// benchmarking shows it can take 7 times longer than the other two in some cases. The other two
    // do n swaps, minus a delta (0 or 2 for Reversal, gcd(d, n) for Successive), so that's about
    // twice as many reads and writes. But benchmarking shows that they usually perform better than
    // Dolphin. Reversal is about as good as Successive on average, and it is much simpler,

     * need to be on the same host. This operation does not copy extended
     * file attributes such as ACLs but it does copy regular attributes as
     * well as create and last write times. This method is almost twice as
     * efficient as manually copying as it employs an additional write
     * thread to read and write data concurrently.
     * <br>
     * It is not possible (nor meaningful) to copy entire workgroups or

        case WILL_CLOSE:
        case CLOSING:
        case CLOSED:
          throw new IllegalStateException("Cannot call finishToFuture() twice");

        case OPEN:
          throw new AssertionError();
      }
    }
    return future;
  }

  /**

calling <code>twoprint</code> will call <code>setup</code> exactly
once.
The <code>setup</code> function will complete before either call
of <code>print</code>.
The result will be that <code>"hello, world"</code> will be printed
twice.
</p>

<h3 id="atomic">Atomic Values</h3>

<p>
The APIs in the <a href="/pkg/sync/atomic/"><code>sync/atomic</code></a>
package are collectively “atomic operations”

			if !errors.Is(err, errErasureWriteQuorum) {
				t.Errorf("Expected putObject to fail with %v, but failed with %v", toObjectErr(errErasureWriteQuorum, bucket, object), err)
			}
		})
	}
}

// Test PutObject twice, one small and another bigger
// than small data threshold and checks reading them again
func TestPutObjectSmallInlineData(t *testing.T) {
	ctx, cancel := context.WithCancel(t.Context())
	defer cancel()

   *
   * <p>The current implementation uses the concurrency level to create a fixed number of hashtable
   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and
   * once after loading completes). Much internal cache management is performed at the segment

        verify(mockNdrBuffer).align(4);
        verify(mockNdrBuffer, times(2)).enc_ndr_short(0); // length and maximum_length are both 0
        verify(mockNdrBuffer, times(2)).enc_ndr_referent(null, 1); // Called twice for name.buffer and sid
        verify(mockDeferredNdrBuffer, never()).enc_ndr_long(anyInt());
        verify(mockDeferredNdrBuffer, never()).enc_ndr_short(anyShort());
        // Note: NdrBuffer does not have encode method

   *
   * <p>The current implementation uses the concurrency level to create a fixed number of hashtable
   * segments, each governed by its own write lock. The segment lock is taken once for each explicit
   * write, and twice for each cache loading computation (once prior to loading the new value, and
   * once after loading completes). Much internal cache management is performed at the segment

      }

      // the base implementation from AbstractSet uses size() and containsAll()
      // both require iterating over the entire SetView
      // we avoid iterating twice by doing the equivalent of both in one iteration
      int thisSize = 0;
      for (E e : this) {
        try {
          if (!that.contains(e)) {
            return false;
          }

//           non-alphanumeric characters to '_' to make resulting names match
//           the "[a-z][a-z0-9_]*" pattern for operation argument names.
//           `inputs` cannot contain the same tensor twice.
//  noutputs - number of elements in `outputs` array
//  outputs - array of TF_Outputs that specify the outputs of the function.
//            If `noutputs` is zero (the function returns no outputs), `outputs`