"/job:localhost/replica:0/task:0/device:CPU:0"}, %arg3: tensor<!tf_type.variant> {tf.device = "/job:localhost/replica:0/task:0/device:CPU:0"}, %arg4: tensor<!tf_type.resource<tensor<7x7x3x64xf32>>> {tf.device = "/job:localhost/replica:0/task:0/device:TPU:0"}, %arg5: tensor<!tf_type.resource<tensor<f32>>> {tf.device = "/job:localhost/replica:0/task:0/device:TPU:0"}, %arg6: tensor<!tf_type.resource<tensor<f32>>> {tf.device = "/job:localhost/replica:0/task:0/device:TPU:0"}, %arg7: tensor<!tf_type.resource<tensor<i64>>>...

                    // enable re-resolution
                    org.eclipse.aether.artifact.Artifact art = dep.getArtifact();
                    art = art.setFile(null).setVersion(art.getBaseVersion());
                    dep = dep.setArtifact(art);
                }
                collect.addDependency(dep);
            }
        }

  return  %outputs_6, %outputs_12, %outputs_18, %arg3, %arg4, %arg5, %arg6 : tensor<i32>, tensor<i32>, tensor<!tf_type.variant<tensor<*xf32>>>, tensor<i32>, tensor<!tf_type.resource<tensor<3x1xf32>>>, tensor<?x3xf32>, tensor<?x4xf32>
}

// CHECK-LABEL: @"map/while_body/MapFnBody"

    %arg4: tensor<!tf_type.resource<tensor<?xi32>>>,
    %arg5: tensor<!tf_type.resource<tensor<?xi32>>>) -> tensor<?xi32> {
    %3:2 = tf_device.replicate(
      [%arg0, %arg1] as %ri_0: tensor<!tf_type.resource<tensor<?xi32>>>,
      [%arg2, %arg3] as %ri_1: tensor<!tf_type.resource<tensor<?xi32>>>,
      [%arg4, %arg5] as %ri_2: tensor<!tf_type.resource<tensor<?xi32>>>) {_mirrored_variable_indices = [0, 2], n = 2 : i32} {

        when:
        ModuleComponentArtifactMetadata result = serialize(identifier, serializer)

        then:
        result.id.componentIdentifier.group == 'group'
        result.id.componentIdentifier.module == 'module'
        result.id.componentIdentifier.version == 'version'
        result.name.name == "art-name"
        result.name.type == "type"

}

// CHECK-LABEL: func.func private @"map/while_body/TfMlrtAsyncWhileBody"(%arg0: !mlrt.promise, %arg1: !mlrt.future, %arg2: !mlrt.promise, %arg3: !mlrt.future, %arg4: !mlrt.promise, %arg5: tensor<i32>, %arg6: tensor<?x!tf_type.resource>, %arg7: tensor<*xf32>) {
// CHECK-NEXT:    %cst = "tf.Const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>

        def componentId = DefaultModuleComponentIdentifier.newId(id)

        def artifacts = [new PublishArtifactLocalArtifactMetadata(componentId, new DefaultPublishArtifact("art1", "zip", "art", null, new Date(), new File("art1.zip")))]
        def defaultVariant = createConfigurationMetadata("default", componentId, [], artifacts)

        when:
        ModuleComponentArtifactIdentifier result = serialize(identifier, serializer)

        then:
        result.componentIdentifier.group == 'group'
        result.componentIdentifier.module == 'module'
        result.componentIdentifier.version == 'version'
        result.name.name == "art-name"
        result.name.type == "type"

  %0 = "tf.Const"() {_output_shapes = ["tfshape$"], device = "", dtype = f32, value = dense<0.000000e+00> : tensor<f32>} : () -> tensor<f32>

                            confs += it
                        }
                    }
                    def attrs = [name: art.name, type: art.type, ext: art.ext, conf: confs.join(',')]
                    if (art.classifier) {
                        attrs["m:classifier"] = art.classifier
                    }
                    builder.artifact(attrs)
                }
            }
        }