t.Errorf("Validate() failed: %s", err)
	}

	msg := []byte("test")
	enc, err := EncryptPKCS1v15(rand.Reader, &priv.PublicKey, msg)
	if err == ErrMessageTooLong {
		t.Log("key too small for EncryptPKCS1v15")
	} else if err != nil {
		t.Errorf("EncryptPKCS1v15: %v", err)
	}
	if err == nil {
		dec, err := DecryptPKCS1v15(nil, priv, enc)
		if err != nil {
			t.Errorf("DecryptPKCS1v15: %v", err)

				// picked over a node with a smaller number of pods with the same negative
				// priority (and similar scenarios).
				sumPriorities += int64(corev1helpers.PodPriority(pod)) + int64(math.MaxInt32+1)
			}
			// The smaller the sumPriorities, the higher the score.
			return -sumPriorities
		}
		minNumPodsScoreFunc := func(node string) int64 {
			// The smaller the length of pods, the higher the score.

    assertEquals(-1, read);

    lin.reset();
    byte[] small = new byte[5];
    read = lin.read(small);
    assertEquals(2, read);
    assertEquals(big[0], small[0]);
    assertEquals(big[1], small[1]);

    lin.reset();
    read = lin.read(small, 2, 3);
    assertEquals(2, read);
    assertEquals(big[0], small[2]);
    assertEquals(big[1], small[3]);
  }

  public void testLimit_mark() throws Exception {

        "@com_google_absl//absl/status",
        "@com_google_absl//absl/status:statusor",
        "@com_google_absl//absl/strings",
    ],
)

tf_cc_test(
    name = "metrics_test",
    size = "small",
    srcs = ["metrics_test.cc"],
    deps = [
        ":metrics",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",

        when:
        decode(bytes) { Decoder decoder ->
            decoder.readLong()
        }

        then:
        thrown(EOFException)
    }

    def "can encode and decode a small long"() {
        expect:
        def bytesA = encode { Encoder encoder ->
            encoder.writeSmallLong(a as long)
        }
        def bytesB = encode { Encoder encoder ->

        "//tensorflow/core/common_runtime:device_set",
        "@llvm-project//mlir:IR",
    ],
    alwayslink = 1,
)

tf_py_strict_test(
    name = "graph_decompose_test",
    size = "small",
    srcs = ["integration/graph_decompose_test.py"],
    data = ["//tensorflow/compiler/mlir/tfr/resources:decomposition_lib"],
    python_version = "PY3",
    srcs_version = "PY3",
    tags = [

   1. Definitions.

      "License" shall mean the terms and conditions for use, reproduction,
      and distribution as defined by Sections 1 through 9 of this document.

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all

// 01: package p
// 02:
// 03: var v, w, z int
// 04:
// 05: func small(x, y int) int {
// 06:   v++
// 07:   // comment
// 08:   if y == 0 {
// 09:     return x
// 10:   }
// 11:   return (x << 1) ^ (9 / y)
// 12: }
// 13:
// 14: func Medium(q, r int) int {
// 15:   s1 := small(q, r)
// 16:   z += s1
// 17:   s2 := small(r, q)
// 18:   w -= s2
// 19:   return w + z
// 20: }
//

  private enum TimeoutsToUse {
    ANY(Timeout.values()),
    PAST(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO),
    FUTURE(Timeout.SMALL, Timeout.MAX),
    SMALL(Timeout.SMALL),
    FINITE(Timeout.MIN, Timeout.MINUS_SMALL, Timeout.ZERO, Timeout.SMALL),
    INFINITE(Timeout.LARGE, Timeout.MAX);

    final ImmutableList<Timeout> timeouts;

    TimeoutsToUse(Timeout... timeouts) {

   1. Definitions.

      "License" shall mean the terms and conditions for use, reproduction,
      and distribution as defined by Sections 1 through 9 of this document.

      "Licensor" shall mean the copyright owner or entity authorized by
      the copyright owner that is granting the License.

      "Legal Entity" shall mean the union of the acting entity and all