TF_Output cond_output;

  // The loop body graph. The inputs are the current values of the loop
  // variables. The outputs are the updated values of the loop variables.
  TF_Graph* const body_graph;
  const TF_Output* const body_inputs;
  TF_Output* const body_outputs;

  // Unique null-terminated name for this while loop. This is used as a prefix
  // for created operations.
  const char* name;
} TF_WhileParams;

  // Inputs to the while loop and the function as a whole
  TF_Operation* feed1 = Placeholder(func_graph_, s_, "feed1");
  TF_Operation* feed2 = Placeholder(func_graph_, s_, "feed2");

  // Outputs of the while loop corresponding to the two inputs above
  // The first one will the function's output
  std::vector<TF_Output> outputs;

  // Add while loop to func_graph_
  {
    // The inputs to the while loop

		}

		written, err := erasure.Decode(ctx, writer, readers, partOffset, partLength, partSize, prefer)
		// Note: we should not be defer'ing the following closeBitrotReaders() call as
		// we are inside a for loop i.e if we use defer, we would accumulate a lot of open files by the time
		// we return from this function.
		closeBitrotReaders(readers)
		if err != nil {
			// If we have successfully written all the content that was asked

labels.homePhone=Home Phone
labels.user_homePostalAddress=Home Postal Address
labels.homePostalAddress=Home Postal Address
labels.user_labeledURI=labeledURI
labels.labeledURI=labeledURI
labels.user_roomNumber=Room Number
labels.roomNumber=Room Number
labels.user_description=Description
labels.description=Description
labels.user_title=Title
labels.title=Title
labels.user_pager=Pager
labels.pager=Pager
labels.user_street=Street

        cliRequest.topDirectory = topDirectory;
        // We're very early in the process, and we don't have the container set up yet,
        // so we rely on the JDK services to eventually look up a custom RootLocator.
        // This is used to compute {@code session.rootDirectory} but all {@code project.rootDirectory}
        // properties will be computed through the RootLocator found in the container.

    peer.acceptFrame() // SYN_STREAM
    peer.sendFrame().headers(false, 3, headerEntries("headers", "bam"))
    peer.acceptFrame() // PING
    peer.sendFrame().headers(true, 3, headerEntries("trailers", "boom"))
    peer.sendFrame().ping(true, Http2Connection.AWAIT_PING, 0) // PONG
    peer.play()

    // Play it back.
    val connection = connect(peer)

   *       RuntimeException} ({@code get} implementations are discouraged from throwing such
   *       exceptions).
   * </ul>
   *
   * <p>The overall principle is to eliminate all checked exceptions: to loop to avoid {@code
   * InterruptedException}, to pass through {@code CancellationException}, and to wrap any exception
   * from the underlying computation in an {@code UncheckedExecutionException} or {@code
   * ExecutionError}.

		zw.CreateHeader(&FileHeader{
			Name:   name,
			Method: Store,
		})
	}

	if err := zw.Close(); err != nil {
		b.Fatal(err)
	}
	data := buf.Bytes()

	for b.Loop() {
		zr, err := NewReader(bytes.NewReader(data), int64(len(data)))
		if err != nil {
			b.Fatal(err)
		}
		zr.Open("does-not-exist")
	}
}

func BenchmarkReaderManyDeepDirs(b *testing.B) {

# WARNING: THESE OPTIONS WONT WORK IF YOU DO NOT HAVE PROPER AUTHENTICATION AND PERMISSIONS

# Use --config=tf_public_cache to try and use the TensorFlow public build cache
# to build TensorFlow. Look at ci/official/envs to find which types of jobs
# push to the cache.  For macOS, use --config=tf_public_macos_cache

labels.homePhone=Home Phone
labels.user_homePostalAddress=Home Postal Address
labels.homePostalAddress=Home Postal Address
labels.user_labeledURI=labeledURI
labels.labeledURI=labeledURI
labels.user_roomNumber=Room Number
labels.roomNumber=Room Number
labels.user_description=Description
labels.description=Description
labels.user_title=Title
labels.title=Title
labels.user_pager=Pager
labels.pager=Pager
labels.user_street=Street