As a consequence, if we want our instrumented classes to be used in place of this variant when executing tests, we need to attach similar attributes to our variant.
In fact, the attribute we care about is `org.gradle.libraryelements` which explains _what the variant contains_, so we can setup the variant this way:

.Declaring the variant attributes
====

	if needSort {
		sort.Sort(variantsSort{varID, variant})
		k, l := 0, -1
		for i, v := range varID {
			w := int(v)
			if l == w {
				// Remove duplicates.
				continue
			}
			varID[k] = varID[i]
			variant[k] = variant[i]
			k++
			l = w
		}
		if str := bytes.Join(variant[:k], separator); len(str) == 0 {
			end = start - 1
		} else {
			scan.resizeRange(start, end, len(str))

Finally, Gradle selects the appropriate variant by looking at the variant attributes:

- the consumer wants a variant with attributes `org.gradle.usage=java-api`
- the producer has a matching variant (`apiElements`)
- the producer has a non-matching variant (`runtimeElements`)

Gradle provides the artifacts and dependencies from the `apiElements` variant to the consumer.

== A more complicated example

	// replicas is the number of Pods created by the StatefulSet controller.
	Replicas int32 `json:"replicas" protobuf:"varint,2,opt,name=replicas"`

	// readyReplicas is the number of pods created by this StatefulSet controller with a Ready Condition.
	ReadyReplicas int32 `json:"readyReplicas,omitempty" protobuf:"varint,3,opt,name=readyReplicas"`

  %zeros-like = "tf.ZerosLike"(%addn) : (tensor<!tf_type.variant<tensor<f32>>>) -> tensor<!tf_type.variant<tensor<f32>>>
  // CHECK-NEXT: %[[ADDN2:.*]] = "tf.AddN"(%[[ADDN]], %[[ZEROS_LIKE]]) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32>
  %addn2 = "tf.AddN"(%addn, %zeros-like) : (tensor<!tf_type.variant<tensor<f32>>>, tensor<!tf_type.variant<tensor<f32>>>) -> tensor<!tf_type.variant<tensor<f32>>>

// -----

func.func @testIfThen(%arg0: tensor<!tf_type.variant>) -> tensor<!tf_type.variant> {
  func.return %arg0 : tensor<!tf_type.variant>
}
func.func @testIfElse(%arg0: tensor<!tf_type.variant>) -> tensor<!tf_type.variant> {
  func.return %arg0 : tensor<!tf_type.variant>
}

// CHECK-LABEL: func @testIfCasts(%arg0: tensor<i1>, %arg1: tensor<!tf_type.variant<tensor<f32>>>) -> tensor<!tf_type.variant<tensor<f32>>>

                }
            }
        }
    }

    def "can select both main variant and test fixtures of a single component"() {
        given:
        repository {
            'org:foo:1.0' {
                variant('api') {}
                variant('runtime') {}
                variant('test-fixtures') {
                    artifact('test-fixtures')

  %0 = "tf.TensorListLength"(%arg1) : (tensor<!tf_type.variant>) -> tensor<i32>
  %1 = "tf.Identity"(%arg1) : (tensor<!tf_type.variant>) -> tensor<!tf_type.variant>
  func.return %0, %1 : tensor<i32>, tensor<!tf_type.variant>

// verify `body` function's signature.
// CHECK: func @tensorlistWhileBody(%[[ARG0:.*]]: tensor<i32>, %[[ARG:.*]]: tensor<2x3xf32>) -> (tensor<i32>, tensor<2x3xf32>)
// CHECK-NOT: tensor<!tf_type.variant>

	HandSize int32 `json:"handSize" protobuf:"varint,2,opt,name=handSize"`

	// `queueLengthLimit` is the maximum number of requests allowed to
	// be waiting in a given queue of this priority level at a time;
	// excess requests are rejected.  This value must be positive.  If
	// not specified, it will be defaulted to 50.
	// +optional
	QueueLengthLimit int32 `json:"queueLengthLimit" protobuf:"varint,3,opt,name=queueLengthLimit"`
}

	HandSize int32 `json:"handSize" protobuf:"varint,2,opt,name=handSize"`

	// `queueLengthLimit` is the maximum number of requests allowed to
	// be waiting in a given queue of this priority level at a time;
	// excess requests are rejected.  This value must be positive.  If
	// not specified, it will be defaulted to 50.
	// +optional
	QueueLengthLimit int32 `json:"queueLengthLimit" protobuf:"varint,3,opt,name=queueLengthLimit"`
}