assertEquals(1, unresolved.size());
        assertEquals(8, classes.size()); // "plexus.pom" and "junit.jar" are excluded.
        assertEquals(1, modules.size());
        assertEquals("plexus-1.0.11.pom", unresolved.get(0).getFileName().toString());
        assertEquals("test-extension-1.jar", classes.get(0).getFileName().toString());
        assertEquals("junit-4.13.1.jar", modules.get(0).getFileName().toString());

    return %1#0, %1#1 : tensor<1x500x4x4xf32>, tensor<1x500x4x4xf32>
  }

        and:
        failure.assertHasDescription "Value '$value' given for org.gradle.debug.port Gradle property is invalid (must be a number between 1 and 65535)"

        where:
        value << ["-1", "0", "1.1", "foo", " 1", "65536"]
    }

    @Flaky(because = "Sometimes it hangs for hours")
    @Issue('https://github.com/gradle/gradle/issues/18084')
    @Requires(IntegTestPreconditions.NotEmbeddedExecutor)

	EIBMBADCALL        = Errno(1000)
	EIBMBADPARM        = Errno(1001)
	EIBMSOCKOUTOFRANGE = Errno(1002)
	EIBMSOCKINUSE      = Errno(1003)
	EIBMIUCVERR        = Errno(1004)
	EOFFLOADboxERROR   = Errno(1005)
	EOFFLOADboxRESTART = Errno(1006)
	EOFFLOADboxDOWN    = Errno(1007)
	EIBMCONFLICT       = Errno(1008)
	EIBMCANCELLED      = Errno(1009)
	EIBMBADTCPNAME     = Errno(1011)
	ENOTBLK            = Errno(1100)

    %15 = stablehlo.convolution(%13, %14) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {pad = [[1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<1x3x3x4xf32>, tensor<3x3x4x4xf32>) -> tensor<1x3x3x4xf32>
    %16 = stablehlo.subtract %10, %15 : tensor<1x3x3x4xf32>
    %17 = stablehlo.broadcast_in_dim %4, dims = [0, 1, 2, 3] : (tensor<1x1x1x4xf32>) -> tensor<1x3x3x4xf32>

    // CHECK-SAME: (tensor<*xi32>, tensor<*xf32>, tensor<i32>)
    %1:3 = func.call @WhileOp_body(%arg0, %arg1, %cst) : (tensor<*xi32>, tensor<*xf32>, tensor<i32>) -> (tensor<*xi32>, tensor<*xf32>, tensor<i32>)
    "tfl.yield"(%1#0, %1#1) : (tensor<*xi32>, tensor<*xf32>) -> ()
  }) : (tensor<i32>, tensor<1xf32>) -> (tensor<i32>, tensor<1xf32>) loc("WhileOp")
  // CHECK: (tensor<i32>, tensor<1xf32>, tensor<i32>) ->

{!../../../docs_src/bigger_applications/app/main.py!}
```

### 🔌 `APIRouter`Ⓜ `users` & `items`

🔜, ➡️ 🔌 `router`Ⓜ ⚪️➡️ 🔁 `users` & `items`:

```Python hl_lines="10-11" title="app/main.py"
{!../../../docs_src/bigger_applications/app/main.py!}
```

!!! info
    `users.router` 🔌 `APIRouter` 🔘 📁 `app/routers/users.py`.

{!../../../docs_src/bigger_applications/app/main.py!}
```

### Include the `APIRouter`s for `users` and `items`

Now, let's include the `router`s from the submodules `users` and `items`:

```Python hl_lines="10-11" title="app/main.py"
{!../../../docs_src/bigger_applications/app/main.py!}
```

!!! info
    `users.router` contains the `APIRouter` inside of the file `app/routers/users.py`.

  %0:2 = "tf_device.cluster"() ({
    // CHECK: tf.ApproxTopK
    // CHECK-NOT: _xla_outside_compilation
    %1:2 = "tf.ApproxTopK"(%arg0) {k = 2} : (tensor<16xf32>) -> (tensor<?xf32>, tensor<?xi32>)
    tf_device.return %1#0, %1#1 : tensor<?xf32>, tensor<?xi32>
  }) {allow_soft_placement = true, num_cores_per_replica = 1, topology =  "", device_assignment =  []} : () -> (tensor<?xf32>, tensor<?xi32>)
  func.return %0#0, %0#1 : tensor<?xf32>, tensor<?xi32>
}

  func.return %1#0, %1#1: tensor<3x4x2xf32>, tensor<3x4x2xi32>
}

// -----

// CHECK-LABEL: topk_d
func.func @topk_d(%arg0: tensor<?x8xf32>) -> (tensor<?x2xf32>, tensor<?x2xi32>) {
  %0 = arith.constant dense<2> : tensor<i32>
  %1:2 = "tfl.topk_v2"(%arg0, %0) : (tensor<?x8xf32>, tensor<i32>) -> (tensor<?x2xf32>, tensor<?x2xi32>)
  func.return %1#0, %1#1: tensor<?x2xf32>, tensor<?x2xi32>
}