*/
abstract class Dispatcher {

  /**
   * Returns a dispatcher that queues events that are posted reentrantly on a thread that is already
   * dispatching an event, guaranteeing that all events posted on a single thread are dispatched to
   * all subscribers in the order they are posted.
   *
   * <p>When all subscribers are dispatched to using a <i>direct</i> executor (which dispatches on

    write(out, data, 0, 100, true);
    File file = out.getFile();
    assertEquals(100, file.length());
    assertTrue(file.exists());
    out.close();

    // Make sure that finalize deletes the file
    out = null;

    // times out and throws RuntimeException on failure
    GcFinalization.awaitDone(
        new GcFinalization.FinalizationPredicate() {
          @Override

- Google Play Services version
  (`Settings` > `Apps` > `Google Play Services` > `App details`):

**Standalone code to reproduce the issue**
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to or attach code demonstrating
the problem.

**Any other info / logs**
Include any logs or source code that would be helpful to diagnose the problem.

}

// checkPathLength - returns error if given path name length more than 255
func checkPathLength(pathName string) error {
	// Apple OS X path length is limited to 1016
	if runtime.GOOS == "darwin" && len(pathName) > 1016 {
		return errFileNameTooLong
	}

	// Disallow more than 1024 characters on windows, there
	// are no known name_max limits on Windows.
	if runtime.GOOS == "windows" && len(pathName) > 1024 {

	metacacheBlockSize = 5000

	// metacacheSharePrefix controls whether prefixes on dirty paths are always shared.
	// This will make `test/a` and `test/b` share listings if they are concurrent.
	// Enabling this will make cache sharing more likely and cause less IO,
	// but may cause additional latency to some calls.
	metacacheSharePrefix = false
)

from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader

# Make sure code inside the TensorFlow codebase can use tf2.enabled() at import.
_os.environ["TF2_BEHAVIOR"] = "1"
from tensorflow.python import tf2 as _tf2
_tf2.enable()

# API IMPORTS PLACEHOLDER

# WRAPPER_PLACEHOLDER

# Make sure directory containing top level submodules is in

   */
  private static long timeoutSeconds() {
    // This class can make no hard guarantees.  The methods in this class are inherently flaky, but
    // we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time
    // bound.  But these ideas are harder to implement.  We do not try to detect or handle a

		for i := len(orderBy.Columns) - 1; i >= 0; i-- {
			if orderBy.Columns[i].Reorder {
				orderBy.Columns = orderBy.Columns[i:]
				clause.Expression = orderBy
				return
			}
		}

		copiedColumns := make([]OrderByColumn, len(v.Columns))
		copy(copiedColumns, v.Columns)
		orderBy.Columns = append(copiedColumns, orderBy.Columns...)
	}

	clause.Expression = orderBy

Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to Colab/Jupyter/any notebook.

Also, please include a link to a GraphDef or the model if possible.

**Any other info / logs**

Include any logs or source code that would be helpful to diagnose the problem.
If including tracebacks, please include the full traceback. Large logs and files

# Sourcing this enables local disk cache
if [[ $(uname -s) == "Darwin" ]]; then
  echo "Please note that using disk cache on macOS is not recommended because the"
  echo "cache can end up being pretty big and make the build process inefficient."
fi