TFE_TensorHandle* h1_task0 = TestMatrixTensorHandle(ctx);
  std::vector<TFE_TensorHandle*> handles_task0;
  if (heavy_load_on_streaming_rpc) {
    // Send 50 tensor copy requests to simulate that there have been some RPC
    // requests been enqueued.
    for (int i = 0; i < 50; ++i) {
      handles_task0.push_back(TestMatrixTensorHandle(ctx));
    }
  }
  const char task1_name[] = "/job:localhost/replica:0/task:1/device:CPU:0";

# the Python version set in "TFCI_PYTHON_VERSION" and use it as default.
# We enable this in the nightly and release builds because before uploading the
# wheels, we install them in a virtual environment and run some smoke tests on
# it. TFCI Mac VMs only have one Python version installed so we need to install
# the other versions manually.
if [[ "${TFCI_MACOS_PYENV_INSTALL_ENABLE}" == 1 ]]; then

import javax.annotation.CheckForNull;
import org.checkerframework.checker.nullness.qual.Nullable;

/**
 * A step in a pipeline of an asynchronous computation. When the last step in the computation is
 * complete, some objects captured during the computation are closed.
 *
 * <p>A pipeline of {@code ClosingFuture}s is a tree of steps. Each step represents either an

	object := ""
	uploadID := ""
	if len(params) >= 1 {
		bucket = params[0]
	}
	if len(params) == 2 {
		object = params[1]
	}
	if len(params) == 3 {
		uploadID = params[2]
	}

	// in some cases just a plain error is being returned
	switch err.Error() {
	case "storage: bucket doesn't exist":
		err = BucketNotFound{
			Bucket: bucket,
		}
		return err
	case "storage: object doesn't exist":

## Attribution

    // 256 characters long
    assertEquals(4904844928629814570L, fingerprint(Strings.repeat("test", 64).getBytes(UTF_8)));
  }

  public void testStringsConsistency() {
    for (String s : Arrays.asList("", "some", "test", "strings", "to", "try")) {
      assertEquals(HASH_FN.newHasher().putUnencodedChars(s).hash(), HASH_FN.hashUnencodedChars(s));
    }
  }

  public void testUtf8() {
    char[] charsA = new char[128];

 * responses. Although this client honors all [HTTP/1.1 (RFC 7234)][rfc_7234] cache headers, it
 * doesn't cache partial responses.
 *
 * ## Force a Network Response
 *
 * In some situations, such as after a user clicks a 'refresh' button, it may be necessary to skip
 * the cache, and fetch data directly from the server. To force a full refresh, add the `no-cache`
 * directive:
 *
 * ```java

   * "two"=2, "three"=3}, and {@code keySet()} and {@code values()} respect the same order. If you
   * want a different order, consider using {@link #orderEntriesByValue(Comparator)}, which changes
   * this builder to sort entries by value.
   *
   * <p>Builder instances can be reused - it is safe to call {@link #buildOrThrow} multiple times to
   * build multiple bimaps in series. Each bimap is a superset of the bimaps created before it.
   *

    if (seq.length() <= maxLength) {
      String string = seq.toString();
      if (string.length() <= maxLength) {
        return string;
      }
      // if the length of the toString() result was > maxLength for some reason, truncate that
      seq = string;
    }

    return new StringBuilder(maxLength)
        .append(seq, 0, truncationLength)
        .append(truncationIndicator)
        .toString();
  }

  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }
  std::sort(grads.begin(), grads.end());
  return grads;
}

std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def) {
  std::vector<string> names;
  auto functions = graph_def.library().function();