

        where:
        expression                                                                                      | output1                     | output2                            | output3

// Tests input and output names from FlatBuffer are added to `tf.entry_function` attribute.

// CHECK-LABEL: @main
func.func @main(%arg0: tensor<4xi8>, %arg1: tensor<4xi32>) -> (tensor<4xi32>, tensor<4xi8>)
// CHECK: attributes {tf.entry_function = {inputs = "input0,input1", outputs = "output0,output1"}}
attributes {tf.entry_function = {inputs = "input0,input1", outputs = "output0,output1"}} {

        }
    }

    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)

          ],
          "name": "output0",
          "quantization": {
          }
        },
        {
          "shape": [
            128,
            32,
            32,
            3
          ],
          "name": "output1",
          "quantization": {
          }
        }
      ],
      "inputs": [
        0,
        1
      ],
      "outputs": [
        2,
        3
      ],

  %graph_result = tf_executor.graph {
    %output0, %control0 = tf_executor.island {
      %a = "tf.opA"(%arg0) : (tensor<i32>) -> tensor<i32>
      tf_executor.yield %a : tensor<i32>
    }
    %output1, %control1 = tf_executor.island {
      %b = "tf.opB"(%output0) : (tensor<i32>) -> tensor<i32>
      tf_executor.yield %b : tensor<i32>
    }
    tf_executor.fetch %output1 : tensor<i32>
  }

        withWatchFs().run ":incremental", "-DoutputDir=output1"
        then:
        executedAndNotSkipped(":incremental")

        when:
        file("build/output2/overlapping.txt").text = "overlapping"
        waitForChangesToBePickedUp()
        withWatchFs().run ":incremental", "-DoutputDir=output2"
        then:
        executedAndNotSkipped(":incremental")
        file("build/output1").assertDoesNotExist()

        when:

  std::unordered_set<string> outputs;
  TF_ASSERT_OK(FreezeSavedModel(saved_model_bundle, &frozen_graph_def, &inputs,
                                &outputs));
  std::unordered_set<string> expected_inputs = {"input0:0", "input1:0"};
  std::unordered_set<string> expected_outputs = {"output0:0", "output1:0"};
  EXPECT_EQ(expected_inputs, inputs);
  EXPECT_EQ(expected_outputs, outputs);
}

                }
                outputs.files files(fileList) withPropertyName("out")
                def output1 = project.file("build/output1.txt")
                def output2 = project.file("build/output2.txt")
                doLast {
                    output1.parentFile.mkdirs()
                    output1 << "data"
                    if (!System.getProperty("changedCardinality")) {