return VariantBinaryAddFunc(
        cc_ctx, cc_a.scalar<Variant>()(), cc_b.scalar<Variant>()(),
        cc_out->scalar<Variant>().data(), binary_add_func);
  } else {
    binary_add_func(ctx, a, b, out);
    return cc_ctx->status();
  }
}

static Status VariantBinaryAddFunc(
    ::tensorflow::OpKernelContext* cc_ctx, const Variant& a, const Variant& b,
    Variant* out,

           metadata = ""} : (tensor<*x!tf_type.variant>) -> tensor<!tf_type.variant>
  %5 = "tf.BatchDatasetV2"(%4, %0, %1) {device = "",
           output_shapes = [#tf_type.shape<>],
           output_types = [i32],
           parallel_copy = false,
           metadata = ""} : (tensor<!tf_type.variant>, tensor<i64>, tensor<i1>) -> tensor<!tf_type.variant>
  func.return %5 : tensor<!tf_type.variant>
}

		pc := &meshconfig.ProxyConfig{}
		if err := protomarshal.ApplyYAML(v, pc); err == nil {
			if pc.GetImage().GetImageType() != "" {
				variant = pc.GetImage().GetImageType()
			}
		}
	}
	if variant == "default" {
		variant = ""
	}
	return variant
}

func NewEffectiveProxyConfigResolver(c analysis.Context) *EffectiveProxyConfigResolver {
	mc := &meshconfig.MeshConfig{}
	rootNamespace := ""

		} else {
			return false
		}
	case objabi.R_PCREL, objabi.R_PCRELDBL, objabi.R_CALL:
		elfrel := elf.R_390_NONE
		rVariant := ldr.RelocVariant(s, ri)
		isdbl := rVariant&sym.RV_TYPE_MASK == sym.RV_390_DBL
		// TODO(mundaym): all DBL style relocations should be
		// signalled using the variant - see issue 14218.
		switch r.Type {
		case objabi.R_PCRELDBL, objabi.R_CALL:
			isdbl = true
		}

        defaultBuildComponentIdentifier.libraryName == 'myLib'
        defaultBuildComponentIdentifier.variant == 'api'
        defaultBuildComponentIdentifier.displayName == /project ':myPath' library 'myLib' variant 'api'/
        defaultBuildComponentIdentifier.toString() == /project ':myPath' library 'myLib' variant 'api'/
    }

    def "is instantiated with null project constructor parameter value"() {
        when:

    %2 = "tf.Identity"(%1) : (tensor<!tf_type.variant<tensor<f32>>>) -> (tensor<!tf_type.variant<tensor<f32>>>)
    "tf.Identity"(%2) : (tensor<!tf_type.variant<tensor<f32>>>) -> (tensor<!tf_type.variant<tensor<f32>>>)
    tf_device.return
  }) {cluster_attr = "cluster_attr"} : () -> ()
  func.return
}

  %outputs_60 =  "tf.Identity"(%outputs_58) {device = ""} : (tensor<*x!tf_type.variant>) -> tensor<*x!tf_type.variant>
  return %outputs_34, %outputs_36, %outputs_44, %outputs_60, %arg4, %arg5 : tensor<*xi32>, tensor<*xi32>, tensor<*xi32>, tensor<*x!tf_type.variant>, tensor<!tf_type.variant>, tensor<?xf32>
}

        then:
        javaLibrary.parsedModuleMetadata.variant("apiElements") {
            noMoreDependencies()
        }
        javaLibrary.parsedModuleMetadata.variant("runtimeElements") {
            noMoreDependencies()
        }
        javaLibrary.parsedModuleMetadata.variant("featureApiElements") {
            noMoreDependencies()
        }
        javaLibrary.parsedModuleMetadata.variant("featureRuntimeElements") {

     * </p>
     *
     * @param variant the variant to find the dependencies for
     * @throws IllegalStateException if the variant is not a selected variant of this component
     * @since 5.6
     */
    List<DependencyResult> getDependenciesForVariant(ResolvedVariantResult variant);

  } : (tensor<!tf_type.variant>) -> tensor<!tf_type.variant>

  func.return %0 : tensor<!tf_type.variant>
// CHECK: "tf.MapDataset"(