def "uses artifacts defined by dependency descriptor"() {
        def artifact1 = new Artifact(new DefaultIvyArtifactName("art1", "type", "ext"), ["config"] as Set)
        def artifact2 = new Artifact(new DefaultIvyArtifactName("art2", "type", "ext"), ["other"] as Set)
        def artifact3 = new Artifact(new DefaultIvyArtifactName("art3", "type", "ext"), ["super"] as Set)

        given:

// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

package art

import (
	_ "embed"

	"github.com/fatih/color"
)

//go:embed istio-ascii.txt
var istioASCIIArt string

func IstioArt() string {
	return istioASCIIArt
}

func IstioColoredArt() string {

                    resolvedArtifacts.map { arts ->
                        arts.collect { art ->
                            objects.newInstance(ResolvedArtifactBean).tap { bean ->
                                bean.file = art.file
                                bean.id = art.id
                                bean.type = art.type
                                bean.variant = art.variant
                            }

    %0 = stablehlo.constant dense<500> : tensor<100xi64>
    %1 = stablehlo.constant dense<0> : tensor<100xi64>
    %2 = stablehlo.compare  LT, %arg2, %1 : (tensor<100xi64>, tensor<100xi64>) -> tensor<100xi1>
    %3 = stablehlo.add %arg2, %0 : tensor<100xi64>

  // CHECK: "tfl.conv_2d"(%arg0, %arg1, %arg2) <{dilation_h_factor = 2 : i32, dilation_w_factor = 2 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 1 : i32, stride_w = 1 : i32}> : (tensor<1x112x80x128xf32>, tensor<128x3x3x128xf32>, tensor<128xf32>) -> tensor<1x108x76x128xf32>

  %0:2 = "tfl.while"(%cst0, %cst1) ({
    ^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
      %cst_0 = arith.constant dense<0> : tensor<i32>
      %1 = "tfl.greater"(%arg2, %cst_0) : (tensor<*xi32>, tensor<i32>) -> tensor<i1>
      "tfl.yield"(%1) : (tensor<i1>) -> ()
  },  {
    ^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
      %1 = "tfl.sub"(%arg2, %arg0) {fused_activation_function = "NONE"} :

        log(logLevel, throwable, format, new Object[]{arg});
    }

    private void log(LogLevel logLevel, Throwable throwable, String format, Object arg1, Object arg2) {
        log(logLevel, throwable, format, new Object[]{arg1, arg2});
    }

    private void log(LogLevel logLevel, Throwable throwable, String format, Object[] args) {
        FormattingTuple tuple = MessageFormatter.arrayFormat(format, args);

  %0 = "tfl.slice"(%arg0, %arg1, %arg2) : (tensor<4x384x32xf32>, tensor<3xi32>, tensor<3xi32>) -> tensor<1x384x32xf32>
  func.return %0 : tensor<1x384x32xf32>
}

// PARTIAL-LABEL: @arg_reuse_test_2

  %0:1 = "tfl.while"(%arg0, %arg1) ({
  ^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
    %1 = func.call @WhileOp_cond(%arg2, %arg3) : (tensor<*xi32>, tensor<*xf32>) -> tensor<i1>
    "tfl.yield"(%1) : (tensor<i1>) -> ()
  },  {
  ^bb0(%arg2: tensor<*xi32>, %arg3: tensor<*xf32>):
    %1:2 = func.call @WhileOp_body(%arg2, %arg3) : (tensor<*xi32>, tensor<*xf32>) -> (tensor<*xi32>, tensor<*xf32>)

}

// CHECK-LABEL: conv2d_backprop_input_with_add
func.func @conv2d_backprop_input_with_add(%arg0: tensor<4xi32>, %arg1: tensor<3x3x1x32xf32>, %arg2: tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32> {
  %0 = "tf.Conv2DBackpropInput"(%arg0, %arg1, %arg2) {strides = [1, 2, 2, 1], padding="SAME", dilations=[1, 1, 1, 1]}: (tensor<4xi32>, tensor<3x3x1x32xf32>, tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32>