if (features.remove(CollectionFeature.ALLOWS_NULL_VALUES)) {
      // the null value might be out of bounds, so we can't always construct a subset with nulls
      features.add(CollectionFeature.ALLOWS_NULL_QUERIES);
      // but add null might still be supported if it happens to be within range of the subset
      suppressing.add(CollectionAddTester.getAddNullUnsupportedMethod());

      --enable-languages="c,c++" \
      --enable-linker-build-id \
      --enable-plugin \
      --enable-shared \
      --enable-threads=posix \
      --with-default-libstdcxx-abi=${LIBSTDCXX_ABI} \
      --with-gcc-major-version-only \
      --with-linker-hash-style="gnu" \
      && \
      make -j$(nproc) && \
      make install


# Create the devtoolset libstdc++ linkerscript that links dynamically against

   If it is impossible for You to comply with any of the terms of this License
   with respect to some or all of the Covered Software due to statute, judicial
   order, or regulation then You must: (a) comply with the terms of this License
   to the maximum extent possible; and (b) describe the limitations and the code
   they affect. Such description must be placed in a text file included with all

typedef struct TF_Input {
  TF_Operation* oper;
  int index;  // The index of the input within oper.
} TF_Input;

// Represents a specific output of an operation.
typedef struct TF_Output {
  TF_Operation* oper;
  int index;  // The index of the output within oper.
} TF_Output;

// TF_Function is a grouping of operations with defined inputs and outputs.

   * overkill for most Atomics because they are usually irregularly
   * scattered in memory and thus don't interfere much with each
   * other. But Atomic objects residing in arrays will tend to be
   * placed adjacent to each other, and so will most often share
   * cache lines (with a huge negative performance impact) without
   * this precaution.
   *
   * In part because Cells are relatively large, we avoid creating

a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexibility to the application developer, whereas in previous “parameter server” designs the management of shared state is built into the system, TensorFlow enables developers to experiment with novel optimizations and training algorithms. TensorFlow...

    /** Applies this function to the given argument and its index within a stream. */
    @ParametricNullness
    R apply(@ParametricNullness T from, long index);
  }

  /*
   * @IgnoreJRERequirement should be redundant with the one on Streams itself, but it's necessary as
   * of Animal Sniffer 1.24. Maybe Animal Sniffer processes this nested class before it processes

 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this library; if not, write to the Free Software
 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
 */

package jcifs.smb1.smb1;

public interface WinError {

    /* Don't bother to edit this. Everthing within the interface
     * block is automatically generated from the ntstatus package.
     */

		if group > 0 {
			for k := range timeOccurrenceMap {
				if k == nano {
					// We add to ourself later
					continue
				}
				diff := k - nano
				if diff < 0 {
					diff = -diff
				}
				// We are within the limit
				if diff < groupNano {
					timeOccurrenceMap[k]++
				}
			}
		}
		// Add ourself...
		timeOccurrenceMap[nano]++
	}

	maxima = 0 // Counter for remembering max occurrence of elements.

                    + count
                    + " trials");
          }
        }
      }
    }
  }

  /**
   * Test for avalanche with 2-bit deltas. Most probabilities of output bit(j) differing are well
   * within 50%.
   */
  static void check2BitAvalanche(HashFunction function, int trials, double epsilon) {
    Random rand = new Random(0);
    int keyBits = 32;