then:
        output.toString().contains("task logging")
        output.toString().contains("warn logging")
        output.toString().contains("lifecycle logging")
        output.toString().contains("quiet logging")
        if (targetVersion.baseVersion >= GradleVersion.version('4.7')) {
            // Changed handling of error log messages
            output.toString().contains("error logging")
        } else {

        when:
        outputs.snapshot { run "compileJava" }
        a.text = "class A { public void foo() {} }"
        run "compileJava", "--info"

        then:
        outputs.recompiledClasses("A")
    }

    def "generated files and classes are deleted when processor is removed"() {
        given:
        java "@Thing class A {}"

        when:
        outputs.snapshot { run "compileJava" }

                absl::Span<AbstractTensorHandle*> outputs, bool use_function) {
  if (use_function) {
    const char* fn_name = "test_fn";
    core::RefCountPtr<AbstractFunction> scoped_func;
    // Returning null tensors from a tf.function is not supported, so we keep
    // track of indices in the model's outputs are nullptr in this set.
    // The FunctionDef only outputs the non-null tensors. We later pad the

     * {@inheritDoc}
     */
    @Override
    ImmutableSortedMap<String, CurrentFileCollectionFingerprint> getInputFileProperties();

    /**
     * Snapshots of the roots of output properties.
     *
     * This includes snapshots for the whole output {@link org.gradle.api.file.FileCollection}.
     *
     * @see PreviousExecutionState#getOutputFilesProducedByWork()
     * @see AfterExecutionResult#getAfterExecutionOutputState()
     */

        // If there are different output properties compared to the previous execution, then we do have output changes
        if (!previous.keySet().equals(current.keySet())) {
            return true;
        }

        // Otherwise, do deep compare of outputs
        ChangeDetectorVisitor visitor = new ChangeDetectorVisitor();

};

// Idenitfy tf_device.cluster_func input-output alias pairs.
// This is currently conservative, primarily handling the following base case:
// ```
// %value = tf.ReadVariableOp(%resource_var)
// %output:N = tf_device.cluster_func(..., /*input index = a*/ %value, ...)
// tf.AssignVariableOp(%resource_var, %output#b) // write output #b to resource
// ```
// where `%value` and `%output#b` have only one use. (a, b) would be added as

OutputTensor ToOutputTensor(const Output& output) {
  return OutputTensor(output.node(), output.index());
}

// Utility function for converting to internal C++ datatypes.
std::vector<OutputTensor> ToOutputTensors(const std::vector<Output>& outputs) {
  std::vector<OutputTensor> result(outputs.size());
  for (int i = 0; i < outputs.size(); ++i) {
    result[i] = ToOutputTensor(outputs[i]);
  }
  return result;
}

        then:
        repository.isGeneratedByGradle(file('build'))
        repository.isGeneratedByGradle(file('build/outputs'))
        repository.isGeneratedByGradle(file('build/outputs/directory'))
        repository.isGeneratedByGradle(file('build/outputs/directory/subdir'))
        repository.isGeneratedByGradle(file('build/file'))
        repository.isGeneratedByGradle(file('build/file/other'))

            withArgument("--max-workers=$threadCount")
        }
    }

    def "overlapping outputs prevent parallel execution"() {
        given:
        withParallelThreads(2)

        and:
        buildFile << """
            aPing.outputs.dir "dir"
            bPing.outputs.file "dir/file"
        """
        expect:
        2.times {

# RUN: tf_tfl_translate -unfold_batchmatmul=false -tf-input-arrays=Placeholder,Placeholder_1 -tf-input-shapes=2,5,3:3,7 -tf-input-data-types=DT_FLOAT,DT_FLOAT -tf-output-arrays=MatMul -output-mlir %s -o - 2>&1 | FileCheck %s

node {
  name: "Placeholder"
  op: "Placeholder"
  attr {
    key: "dtype"
    value {
      type: DT_FLOAT
    }
  }
  attr {
    key: "shape"
    value {
      shape {
        dim {
          size: 2