</field>
        <field>
          <name>classLoadingStrategy</name>
          <description>The class loading strategy: 'self-first' (the default), 'parent-first' (loads classes from the parent, then from the extension) or 'plugin' (follows the rules from extensions defined as plugins).</description>
          <version>1.1.0+</version>
          <defaultValue>self-first</defaultValue>
          <required>false</required>

       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the $LD_LIBRARY_PATH environment variable.
       * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).
     * If error still persists then, apparently your CPU model does not support AVX instruction sets.
       * Refer [hardware requirements](https://www.tensorflow.org/install/pip#hardware-requirements).
   

#
# Repacks libtensorflow tarballs into $DIR with provided $TARBALL_SUFFIX.

DIR=$1
mkdir -p "$DIR"
TARBALL_SUFFIX=$2

if [[ $(uname -s) != MSYS_NT* ]]; then
  cp bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz "${DIR}/libtensorflow${TARBALL_SUFFIX}.tar.gz"
  cp bazel-bin/tensorflow/tools/lib_package/libtensorflow_proto.zip "${DIR}"
else

<%@page pageEncoding="UTF-8" contentType="text/html; charset=UTF-8"%>
<h2>Query Syntax</h2>
<dl>
	<dt>Field</dt>
	<dd>
		You can search any field by typing the field name followed by a colon
		":" and then the term you are looking for. If you want to find
		documents which has "Fess" as the document title, you can enter:
		<pre>title:Fess</pre>
		The available fields are "url", "host", "site", "title", "content",

    thread2.join();
    assertEquals(1, runCalled.get());
  }

  public void testAddAfterRun() throws Exception {
    // Run the previous test
    testRunOnPopulatedList();

    // If it passed, then verify an Add will be executed without calling run
    CountDownLatch countDownLatch = new CountDownLatch(1);
    list.add(new MockRunnable(countDownLatch), newCachedThreadPool());
    assertTrue(countDownLatch.await(1L, SECONDS));

 * <p>
 * If the {@code requestType} is not set explicitly, it will be inferred
 * from the {@code pathScope} and the injected field type. If the type
 * is {@link org.apache.maven.api.Node Node} and {@code pathScope == ""},
 * then the dependencies will be <i>collected</i>.
 * If the type is {@link org.apache.maven.api.Node Node} or
 * {@code List<}{@link org.apache.maven.api.Node Node}{@code >},

    // merged into POM being built. Once the POM builder has this plugin information, versions can be assigned
    // by the POM builder because they will have to be defined in plugin management. Once this is setComplete then it
    // can be passed back so that the default configuration information can be populated.
    //
    // We need to know the specific version so that we can look up the right version of the plugin descriptor

``MinIO`` community welcomes your contribution. To make the process as seamless as possible, we recommend you read this contribution guide.

## Development Workflow

Start by forking the MinIO GitHub repository, make changes in a branch and then send a pull request. We encourage pull requests to discuss code changes. Here are the steps in details:

### Setup your MinIO GitHub Repository

    exec.execute(task);
    runLatch.await();
    assertEquals(1, listenerLatch.getCount());
    assertFalse(task.isDone());
    assertFalse(task.isCancelled());

    // Finish the task by unblocking the task latch.  Then wait for the
    // listener to be called by blocking on the listener latch.
    taskLatch.countDown();
    assertEquals(25, task.get().intValue());
    assertTrue(listenerLatch.await(5, SECONDS));

 *
 * This is because the ModelProcessor interface extends ModelLocator and ModelReader. If we
 * made this component available under all its interfaces then it could end up being injected
 * into itself leading to a stack overflow.
 *
 * A side effect of using @Typed is that it translates to explicit bindings in the container.