// and sets 'device_name' accordingly.
// `device_type` must be either "GPU" or "TPU".
bool GetDeviceName(TFE_Context* ctx, tensorflow::string* device_name,
                   const char* device_type);

// Create a ServerDef with the given `job_name` and add `num_tasks` tasks in it.
tensorflow::ServerDef GetServerDef(const tensorflow::string& job_name,
                                   int num_tasks);

        radix);
    if (x == 0) {
      // Simply return "0"
      return "0";
    } else if (x > 0) {
      return Long.toString(x, radix);
    } else {
      char[] buf = new char[64];
      int i = buf.length;
      if ((radix & (radix - 1)) == 0) {
        // Radix is a power of two so we can avoid division.
        int shift = Integer.numberOfTrailingZeros(radix);

  public Hasher putLong(long l) {
    ByteBuffer scratch = scratch();
    scratch.putLong(l);
    return update(scratch, Longs.BYTES);
  }

  @Override
  @CanIgnoreReturnValue
  public Hasher putChar(char c) {
    ByteBuffer scratch = scratch();
    scratch.putChar(c);
    return update(scratch, Chars.BYTES);
  }

  private ByteBuffer scratch() {
    if (scratch == null) {

/**
 * Extracts non-overlapping substrings from an input string, typically by recognizing appearances of
 * a <i>separator</i> sequence. This separator can be specified as a single {@linkplain #on(char)
 * character}, fixed {@linkplain #on(String) string}, {@linkplain #onPattern regular expression} or
 * {@link #on(CharMatcher) CharMatcher} instance. Or, instead of using a separator at all, a

#
# Default mapping as follows:
# --------------------------------------------------------
# | JDBC Type     | Java Native          | CSharp Native |
# | ------------------------------------------------------
# | CHAR          | java.lang.String     | String        |
# | VARCHAR       | java.lang.String     | String        |
# | LONGVARCHAR   | java.lang.String     | String        |
# | NUMERIC       | java.math.BigDecimal | decimal?      |

    protected static DcerpcBinding parseBinding(final String str) throws DcerpcException {
        int state, mark, si;
        final char[] arr = str.toCharArray();
        String proto = null, key = null;
        DcerpcBinding binding = null;

        state = mark = si = 0;
        do {
            final char ch = arr[si];

            switch (state) {
            case 0:
                if (ch == ':') {

   * @param off the offset into the buffer
   * @param len the number of characters to process
   * @throws IOException if an I/O error occurs
   * @see #finish
   */
  protected void add(char[] cbuf, int off, int len) throws IOException {
    int pos = off;
    if (sawReturn && len > 0) {
      // Last call to add ended with a CR; we can handle the line now.
      if (finishLine(cbuf[pos] == '\n')) {
        pos++;

        }

        final long start = System.currentTimeMillis();
        final StringBuilder buf = new StringBuilder(searchWord.length());
        char prev = 0;
        for (final char c : searchWord.toCharArray()) {
            if (!Character.isWhitespace(c)) {
                buf.append(c);
            } else if (!Character.isWhitespace(prev)) {
                buf.append(' ');

        out.println("</td></tr></table>");
        out.println("</BODY></HTML>");
        out.close();
    }

    private String parseServerAndShare(final String pathInfo) {
        final char[] out = new char[256];
        char ch;
        int len, p, i;

        if (pathInfo == null) {
            return null;
        }
        len = pathInfo.length();

        p = i = 0;

namespace gradients {
namespace internal {
namespace {
using std::vector;
using tensorflow::TF_StatusPtr;
using tracing::TracingOperation;

class CppGradients
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());
    TF_SetTracingImplementation(std::get<0>(GetParam()), status.get());
    absl::Status s = StatusFromTF_Status(status.get());