#     elinux_aarch64:  Embedded Linux options for aarch64 (ARM64) CPU support.
#     elinux_armhf:    Embedded Linux options for armhf (ARMv7) CPU support.
#
# Release build options (for all operating systems)
#     release_base:                    Common options for all builds on all operating systems.
#     release_cpu_linux:               Toolchain and CUDA options for Linux CPU builds.

b-1]}),eq:nb(function(a,b,c){return[0>c?c+b:c]}),even:nb(function(a,b){for(var c=0;b>c;c+=2)a.push(c);return a}),odd:nb(function(a,b){for(var c=1;b>c;c+=2)a.push(c);return a}),lt:nb(function(a,b,c){for(var d=0>c?c+b:c;--d>=0;)a.push(d);return a}),gt:nb(function(a,b,c){for(var d=0>c?c+b:c;++d<b;)a.push(d);return a})}},d.pseudos.nth=d.pseudos.eq;for(b in{radio:!0,checkbox:!0,file:!0,password:!0,image:!0})d.pseudos[b]=lb(b);for(b in{submit:!0,reset:!0})d.pseudos[b]=mb(b);function pb(){}pb.prototype...

    /** Property name for socket timeout setting */
    public static final String SO_TIMEOUT_PROPERTY = "soTimeout";

    /** Property name for proxy host setting */
    public static final String PROXY_HOST_PROPERTY = "proxyHost";

    /** Property name for proxy port setting */
    public static final String PROXY_PORT_PROPERTY = "proxyPort";

    /** Property name for proxy authentication scheme setting */

		t.Fatalf("file count=%d, want %d", len(z.File), len(zt.File))
	}

	// test read of each file
	for i, ft := range zt.File {
		readTestFile(t, zt, ft, z.File[i], raw)
	}
	if t.Failed() {
		return
	}

	// test simultaneous reads
	n := 0
	done := make(chan bool)
	for i := 0; i < 5; i++ {
		for j, ft := range zt.File {
			go func(j int, ft ZipTestFile) {
				readTestFile(t, zt, ft, z.File[j], raw)

		}
	}
}

// make sure Equal returns false for minimally different strings. The data
// is all zeros except for a single one in one location.
func TestNotEqual(t *testing.T) {
	var size = 128
	if testing.Short() {
		size = 32
	}
	a := make([]byte, size)
	b := make([]byte, size)

	for len := 0; len <= size; len++ {
		for x := 0; x <= size-len; x++ {
			for y := 0; y <= size-len; y++ {

	var texts [31]string
	str := ""
	all := ""
	for i := 0; i < len(texts)-1; i++ {
		texts[i] = str + "\n"
		all += texts[i]
		str += string(rune(i%26 + 'a'))
	}
	texts[len(texts)-1] = all

	for h := 0; h < len(texts); h++ {
		text := texts[h]
		for i := 0; i < len(readMakers); i++ {
			for j := 0; j < len(bufreaders); j++ {
				for k := 0; k < len(bufsizes); k++ {
					readmaker := readMakers[i]

				"application/vnd.shana.informed.package",
				"application/vnd.simtech-mindmapper",
				"application/vnd.smaf",
				"application/vnd.smart.teacher",
				"application/vnd.software602.filler.form+xml",
				"application/vnd.software602.filler.form-xml-zip",
				"application/vnd.solent.sdkm+xml",
				"application/vnd.spotfire.dxp",
				"application/vnd.spotfire.sfs",
				"application/vnd.sss-cod",
				"application/vnd.sss-dtf",

const char* kNegStackToString = "File \"neg.cc\", line 15, in beta";

std::vector<IOSpec> M(const std::initializer_list<string>& names) {
  std::vector<IOSpec> v;
  for (const string& name : names) {
    v.push_back(IOSpec(name, DT_INVALID));
  }
  return v;
}

// Specification for an expected edge.
// src is either:
// - input name (as it appears in FunctionDef)
// - name of output tensor (in nested "add:z:0" format)
// dst is either:

	VPGATHERQQ Y0, (R13)(Y1*1), Y2          // c4c2fd91540d00
	VPGATHERQQ Y0, 16(R13)(Y1*1), Y2        // c4c2fd91540d10
	VPGATHERQQ Y0, 512(R13)(Y1*1), Y2       // c4c2fd91940d00020000
	// Test low-8 register for /is4 "hr" operand.
	VPBLENDVB X0, (BX), X1, X2              // c4e3714c1300
	// <XMM0>/Yxr0 tests.
	SHA256RNDS2 X0, (BX), X2   // 0f38cb13
	SHA256RNDS2 X0, (R11), X2  // 410f38cb13
	SHA256RNDS2 X0, X2, X2     // 0f38cbd2

void TestEncodeDecode(int line, const std::vector<string>& data) {
  const int64_t n = data.size();
  absl::Status status;
  for (const std::vector<int64_t>& dims :
       std::vector<std::vector<int64_t>>{{n}, {1, n}, {n, 1}, {n / 2, 2}}) {
    // Create C++ Tensor
    Tensor src(tensorflow::DT_STRING, TensorShape(dims));
    for (int64_t i = 0; i < src.NumElements(); ++i) {
      src.flat<tstring>()(i) = data[i];
    }