<h2>section1</h2>
text1
<h3>section 1.1</h3>
text2
<h2>section 2</h2>
text3
'''

        when:
        def result = parser.parse(classMetaData, listener)

        then:
        format(result.docbook) == '''<section><title>section1</title><para>
text1
</para><section><title>section 1.1</title><para>
text2
</para></section></section><section><title>section 2</title><para>
text3</para></section>'''

    }

    Violation acceptOrReject(JApiCompatibility member, Violation rejection) {
        List<String> changes = member.compatibilityChanges.collect { Violation.describe(it) }
        return acceptOrReject(member, changes, rejection)
    }

    Violation acceptOrReject(JApiCompatibility member, List<String> changes, Violation rejection) {
        Set<ApiChange> seenApiChanges = (Set<ApiChange>) context.userData["seenApiChanges"]

  c. You must comply with the conditions in Section 3(a) if You Share
     all or a substantial portion of the contents of the database.

For the avoidance of doubt, this Section 4 supplements and does not
replace Your obligations under this Public License where the Licensed
Rights include other Copyright and Similar Rights.


Section 5 -- Disclaimer of Warranties and Limitation of Liability.

    test to timeout but it could be useful when you need to execute a single
    test or more in general your filtered/selected tests have a very low
    execution time and the sharding
    [could create an overhead on the test execution](https://github.com/bazelbuild/bazel/issues/2113#issuecomment-264054799).

2.  Using [Docker](https://www.docker.com) and TensorFlow's CI scripts.

    ```bash

            }
            return exitValue;
        } catch (final CrawlerSystemException e) {
            throw e;
        } catch (final InterruptedException e) {
            if (mt != null && mt.isTeminated()) {
                throw new CommandExecutionException("The command execution is timeout: " + String.join(" ", commands), e);

                                                  int keep_alive_secs) = 0;

  // Set up a multi-client distributed execution environment. Must be called
  // on all tasks in the cluster. This call internally coordinates with other
  // tasks to initialize the eager context and TF server for multi-client
  // execution.
  virtual absl::Status EnableCollectiveOps(const ServerDef& server_def) = 0;

  // Check if the remote task is alive.

es.io/whitelist-source-range: 0.0.0.0/0 path: / hosts: - console.minio-example.local tls: [] # - secretName: chart-example-tls # hosts: # - chart-example.local ## Node labels for pod assignment ## Ref: https://kubernetes.io/docs/user-guide/node-selection/ ## nodeSelector: {} tolerations: [] affinity: {} topologySpreadConstr: [] ## Add stateful containers to have security context, if enabled MinIO will run as this ## user and group NOTE: securityContext is only enabled if persistence.enabled=true...

es.io/whitelist-source-range: 0.0.0.0/0 path: / hosts: - console.minio-example.local tls: [] # - secretName: chart-example-tls # hosts: # - chart-example.local ## Node labels for pod assignment ## Ref: https://kubernetes.io/docs/user-guide/node-selection/ ## nodeSelector: {} tolerations: [] affinity: {} topologySpreadConstr: [] ## Add stateful containers to have security context, if enabled MinIO will run as this ## user and group NOTE: securityContext is only enabled if persistence.enabled=true...

}

#result .title {
	margin: 1.0em 0 0.5em 0;
	font-size: 120%;
	font-weight: 600;
}

section.content table {
	display: table;
	table-layout: fixed;
	width
}

section.content table td {
	display: table-cell;
	word-wrap: break-word;
	overflow-wrap: break-word;
}

section.content table .label {
	color: #fff;
}

textarea.systemInfoData {
	height: 22em;
	line-height: 1.5em;
}

namespace tensorflow {

// Represents the results of the execution of an operation.
struct OutputList {
  std::vector<AbstractTensorHandle*> outputs;
  int expected_num_outputs = -1;
};

namespace tracing {

// =============================================================================
// Implementation detail for the unified execution APIs for Eager and tracing
// backends (graph/MLIR).
//