setError(ImportErrorf(p.ImportPath, "invalid import path %q", p.ImportPath))
		return
	}

	// Errors after this point are caused by this package, not the importing
	// package. Pushing the path here prevents us from reporting the error
	// with the position of the import declaration.
	stk.Push(path)
	defer stk.Pop()

	pkgPath := p.ImportPath
	if p.Internal.CmdlineFiles {

        function_name_uniquifier_(function_name_uniquifier),
        error_handler_(module.getContext()) {
    // Log import config.
    if (VLOG_IS_ON(1)) {
      LOG(INFO) << "Importing with: " << specs.str();
      for (auto& it : *tf_name_to_mlir_name) {
        LOG(INFO) << "\t" << it.first << " -> " << it.second;
      }
    }

    stack_traces_ = LoadTracesFromDebugInfo(debug_info_);
  }

ImportPath       = string_lit .
</pre>

<p>
The PackageName is used in <a href="#Qualified_identifiers">qualified identifiers</a>
to access exported identifiers of the package within the importing source file.
It is declared in the <a href="#Blocks">file block</a>.
If the PackageName is omitted, it defaults to the identifier specified in the
<a href="#Package_clause">package clause</a> of the imported package.

    data_gen = self._create_data_generator(
        input_key='input', shape=input_placeholder.shape
    )

    # StatusNotOk error. `Exception` is used here because importing
    # `StatusNotOk` may break the open-sourced version of TensorFlow.
    with self.assertRaisesRegex(
        Exception,
        'could not be found in SavedModel, with available tags',
    ) as raises:

		return err
	}

	importcfg := a.Objdir + "importcfg.link"
	if err := b.writeLinkImportcfg(a, importcfg); err != nil {
		return err
	}

	// TODO(rsc): There is a missing updateBuildID here,
	// but we have to decide where to store the build ID in these files.
	a.built = a.Target
	return BuildToolchain.ldShared(b, a, a.Deps[0].Deps, a.Target, importcfg, a.Deps)
}

          <description>The group ID of the reporting plugin in the repository.</description>
        </field>
        <field>
          <name>artifactId</name>
          <version>4.0.0+</version>
          <type>String</type>
          <required>true</required>
          <description>The artifact ID of the reporting plugin in the repository.</description>
        </field>
        <field>

			t.Errorf("Admit pod: %v, expected: %v, actual: %v", pod, expected[i], result.Admit)
		}
	}

	// move the clock past transition period to ensure that we stop reporting pressure
	fakeClock.Step(5 * time.Minute)
	summaryProvider.result = summaryStatsMaker("2Gi", podStats)
	podKiller.pod = nil // reset state
	_, err = manager.synchronize(diskInfoProvider, activePodsFunc)

  status->status = tensorflow::errors::Unimplemented(
      "Creating while loops is not supported on mobile. File a bug at "
      "https://github.com/tensorflow/tensorflow/issues if this feature is "
      "important to you");
  return EmptyWhileParams();
#else
  if (ninputs == 0) {
    status->status =
        InvalidArgument("TF_NewWhile() must be passed at least one input");
    return EmptyWhileParams();
  }

	// doesn't free mp while we are still using it.
	//
	// Note that the free list must not be linked through alllink because
	// some functions walk allm without locking, so may be using alllink.
	//
	// N.B. It's important that the M appears on the free list simultaneously
	// with it being removed so that the tracer can find it.
	mp.freeWait.Store(freeMWait)
	mp.freelink = sched.freem
	sched.freem = mp
	unlock(&sched.lock)

		Deadline() (time.Time, bool)
	}
	if td, ok := t.(deadliner); ok {
		if deadline, ok := td.Deadline(); ok {
			timeout = time.Until(deadline)
			timeout = timeout * 19 / 20 // Give 5% headroom for cleanup and error-reporting.
		}
	}

	deadline := time.Now().Add(timeout)
	for {
		if fn() {
			return true
		}
		if time.Until(deadline) < pollDuration {
			return false
		}
		time.Sleep(pollDuration)
	}