pushd "${TFCI_OUTPUT_DIR}"

# Unpack the wheel to get all the file contents. The pure python wheel we built
# above is tagged with "py3-none-any". We cannot change the tags by simply
# renaming the wheels as uploading to PyPI would fail with "File already exists"
# error. In order to upload to PyPI, we unpack the wheel and change the tag

      <plugin>
        <groupId>org.apache.maven.plugins</groupId>
        <artifactId>maven-dependency-plugin</artifactId>
        <executions>
          <execution>
            <id>unpack-jline-native</id>
            <goals>
              <goal>unpack-dependencies</goal>
            </goals>
            <configuration>
              <includeArtifactIds>jline-native</includeArtifactIds>

				</configuration>
			</plugin>
			<plugin>
				<artifactId>maven-dependency-plugin</artifactId>
				<executions>
					<execution>
						<id>unpack-provided</id>
						<phase>generate-resources</phase>
						<goals>
							<goal>unpack-dependencies</goal>
						</goals>
						<configuration>
							<includeScope>provided</includeScope>

* installation
* activation
* update
* deactivation
* un-installation

When a plugin is installed we may want to check the license and make users agree. We may also want to unpack the given plugin in a particular location.

        }

        iterator = topMetaIterator.next();

        if (iterator instanceof ConcatenatedIterator) {
          // Instead of taking linear time in the number of nested concatenations, unpack
          // them into the queue
          @SuppressWarnings("unchecked")
          ConcatenatedIterator<T> topConcat = (ConcatenatedIterator<T>) iterator;
          iterator = topConcat.iterator;

            "names (",
            n->name(),
            "). This is a bug. Please file an issue at "
            "https://github.com/tensorflow/tensorflow/issues.");
      }
    }
  }

  // Unpack the results from grad_outputs_arg.
  TFOutputsFromOutputs(dy_arg, dy);
#endif  // defined(IS_MOBILE_PLATFORM) || defined(IS_SLIM_BUILD)
}

// TF_Session functions ----------------------------------------------

limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/dlpack.h"

#include <string>

#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"

are deprecated in favor of `tf.multiply`, `tf.subtract` and `tf.negative`. *
`tf.pack` and `tf.unpack` are deprecated in favor of `tf.stack` and
`tf.unstack`. * `TensorArray.pack` and `TensorArray.unpack` are getting
deprecated in favor of `TensorArray.stack` and `TensorArray.unstack`. * The
following Python functions have had their arguments changed to use `axis` when

	dm.Unlock(context.Background())
}

func TestSimpleLockUnlockMultipleTimes(t *testing.T) {
	dm := NewDRWMutex(ds, "test")

	dm.Lock(id, source)
	time.Sleep(time.Duration(10+(rand.Float32()*50)) * time.Millisecond)
	dm.Unlock(context.Background())

	dm.Lock(id, source)
	time.Sleep(time.Duration(10+(rand.Float32()*50)) * time.Millisecond)
	dm.Unlock(context.Background())

	dm.Lock(id, source)

			delete(n.lockMap, resource)
		}
		n.lockMapMutex.Unlock()
	}

	return
}

// Unlock the namespace resource.
func (n *nsLockMap) unlock(volume string, path string, readLock bool) {
	resource := pathJoin(volume, path)

	n.lockMapMutex.Lock()
	defer n.lockMapMutex.Unlock()
	if _, found := n.lockMap[resource]; !found {
		return
	}
	if readLock {