pos syntax.Pos
	typ Type
}

func (check *Checker) monomorph() {
	// We detect unbounded instantiation cycles using a variant of
	// Bellman-Ford's algorithm. Namely, instead of always running |V|
	// iterations, we run until we either reach a fixed point or we've
	// found a path of length |V|. This allows us to terminate earlier
	// when there are no cycles, which should be the common case.

	again := true
	for again {

        kube::log::usage "'$0': argument to -p must be numeric and greater than 0"
        kube::test::usage
        exit 1
      fi
      ;;
    i)
      kube::log::usage "'$0': use GOFLAGS='-count <num-iterations>'"
      kube::test::usage
      exit 1
      ;;
    :)
      kube::log::usage "Option -${OPTARG} <value>"
      kube::test::usage
      exit 1
      ;;
    ?)
      kube::test::usage

			c = 0
			ng = nng
		}
		if c >= 100 {
			// The same value 100 times in a row is good enough.
			return ng
		}
		runtime.Gosched()
	}
	panic("failed to stabilize NumGoroutine after 1000 iterations")
}

func TestPullDoubleNext(t *testing.T) {
	next, _ := Pull(doDoubleNext())
	nextSlot = next
	next()
	if nextSlot != nil {
		t.Fatal("double next did not fail")
	}
}

						break
					}
				}
				// Process generated changes
				continue
			}
		}
		evaluateTestResults(ctx, ctrl, reactor.VolumeReactor, test, t)
		logger.V(4).Info("Test finished after iterations", "testName", test.name, "iterations", counter)
	}

	for _, test := range tests {
		test := test
		t.Run(test.name, func(t *testing.T) {
			t.Parallel()
			run(t, test)
		})
	}
}

	MOVD y+48(FP), R4	// R4 = y = c
	MOVD z_len+8(FP), R11	// R11 = z_len

	CMP   R11, $0		// If z_len is zero, return
	BEQ   done

	// We will process the first iteration out of the loop so we capture
	// the value of c. In the subsequent iterations, we will rely on the
	// value of CA set here.
	MOVD  0(R8), R20	// R20 = x[i]
	ADD   $-1, R11		// R11 = z_len - 1
	ADDC  R20, R4, R6	// R6 = x[i] + c

# because it is willing to drop dependencies on non-root modules that do not
# otherwise provide imported packages.
#
# On the first iteration, it adds x.1 as a root, which upgrades z and w,
# dropping w.1's requirement on y. w.1 was initially a root, so the upgraded
# w.2-pre is retained as a root.
#
# On the second iteration, it adds y.1 as a root, which upgrades w and x,

    putEdge(N2, N1);
    assertThat(graph.outDegree(N1)).isEqualTo(3);
  }

  // Stable order tests

  // Note: Stable order means that the ordering doesn't change between iterations and versions.
  // Ideally, the ordering in test should never be updated.
  @Test
  public void stableIncidentEdgeOrder_edges_returnsInStableOrder() {

				},
			},
			errRegex: "",
		},
	}

	for _, tt := range tests {
		t.Run(tt.test, func(t *testing.T) {
			// Use a closure so defer statements trigger between loop iterations.
			err := func() error {
				kubeConfig := v1.Config{}

				if tt.cluster != nil {
					kubeConfig.Clusters = []v1.NamedCluster{*tt.cluster}
				}

				if tt.context != nil {

  }
};

// Test for resource leaks related to TensorFlow session closing requirements
// when loading and unloading large numbers of SavedModelBundles.
// TODO(sukritiramesh): Increase run iterations and move outside of the test
// suite.
TEST_F(LoaderTest, ResourceLeakTest) {
  SavedModelBundle bundle;
  SessionOptions session_options;
  RunOptions run_options;

  const string export_dir =

// true on iteration 0, 1, 2 respectively.  This is made more precise in the
// comment on the AndRecurrence class.
//
// The general algorithm that deals with cycles does two topological-order
// iterations over the graph.  On the first iteration it assigns a symbolic
// predicate to merge nodes with backedges.  On the second iteration it tries