protocol, ip string
	port         int32
}

type hostPortInfoBuilder struct {
	inputs []hostPortInfoParam
}

func newHostPortInfoBuilder() *hostPortInfoBuilder {
	return &hostPortInfoBuilder{}
}

func (b *hostPortInfoBuilder) add(protocol, ip string, port int32) *hostPortInfoBuilder {
	b.inputs = append(b.inputs, hostPortInfoParam{protocol, ip, port})
	return b
}

You have to define the task inputs and outputs manually.

2. Using a task as a copy source, i.e., as an argument to `from()`, won't create an automatic task dependency between your task and that copy source.
As such, if you use the `copy()` method as part of a task action, you must explicitly declare all inputs and outputs to get the correct behavior.

					DeleteMarker: false,
				},
				{
					Name:         "unique/folder/1.txt",
					DeleteMarker: false,
				},
			},
		},
	}

	testCases := []struct {
		// Inputs to ListObjects.
		bucketName string
		prefix     string
		marker     string
		delimiter  string
		maxKeys    int
		versioned  bool
		// Expected output of ListObjects.
		resultL ListObjectsInfo

                void transform(TransformOutputs outputs) {
                    def input = inputArtifact.get().asFile
                    println "converting \${input.name} to red"
                    assert input.file
                    def output = outputs.file(input.name + ".red")
                    output.text = input.text + ".red"
                }
            }

            dependencies {

                    def input = inputArtifact.get().asFile
                    if (input.exists()) {
                        println "processing \${input.name}"
                    } else {
                        println "processing missing \${input.name}"
                    }
                    def output = outputs.file(input.name + ".green")
                    output.text = input.list().length + ".green"
                }

      }
    }
  }
  return has_quantized_types_for_weights;
}

// Checks if all the inputs are quantized.
bool IsQuantizedCallforStaticRange(TF::PartitionedCallOp call_op) {
  bool has_quantized_types = false;
  for (Value input : call_op.getArgs()) {
    if (auto type = mlir::dyn_cast<TensorType>(input.getType())) {
      if (mlir::isa<QuantizedType>(type.getElementType())) {
        has_quantized_types = true;

[[declare_unreadable_input_output]]
==== Declaring input or output directories which contain unreadable content

For up-to-date checks Gradle relies on tracking the state of the inputs and the outputs of a task.
Gradle used to ignore unreadable files in the input or outputs to support certain use-cases, although it cannot track their state.

		srcPath     string
		expectedErr error
	}{
		// TestXLStorage case - 1.
		// TestXLStorage case with valid inputs, expected to pass.
		{
			srcVol:      "success-vol",
			srcPath:     "success-file",
			expectedErr: nil,
		},
		// TestXLStorage case - 2.
		// TestXLStorage case with valid inputs, expected to pass.
		{
			srcVol:      "success-vol",
			srcPath:     "path/to/success-file",

                    assertThat(peeker.getDone(input1)).isSameInstanceAs("value1");
                    try {
                      peeker.getDone(input2Failed);
                      fail("Peeker should fail for failed inputs");
                    } catch (ExecutionException expected) {
                    }
                    try {
                      peeker.getDone(nonInput);

                            &output_permutation, &call_node_def_));

    // Apply the input/output permutations to the 'args_by_...' and 'results_'
    // mappings, so when we build edges in BuildOutputGraph() we
    // connect them to the right input/output positions.
    if (input_permutation.size() != args_by_src_.size()) {
      return errors::InvalidArgument("Input permutation has incorrect size.");
    }