continue
			}
			if e := buf.Flush(); e != nil {
				t.Errorf("%s: buf.Flush = %v", context, e)
			}

			written := w.Bytes()
			if len(written) != nwrite {
				t.Errorf("%s: %d bytes written", context, len(written))
			}
			for l := 0; l < len(written); l++ {
				if written[l] != data[l] {
					t.Errorf("wrong bytes written")
					t.Errorf("want=%q", data[:len(written)])

	w, err := zw.CreateHeader(hdr)
	if err != nil {
		t.Fatalf("create zip header: %v", err)
	}
	_, err = w.Write([]byte("some data"))
	if err != nil {
		t.Fatalf("write zip contents: %v", err)

	}
	err = zw.Close()
	if err != nil {
		t.Fatalf("close zip writer: %v", err)

	}

	zr, err := NewReader(bytes.NewReader(buf.Bytes()), int64(buf.Len()))
	if err != nil {

				"application/vnd.sun.xml.impress",
				"application/vnd.sun.xml.impress.template",
				"application/vnd.sun.xml.math",
				"application/vnd.sun.xml.writer",
				"application/vnd.sun.xml.writer.global",
				"application/vnd.sun.xml.writer.template",
				"application/vnd.sun.wadl+xml",
				"application/vnd.sus-calendar",
				"application/vnd.svd",
				"application/vnd.swiftview-ics",

build:elinux_armhf --platforms=@org_tensorflow//tensorflow/tools/toolchains/linux:linux_armhf
build:elinux_armhf --copt -mfp16-format=ieee

# Config-specific options should come above this line.

# Load rc file written by ./configure.
try-import %workspace%/.tf_configure.bazelrc

# Load rc file with user-specific options.
try-import %workspace%/.bazelrc.user

# Here are bazelrc configs for release builds

java.util.Map optionsByString; private boolean allowMixedOptions; private boolean allowUnknownOptions; private final java.io.PrintWriter deprecationPrinter; static void <clinit>(); public void CommandLineParser(); public void CommandLineParser(java.io.Writer); public transient ParsedCommandLine parse(String[]) throws CommandLineArgumentE; public ParsedCommandLine parse(Iterable) throws CommandLineArgumentE; public CommandLineParser allowMixedSubcommand(); public CommandLineParser allowUnknownOptions();...

				if n == 0 {
					out.Write(in[i:])
					break
				}
				if HasPrefix(in[i:], old) {
					out.Write(new)
					i += len(old)
					n--
					if len(old) != 0 {
						continue
					}
					if i == len(in) {
						break
					}
				}
				if len(old) == 0 {
					_, length := utf8.DecodeRune(in[i:])
					out.Write(in[i : i+length])
					i += length

//   DoSomethingWithOperation(oper);
// }
TF_CAPI_EXPORT extern TF_Operation* TF_GraphNextOperation(TF_Graph* graph,
                                                          size_t* pos);

// Write out a serialized representation of `graph` (as a GraphDef protocol
// message) to `output_graph_def` (allocated by TF_NewBuffer()).
// `output_graph_def`'s underlying buffer will be freed when TF_DeleteBuffer()
// is called.

	//TODO: this compiles to add r5,r6,r0. It should be addi r5,r6,0.
	//      this is OK since r0 == $0, but the latter is preferred.
	ADD $0, R6, R5             	// 7ca60214

        //TODO: the assembler rewrites these into ADDIS $19, R5, Rx and ADD $-10617, Rx, Rx, but the test only sees the first ADDIS
	ADD $1234567, R5                // 3ca50013 or 0600001238a5d687
	ADD $1234567, R5, R6            // 3cc50013 or 0600001238c5d687

tyle(e[0]))?d.display:n.css(e[0],"display");return e.detach(),f}function tb(a){var b=l,c=rb[a];return c||(c=sb(a,b),"none"!==c&&c||(qb=(qb||n("<iframe frameborder='0' width='0' height='0'/>")).appendTo(b.documentElement),b=qb[0].contentDocument,b.write(),b.close(),c=sb(a,b),qb.detach()),rb[a]=c),c}var ub=/^margin/,vb=new RegExp("^("+Q+")(?!px)[a-z%]+$","i"),wb=function(a){return a.ownerDocument.defaultView.getComputedStyle(a,null)};function xb(a,b,c){var d,e,f,g,h=a.style;return c=c||wb(a),c&&(g...

  const string input_name =
      signature_def.inputs().at(tensorflow::kRegressInputs).name();
  const string output_name =
      signature_def.outputs().at(tensorflow::kRegressOutputs).name();

  // Write {0, 1, 2, 3} as tensorflow::Example inputs.
  Tensor input(tensorflow::DT_STRING, TensorShape({4}));
  for (int64_t i = 0; i < input.NumElements(); ++i) {
    tensorflow::Example example;