then:
        outputContains("files: [test-lib.jar, transformed-a1.jar, transformed-b2.jar, test-1.0.jar]")
        outputContains("components: [test-lib.jar, project :lib, project :ui, org:test:1.0]")
        outputContains("variants: [{artifactType=jar}, {artifactType=jar, buildType=debug, flavor=one, usage=transformed}, {artifactType=jar, usage=transformed}, {artifactType=jar, org.gradle.status=integration}]")
    }

dialect to their region-based counterparts, i.e., `tf.If` is transformed to
`tf.IfRegion` and `tf.While` is transformed to `tf.WhileRegion`.

For example, this functional operation

```mlir
  %0 = "tf.If"(%arg0, %arg1) {
    then_branch = @then_branch_func, else_branch = @else_branch_func, is_stateless = false
  } : (tensor<i1>, tensor<*xf32>) -> tensor<*xf32>
```

will be transformed into this region-based operation

```mlir

        super.writeRealisedConfigurationsData(encoder, transformed, deduplicationDependencyCache);
        if (transformed instanceof RealisedMavenModuleResolveMetadata) {
            writeDerivedVariants(encoder, (RealisedMavenModuleResolveMetadata) transformed, deduplicationDependencyCache);
        }
    }

  let description = [{
    This pass transforms functional control flow operations in the TensorFlow
    dialect to their region-based counterparts, i.e., `tf.If` is transformed to
    `tf.IfRegion` and `tf.While` is transformed to `tf.WhileRegion`.

    For example, this functional operation

    ```mlir
      %0 = "tf.If"(%arg0, %arg1) {

 */

package org.gradle.model.dsl.internal.transform;

import org.gradle.model.dsl.internal.inputs.PotentialInputs;

import javax.annotation.Nullable;

/**
 * Implemented by transformed rules closure.
 */
public interface TransformedClosure {
    /**
     * Returns the input references for this closure.
     */
    InputReferences inputReferences();

    /**

 * limitations under the License.
 */

package org.gradle.api.internal.artifacts.transform;

/**
 * Companion type to {@link TransformStepNode} that knows how to compute extra dependent nodes aside from the to be transformed artifact.
 * Instances of this type should not be shared beyond a single transform chain.
 *
 * @see TransformUpstreamDependenciesResolverFactory
 */
public interface TransformUpstreamDependenciesResolver {
    /**

import org.gradle.api.artifacts.component.ModuleComponentSelector;

/**
 * Represents dependency information as stored in an external descriptor file (POM or IVY.XML).
 * This information is able to be transformed into a `ModuleDependencyMetadata` instance.
 */
public abstract class ExternalDependencyDescriptor {

    public abstract ModuleComponentSelector getSelector();

    public abstract boolean isOptional();

     *
     * @param problem the problem to transform
     * @param id the operation id associated with the problem
     * @return the transformed problem
     */
    Problem transform(Problem problem, OperationIdentifier id);

import org.gradle.internal.model.CalculatedValueContainer;
import org.gradle.internal.model.CalculatedValueContainerFactory;

/**
 * An artifact set containing transformed external artifacts.
 */
public class TransformedExternalArtifactSet extends AbstractTransformedArtifactSet {
    public TransformedExternalArtifactSet(
        ComponentIdentifier componentIdentifier,

      %replicated_output = "tf.TPUReplicatedOutput(%identity) : (tensor<i32>) -> tensor<i32>
      return %replicated_output : tensor<i32>
    }
    ```

    will be transformed into:

    ```mlir
    func @tpu_computation(%arg0: tensor<i32>) -> tensor<i32> {
      %cluster = "tf_device.cluster"() ( {
        %identity = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<i32>