baseVariant = immutableMetadata.getConfiguration('runtime')
        }

        then:
        variants.size() == initialVariantCount + 1
        variants.last().name == 'new-variant'
        variants.last().attributes == baseVariant.attributes
        variants.last().capabilities == baseVariant.capabilities

    }

    private static void assertAttributes(GradleModuleMetadata.Variant variant, Map<String, Object> expected) {
        assert variant.attributes.size() == expected.size()
        expected.each { attribute, value ->
            assert variant.attributes.containsKey(attribute)
            assert variant.attributes[attribute] == value
        }
    }

    void assertNoDependencies() {

  %1 = "tf.AddN"(%arg0, %arg1) : (tensor<!tf_type.variant<tensor<*xi32>>>, tensor<!tf_type.variant<tensor<*xi32>>>) -> tensor<!tf_type.variant<tensor<*xi32>>>

               - Variant javadoc provides com.google.code.gson:gson:2.8.5
               - Variant platform-compile provides com.google.code.gson:gson-derived-platform:2.8.5
               - Variant platform-runtime provides com.google.code.gson:gson-derived-platform:2.8.5
               - Variant runtime provides com.google.code.gson:gson:2.8.5
               - Variant sources provides com.google.code.gson:gson:2.8.5"""

            return getArtifactsForGraphVariant(variant);
        } else {
            return ImmutableSet.of(variant.prepareForArtifactResolution().resolveAdhocVariant(variantResolver, artifacts));
        }
    }

    /**
     * Gets all artifact variants that should be considered for artifact selection.
     *
     * <p>This emulates the normal variant selection process where graph variants are first

      f = @identity} : (tensor<!tf_type.variant<tensor<f32>>>) -> tensor<!tf_type.variant<tensor<f32>>>
  %2 = "tf.OptionalGetValue"(%1) : (tensor<!tf_type.variant<tensor<f32>>>) -> tensor<f32>
  %3 = "tf.OptionalNone"() : () -> tensor<!tf_type.variant<tensor<f32>>>
  return %2, %3 : tensor<f32>, tensor<!tf_type.variant<tensor<f32>>>
}

func.func private @identity(%arg0: tensor<!tf_type.variant<tensor<f32>>>) -> tensor<!tf_type.variant<tensor<f32>>> {

                def distinguishingValues = distinguisher == 'flavor' ? "\n  - Value: 'paid' selects variant: 'bar'\n  - Value: 'free' selects variant: 'foo'" : "\n  - Value: 'bar' selects variant: 'bar'\n  - Value: 'foo' selects variant: 'foo'"

    def "expressing a preference for a variant with capabilities declared in a published modules does not evict unrelated variants"() {
        given:
        repository {
            'org:testB:1.0' {
                variant('runtime') {
                    capability('org', 'testB', '1.0')
                }
                variant('runtimeAlt') {
                    capability('org', 'testB', '1.0')

        if (variants == null || variants.isEmpty() || !allArtifactSet.isEmpty()) {
            visitor.visitOwnVariant(displayName, attributes.asImmutable(), allArtifactSet);
        }
        if (variants != null) {
            for (ConfigurationVariantInternal variant : variants.withType(ConfigurationVariantInternal.class)) {

    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,