* com.google.guava:listenablefuture:1.0 artifact. (For more on that artifact, see
 * https://github.com/google/guava/releases/tag/v27.0) This means that the copy of ListenableFuture
 * in com.google.guava:guava differs from the "frozen" copy in the listenablefuture artifact. This
 * could in principle cause problems for some users. Still, we expect that the benefits of the

 * com.google.guava:listenablefuture:1.0 artifact. (For more on that artifact, see
 * https://github.com/google/guava/releases/tag/v27.0) This means that the copy of ListenableFuture
 * in com.google.guava:guava differs from the "frozen" copy in the listenablefuture artifact. This
 * could in principle cause problems for some users. Still, we expect that the benefits of the

 * com.google.guava:listenablefuture:1.0 artifact. (For more on that artifact, see
 * https://github.com/google/guava/releases/tag/v27.0) This means that the copy of ListenableFuture
 * in com.google.guava:guava differs from the "frozen" copy in the listenablefuture artifact. This
 * could in principle cause problems for some users. Still, we expect that the benefits of the

// Supports following actions:
// - restart (restarts all the MinIO instances in a setup)
// - stop (stops all the MinIO instances in a setup)
// - freeze (freezes all incoming S3 API calls)
// - unfreeze (unfreezes previously frozen S3 API calls)
func (a adminAPIHandlers) ServiceHandler(w http.ResponseWriter, r *http.Request) {
	ctx := r.Context()

	vars := mux.Vars(r)
	action := vars["action"]

	var serviceSig serviceSignal

	}
	return sys.collectPeerMetrics(ctx, peerChannels, g)
}

// ServiceFreeze freezes all S3 API calls when 'freeze' is true,
// 'freeze' is 'false' would resume all S3 API calls again.
// NOTE: once a tenant is frozen either two things needs to
// happen before resuming normal operations.
//   - Server needs to be restarted 'mc admin service restart'
//   - 'freeze' should be set to 'false' for this call

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    to the layer came from a keras input.
*   Clean up `BatchNormalization` layer's `trainable` property to act like
    standard python state when it's used inside `tf.functions` (frozen at
    tracing time), instead of acting like a pseudo-variable whose updates *kind
    of sometimes* get reflected in already-traced `tf.function` traces.
*   Add the `Conv1DTranspose` layer.

  }

  public void testBroken() {
    Iterator<Object> broken = new BrokenAbstractSequentialIterator();
    assertTrue(broken.hasNext());
    // We can't retrieve even the known first element:
    assertThrows(SomeUncheckedException.class, broken::next);
    assertThrows(SomeUncheckedException.class, broken::next);
  }

  private static Iterator<Integer> newDoubler(int first, int last) {

     *
     * @param dc the domain controller address
     * @param tc the CIFS context containing credentials
     * @throws CIFSException if an error occurs during authentication
     * @deprecated functionality is broken and will be removed at some point,
     *             use actual Active Directory authentication instead
     */
    @Deprecated
    void logon(CIFSContext tc, Address dc) throws CIFSException;

    /**

## Ports {#ports}

### Windows

<!-- go.dev/issue/71671 -->