continue NextSetOfPrimes
				}
			}
		}

		n := new(big.Int).Set(bigOne)
		totient := new(big.Int).Set(bigOne)
		pminus1 := new(big.Int)
		for _, prime := range primes {
			n.Mul(n, prime)
			pminus1.Sub(prime, bigOne)
			totient.Mul(totient, pminus1)
		}
		if n.BitLen() != bits {
			// This should never happen for nprimes == 2 because
			// crypto/rand should set the top two bits in each prime.

    }
  }

  private abstract static class DelayedActionRunnable implements Runnable {
    private final long tMinus;

    protected DelayedActionRunnable(long tMinus) {
      this.tMinus = tMinus;
    }

    @Override
    public final void run() {
      try {
        Thread.sleep(tMinus);
      } catch (InterruptedException e) {
        throw new AssertionError(e);
      }
      doAction();
    }

        "BroadcastMul is not supported in tracing mode yet.");
  }
  auto imm_ctx = dyn_cast<ImmediateExecutionContext>(ctx);
  AbstractTensorPtr minus_1(imm_ctx->CreateInt32Scalar(-1));
  ImmediateTensorHandlePtr dim(imm_ctx->CreateLocalHandle(minus_1.get()));
  AbstractTensorHandle* expand_dims_outputs;
  TF_RETURN_IF_ERROR(
      ops::ExpandDims(ctx, vec, dim.get(), &expand_dims_outputs, "ExpandDims"));

	if cgo_libc_setegid != nil {
		return minus1, minus1, ENOTSUP
	}
	r1, r2, errno := runtime_doAllThreadsSyscall(trap, a1, a2, a3, a4, a5, a6)
	return r1, r2, Errno(errno)
}

// linked by runtime.cgocall.go
//
//go:uintptrescapes
func cgocaller(unsafe.Pointer, ...uintptr) uintptr

var cgo_libc_setegid unsafe.Pointer // non-nil if cgo linked.

const minus1 = ^uintptr(0)

    name = "Neg_Div_Grad_Y";
    TF_RETURN_IF_ERROR(Neg(ctx, upstream_grad, &temp_output,
                           name.c_str()));  // -U
    AbstractTensorHandlePtr MinusU(temp_output);

    name = "Mul_Div_Grad_Y";
    TF_RETURN_IF_ERROR(Mul(ctx, MinusU.get(), Z, &temp_output,
                           name.c_str()));  // -U*Z
    AbstractTensorHandlePtr UZ(temp_output);

    name = "Div_Grad_Y";

    plus(configuration.get())


/**
 * See [Configuration.minus].
 */
@Deprecated(deprecationMessage, replaceWith = ReplaceWith("get().minus(collection)"), level = DeprecationLevel.HIDDEN)
operator fun <T : Configuration> NamedDomainObjectProvider<T>.minus(collection: FileCollection): FileCollection =
    get().minus(collection)


/**
 * See [Configuration.minus].
 */

              return roundCeilingAsDouble;
            }
            roundFloor = toX(roundFloorAsDouble, RoundingMode.FLOOR);
          }

          X deltaToFloor = minus(x, roundFloor);
          X deltaToCeiling = minus(roundCeiling, x);
          int diff = deltaToFloor.compareTo(deltaToCeiling);
          if (diff < 0) { // closer to floor
            return roundFloorAsDouble;

		// form. So we'll invert and subtract 1. If the
		// most-significant-bit isn't set then we'll need to pad the
		// beginning with 0xff in order to keep the number negative.
		nMinus1 := new(big.Int).Neg(n)
		nMinus1.Sub(nMinus1, bigOne)
		bytes := nMinus1.Bytes()
		for i := range bytes {
			bytes[i] ^= 0xff
		}
		if len(bytes) == 0 || bytes[0]&0x80 == 0 {
			return multiEncoder([]encoder{byteFFEncoder, bytesEncoder(bytes)}), nil

              return roundCeilingAsDouble;
            }
            roundFloor = toX(roundFloorAsDouble, RoundingMode.FLOOR);
          }

          X deltaToFloor = minus(x, roundFloor);
          X deltaToCeiling = minus(roundCeiling, x);
          int diff = deltaToFloor.compareTo(deltaToCeiling);
          if (diff < 0) { // closer to floor
            return roundFloorAsDouble;

    TF_RETURN_IF_ERROR(
        RunAndMaybeSum(ctx, forward, theta_inputs, f_outputs, use_function));
    AbstractTensorHandlePtr fMinus(f_outputs[0]);

    // Take Difference of both estimates: (f(theta + eps) - f(theta - eps)).
    TF_RETURN_IF_ERROR(
        ops::Sub(ctx, fPlus.get(), fMinus.get(), f_outputs, "sub_top"));
    AbstractTensorHandlePtr fDiff(f_outputs[0]);

    // Calculate using the difference quotient definition: