* we wanted to support legacy classes that implement the raw type {@code Comparable} (instead of
   * implementing {@code Comparable<Foo>}) without producing warnings. If so, we would prefer today
   * to produce warnings in that case, and we may change this method to do so in the future. Support
   * for raw {@code Comparable} types in Guava in general is tracked as <a

        this.flags = SMBUtil.readInt4(buffer, bufferIndex + 4); // Flags (4 bytes)
        return 8;
    }

    /**
     * Get the timeout value in 100-nanosecond intervals (raw wire format)
     * @return the timeout in 100-nanosecond intervals
     */
    public long getTimeout100Ns() {
        return timeout100Ns;
    }

    /**
     * Get the timeout value converted to milliseconds

    ModelBuildingResult build(ModelBuildingRequest request, ModelBuildingResult result) throws ModelBuildingException;

    /**
     * Performs only the part of {@link ModelBuilder#build(ModelBuildingRequest)} that loads the raw model
     */
    Result<? extends Model> buildRawModel(File pomFile, int validationLevel, boolean locationTracking);

          if (x * i == n) return factor(x) + " × " + i;
        }
        return Integer.toString(n);
      }
    };

    Request request = new Request.Builder()
        .url("https://api.github.com/markdown/raw")
        .post(requestBody)
        .build();

    try (Response response = client.newCall(request).execute()) {
      if (!response.isSuccessful()) throw new IOException("Unexpected code " + response);

### 1. Fetch the root identity

As the initial step, fetch the private key and certificate of the root identity:

```sh
curl -sSL --tlsv1.2 \
     -O 'https://raw.githubusercontent.com/minio/kes/master/root.key' \
     -O 'https://raw.githubusercontent.com/minio/kes/master/root.cert'
```

### 2. Set the MinIO-KES configuration

```sh
export MINIO_KMS_KES_ENDPOINT=https://play.min.io:7373

  public void run() throws Exception {
    final PipeBody pipeBody = new PipeBody();

    Request request = new Request.Builder()
        .url("https://api.github.com/markdown/raw")
        .post(pipeBody)
        .build();

    streamPrimesToSinkAsynchronously(pipeBody.sink());

    try (Response response = client.newCall(request).execute()) {

            }
        }
        cookey(kn, KnL);
    }

    private void cookey(final int[] raw, final int KnL[]) {
        int raw0, raw1;
        int rawi, KnLi;
        int i;

        for (i = 0, rawi = 0, KnLi = 0; i < 16; ++i) {
            raw0 = raw[rawi];
            rawi++;
            raw1 = raw[rawi++];
            KnL[KnLi] = (raw0 & 0x00fc0000) << 6;
            KnL[KnLi] |= (raw0 & 0x00000fc0) << 10;

)

// PReader - JSON record reader for S3Select.
// Operates concurrently on line-delimited JSON.
type PReader struct {
	args        *ReaderArgs
	readCloser  io.ReadCloser             // raw input
	buf         *bufio.Reader             // input to the splitter
	current     []jstream.KVS             // current block of results to be returned
	recordsRead int                       // number of records read in current slice

when dealing with untrusted data. Based on the security history of these
libraries we consider that it is safe to work with untrusted inputs for PNG,
BMP, GIF, WAV, RAW, RAW\_PADDED, CSV and PROTO formats. All other input formats,
including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could

    @SuppressWarnings("rawtypes") // Trying to test raw class
    TypeToken<List> tokL = new TypeToken<List>() {};
    assertTrue(tokL.isSupertypeOf(StringList.class));
    assertTrue(tokL.isSupertypeOf(StringList.class.getGenericInterfaces()[0]));

    @SuppressWarnings("rawtypes") // Trying to test raw class
    TypeToken<Second> tokS = new TypeToken<Second>() {};