// objectKeyed = transformEntries(map6, transformer);
    // objectKeyed = transformEntries(map8, transformer);
    // objectKeyed = transformEntries(map9, transformer);
    // numberKeyed = transformEntries(map8, transformer);
    // numberKeyed = transformEntries(map9, transformer);

    // Can't loosen the value type:
    // Map<Number, Number> looseValued1 = transformEntries(map5, transformer);

    /**
     * Copies this state, but with the new component ID and the artifacts transformed by the given transformer.
     */
    LocalComponentGraphResolveState copy(ComponentIdentifier newComponentId, Transformer<LocalComponentArtifactMetadata, LocalComponentArtifactMetadata> transformer);

    /**
     * We currently allow a configuration that has been partially observed for resolution to be modified

When a user runs a Gradle build Gradle it uses transformed plugin jars. 
The whole transformation process normally happens on the first use of a build or when a plugin jar is added to the build script classpath.
We transform the jar and cache transformed jars for future use.

We transform plugins classpath, TestKit classpath and buildscript classes separately. 

                }
            }

            configurations {
                transformed
            }

            def intermediateFiles = configurations.implementation.incoming.artifactView {
                attributes.attribute(color, 'green')
            }.files

            dependencies {
                transformed files(intermediateFiles)
            }

   * that the transformer is capable of accepting null inputs. The transformed multimap might
   * contain null values if the transformer sometimes gives a null result.
   *
   * <p>The returned multimap is not thread-safe or serializable, even if the underlying multimap
   * is.
   *
   * <p>The transformer is applied lazily, invoked when needed. This is necessary for the returned

     return %arg0
    }
    func @while_cond(%arg0: tensor<*x!tf_type.resource<tensor<f32>>>) {
      %read = "tf.ReadVariableOp"(%arg0)
      return %read
    }
    ```

    will be transformed to:

    ```mlir
    func @cluster_with_loop() {
      %0 = "tf.VarHandleOp"() ...
      %1 = "tf.ReadVariableOp"(%0)
      %2 = "tf_device.cluster"() ( {

   * the transformer is capable of accepting null inputs. The transformed map might contain null
   * values if the transformer sometimes gives a null result.
   *
   * <p>The returned map is not thread-safe or serializable, even if the underlying map is.
   *
   * <p>The transformer is applied lazily, invoked when needed. This is necessary for the returned

   * the transformer is capable of accepting null inputs. The transformed map might contain null
   * values if the transformer sometimes gives a null result.
   *
   * <p>The returned map is not thread-safe or serializable, even if the underlying map is.
   *
   * <p>The transformer is applied lazily, invoked when needed. This is necessary for the returned

      // Uniform Quantized op requires weights of tf.DepthwiseConv2dNative to
      // be transformed from [H,W,C,M] to [H,W,1,CxM] where
      // H=height,W=width,C=channel,M=multiplier. Therefore, a reshape op is
      // inserted between the constant op and the function op so that the
      // constant is safely transformed for the multi-use cases as well. Note

import org.eclipse.aether.metadata.Metadata;
import org.eclipse.aether.util.ConfigUtils;

/**
 * Maven local GAV level metadata generator.
 * <p>
 * Local snapshot metadata contains non-transformed snapshot version.
 */
class LocalSnapshotMetadataGenerator implements MetadataGenerator {

    private final Map<Object, LocalSnapshotMetadata> snapshots;

    private final Date timestamp;