* Converter.apply (like Converter.convert) is capable of accepting null inputs. However, a
 * supertype of `Function<A, B>` turns out to be massively more useful to callers in practice: They
 * want their output to be non-null in operations like `stream.map(myConverter)`, and we can
 * guarantee that as long as we also require the input type to be non-null[*] (which is a
 * requirement that existing callers already fulfill).
 *

   * {@code Supplier}, whose elements are the result of applying {@code elementFunction} to the
   * inputs, with counts equal to the result of applying {@code countFunction} to the inputs.
   * Elements are added in encounter order.
   *
   * <p>If the mapped elements contain duplicates (according to {@link Object#equals}), the element

   * {@code Supplier}, whose elements are the result of applying {@code elementFunction} to the
   * inputs, with counts equal to the result of applying {@code countFunction} to the inputs.
   * Elements are added in encounter order.
   *
   * <p>If the mapped elements contain duplicates (according to {@link Object#equals}), the element

   * that gets messy here, and we already have null tests for Range.
   */

  /*
   * These generators also rely on consecutive integer inputs (not necessarily in order, but no
   * holes).
   */

  // SetCreationTester has some tests that pass in duplicates. Dedup them.

	// LDADDx/SWPx/CASx atomic instructions
	return arm64.IsAtomicInstruction(op)
}

// IsARM64TBL reports whether the op (as defined by an arm64.A*
// constant) is one of the TBL-like instructions and one of its
// inputs does not fit into prog.Reg, so require special handling.
func IsARM64TBL(op obj.As) bool {
	switch op {
	case arm64.AVTBL, arm64.AVTBX, arm64.AVMOVQ:
		return true
	}
	return false
}

		pc, file, lineNumber, ok = runtime.Caller(traceLevel)
	}
	return trace
}

// HashString - return the highway hash of the passed string
func HashString(input string) string {
	hh, _ := highwayhash.New(magicHighwayHash256Key)
	hh.Write([]byte(input))
	return hex.EncodeToString(hh.Sum(nil))
}

// LogAlwaysIf prints a detailed error message during
// the execution of the server.

        assertEquals(expectedLong, LongMath.binomial(n, k));
      }
    }
  }


  @GwtIncompatible // Slow
  public void testBinomial_exhaustiveNotOverflowing() {
    // Tests all of the inputs to LongMath.binomial that won't cause it to overflow, that weren't
    // tested in the previous method, for k >= 3.
    for (int k = 3; k < LongMath.biggestBinomials.length; k++) {

   * that gets messy here, and we already have null tests for Range.
   */

  /*
   * These generators also rely on consecutive integer inputs (not necessarily in order, but no
   * holes).
   */

  // SetCreationTester has some tests that pass in duplicates. Dedup them.

  return tensorflow::unwrap(op)->DeviceName().c_str();
}

void TFE_OpAddInput(TFE_Op* op, TFE_TensorHandle* input, TF_Status* status) {
  status->status = tensorflow::unwrap(op)->AddInput(tensorflow::unwrap(input));
}

void TFE_OpAddInputList(TFE_Op* op, TFE_TensorHandle** inputs, int num_inputs,
                        TF_Status* status) {
  status->status = tensorflow::unwrap(op)->AddInputList(

    if (yStats.count() == 0) {
      sumOfProductsOfDeltas = values.sumOfProductsOfDeltas();
    } else {
      // This is a generalized version of the calculation in add(double, double) above. Note that
      // non-finite inputs will have sumOfProductsOfDeltas = NaN, so non-finite values will result
      // in NaN naturally.
      sumOfProductsOfDeltas +=
          values.sumOfProductsOfDeltas()
              + (values.xStats().mean() - xStats.mean())