stated above is already equivalent to code execution. In any case, the
recommendation is not to serve models using Eager mode since it also has
performance limitations.

## Multi-Tenant environments

It is possible to run multiple TensorFlow models in parallel. For example,
`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running

	} DfsEnumInfo;

	typedef struct {
		uint32_t level,
		[switch_is(level)] DfsEnumInfo e;
	} DfsEnumStruct;

	[op(0x15)]
	int NetrDfsEnumEx([in,string,unique] wchar_t dfs_name,
			[in] uint32_t level,
			[in] uint32_t prefmaxlen,
			[in,out,unique] DfsEnumStruct *info,
			[in,out,unique] uint32_t *totalentries);

    /** Format error in the name service */
    public static final int FMT_ERR = 0x1;
    /** Server error in the name service */
    public static final int SRV_ERR = 0x2;
    /** Implementation error in the name service */
    public static final int IMP_ERR = 0x4;
    /** Refused error in the name service */
    public static final int RFS_ERR = 0x5;
    /** Active error in the name service */

    }

    public void testParse() {
        RobotsTxt robotsTxt;
        final InputStream in = RobotsTxtHelperTest.class.getResourceAsStream("robots.txt");
        try {
            robotsTxt = robotsTxtHelper.parse(in);
        } finally {
            CloseableUtil.closeQuietly(in);
        }

        for (String userAgent : new String[] { "FessCrawler", "FessCrawler/1.0", "Mozilla FessCrawler" }) {

 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,

  }

  @Override
  public InputStream openStream() throws IOException {
    inputStreamOpened = true;
    return new RandomAmountInputStream(new In(), new Random());
  }

  private final class In extends TestInputStream {

    In() throws IOException {
      super(new ByteArrayInputStream(bytes), options);
    }

    @Override
    public void close() throws IOException {

  }

  @Override
  public InputStream openStream() throws IOException {
    inputStreamOpened = true;
    return new RandomAmountInputStream(new In(), new Random());
  }

  private final class In extends TestInputStream {

    In() throws IOException {
      super(new ByteArrayInputStream(bytes), options);
    }

    @Override
    public void close() throws IOException {

    }

    public void test_getText() {
        final InputStream in = ResourceUtil.getResourceAsStream("extractor/msoffice/test.xls");
        final String content = msExcelExtractor.getText(in, null).getContent();
        CloseableUtil.closeQuietly(in);
        logger.info(content);
        assertTrue(content.contains("テスト"));
    }

    public void test_getText_null() {

    }

    public void test_getText() {
        final InputStream in = ResourceUtil.getResourceAsStream("extractor/msoffice/test.ppt");
        final String content = msPowerPointExtractor.getText(in, null).getContent();
        CloseableUtil.closeQuietly(in);
        logger.info(content);
        assertTrue(content.contains("テスト"));
    }

    public void test_getText_null() {

     * Extracts the filename from the parameters.
     * @param in The input stream (not used).
     * @param params The parameters, expected to contain ExtractData.RESOURCE_NAME_KEY.
     * @return An ExtractData object containing the filename as content.
     */
    @Override
    public ExtractData getText(final InputStream in, final Map<String, String> params) {
        if (in == null) {