outputContains("Compiling with toolchain '${curJvm.javaHome.absolutePath}'")
        outputContains("Compiling with JDK Java compiler API")
        outputDoesNotContain("Compiling with Java command line compiler")
        outputDoesNotContain("Started Gradle worker daemon")
        classJavaVersion(javaClassFile("Foo.class")) == JavaVersion.toVersion(curJvm.javaVersion)

        where:

			fns := fileNodes[filename]
			flatSum, cumSum := fns.Sum()

			fnodes, _, err := getSourceFromFile(filename, reader, fns, 0, 0)
			fmt.Fprintf(w, "ROUTINE ======================== %s in %s\n", name, filename)
			fmt.Fprintf(w, "%10s %10s (flat, cum) %s of Total\n",
				rpt.formatValue(flatSum), rpt.formatValue(cumSum),
				measurement.Percentage(cumSum, rpt.total))

			if err != nil {

// func switchToCrashStack0(fn func())
TEXT runtime·switchToCrashStack0(SB), NOSPLIT, $0-8
	MOVD fn+0(FP), CTXT	// context register
	MOVD	g_m(g), R2	// curm

	// set g to gcrash
	MOVD	$runtime·gcrash(SB), g	// g = &gcrash
	MOVD	R2, g_m(g)	// g.m = curm
	MOVD	g, m_g0(R2)	// curm.g0 = g

	// switch to crashstack
	I64Load (g_stack+stack_hi)(g)
	I64Const $(-4*8)
	I64Add
	I32WrapI64
	Set SP

  int axis = std::get<2>(GetParam());

  TensorShape shape({2, 3, 2});
  auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(shape));
  Cumsum::Attrs attrs;
  attrs.exclusive_ = std::get<0>(GetParam());
  attrs.reverse_ = std::get<1>(GetParam());
  auto y = Cumsum(scope_, x, axis, attrs);
  RunTest({x}, {shape}, {y}, {shape});
}

INSTANTIATE_TEST_SUITE_P(CumsumGrad, CumsumGradTest,

* Veri doğrulama
* API tanımlamaları ve otomatik dokümantasyon

Ve sadece, bunları bir kez tanımlamanız yeterli.

### Burger Sonucu

Bu "aşkınla fast food burgerleri" senaryosunda, çok fazla bekleme olduğu için 🕙, eşzamanlı bir sisteme sahip olmak çok daha mantıklı ⏸🔀⏯.

Web uygulamalarının çoğu için durum böyledir.

Pek çok kullanıcı var, ama sunucunuz pek de iyi olmayan bir bağlantı ile istek atmalarını bekliyor.

Ve sonra yanıtların geri gelmesi için tekrar 🕙 bekliyor

    """
    total_freq = sum(self._hist_freq)
    # hist_freq_cumsum is dividing cumulative sum of hist_freq by total_freq
    # hist_freq_cumsum's value is in range [0, 1] by its definition
    hist_freq_cumsum = np.cumsum(self._hist_freq) / total_freq

    # min_percentile and max_percentile are converted from [0, 100] to [0, 1].
    min_quantile, max_quantile = (
        self._calib_opts.calibration_parameters.min_percentile / 100.0,

			fmt.Fprintf(w, "    AKA ======================== %s\n", name)
		}
		fmt.Fprintf(w, "%10s %10s (flat, cum) %s of Total\n",
			rpt.formatValue(flatSum), rpt.formatValue(cumSum),
			measurement.Percentage(cumSum, rpt.total))

		function, file, line := "", "", 0
		for _, n := range ns {
			locStr := ""
			// Skip loc information if it hasn't changed from previous instruction.

TEXT runtime·switchToCrashStack0(SB), NOSPLIT, $0-8
	MOVV	fn+0(FP), REGCTXT	// context register
	MOVV	g_m(g), R2	// curm

	// set g to gcrash
	MOVV	$runtime·gcrash(SB), g	// g = &gcrash
	CALL	runtime·save_g(SB)
	MOVV	R2, g_m(g)	// g.m = curm
	MOVV	g, m_g0(R2)	// curm.g0 = g

	// switch to crashstack
	MOVV	(g_stack+stack_hi)(g), R2
	ADDV	$(-4*8), R2, R29

	// call target function

TEXT runtime·switchToCrashStack0(SB), NOSPLIT, $0-8
	MOVV	fn+0(FP), REGCTXT	// context register
	MOVV	g_m(g), R4	// curm

	// set g to gcrash
	MOVV	$runtime·gcrash(SB), g	// g = &gcrash
	JAL	runtime·save_g(SB)
	MOVV	R4, g_m(g)	// g.m = curm
	MOVV	g, m_g0(R4)	// curm.g0 = g

	// switch to crashstack
	MOVV	(g_stack+stack_hi)(g), R4
	ADDV	$(-4*8), R4, R3

	// call target function