@ArgumentsSource(FileSystemParamProvider::class)
  fun emptyCache(parameters: Pair<FileSystem, Boolean>) {
    setUp(parameters.first, parameters.second)
    cache.close()
    assertJournalEquals()
  }

  @ParameterizedTest
  @ArgumentsSource(FileSystemParamProvider::class)
  fun recoverFromInitializationFailure(parameters: Pair<FileSystem, Boolean>) {
    setUp(parameters.first, parameters.second)

  // users want to compute multiple gradients over the same tape.
  explicit GradientTape(bool persistent) : persistent_(persistent) {}
  ~GradientTape() {
    for (const auto& pair : op_tape_) {
      pair.second.backward_function_deleter(pair.second.backward_function);
    }
  }

  // Returns whether any tensor in a list of tensors is being watched and has
  // a trainable dtype.

import org.jetbrains.kotlin.types.expressions.OperatorConventions

internal class ReadWriteAccessCheckerFirImpl : ReadWriteAccessChecker {
    override fun readWriteAccessWithFullExpressionByResolve(assignment: KtBinaryExpression): Pair<ReferenceAccess, KtExpression>? {
        val function = assignment.operationReference.mainReference.resolve() as? KtNamedFunction ?: return null
        val name = function.name ?: return null

        return designJspFileNameMap.get(fileName);
    }

    @SuppressWarnings("unchecked")
    public Pair<String, String>[] getDesignJspFileNames() {
        return designJspFileNameMap.entrySet().stream().map(e -> new Pair<>(e.getKey(), e.getValue())).toArray(n -> new Pair[n]);
    }

    public List<Path> refreshDesignJspFiles() {
        final List<Path> fileList = new ArrayList<>();

import org.jetbrains.kotlin.types.expressions.OperatorConventions

internal class ReadWriteAccessCheckerDescriptorsImpl : ReadWriteAccessChecker {
    override fun readWriteAccessWithFullExpressionByResolve(assignment: KtBinaryExpression): Pair<ReferenceAccess, KtExpression> {
        val resolvedCall = analyze(assignment) {
            with((this as KtFe10AnalysisSession).analysisContext.analyze(assignment, Fe10AnalysisFacade.AnalysisMode.PARTIAL)) {

          <defaultValue></defaultValue>
          <identifier>true</identifier>
        </field>
        <field>
          <name>extension</name>
          <version>1.1.0+</version>
          <type>String</type>
          <description>The file extension of the sub-artifact. Each classifier and extension pair may only appear once.</description>

	export      = flag.Bool("export", false, "export xl.meta")
	djson       = flag.Bool("djson", false, "expect djson format for xl.meta")
	genkey      = flag.Bool("genkey", false, "generate key pair")
)

func main() {
	flag.Parse()

	if *genkey {
		generateKeys()
		os.Exit(0)
	}
	var privateKey []byte
	if *keyHex == "" {
		if b, err := os.ReadFile(*privKeyPath); err == nil {

  tensorflow::ImportGraphDefResults results;
  TF_RETURN_IF_ERROR(
      ImportGraphDef(opts, gdef, dst_graph, dst_refiner, &results));

  for (const auto& pair : results.return_tensors) {
    return_nodes->emplace_back(pair.first, pair.second);
  }
  return absl::OkStatus();
}

bool ValidateConstWhileParams(const TF_WhileParams& params, TF_Status* s) {

  /**
   * Returns a new equivalence relation for {@code F} which evaluates equivalence by first applying
   * {@code function} to the argument, then evaluating using {@code this}. That is, for any pair of
   * non-null objects {@code x} and {@code y}, {@code equivalence.onResultOf(function).equivalent(a,
   * b)} is true if and only if {@code equivalence.equivalent(function.apply(a), function.apply(b))}
   * is true.
   *

```Python
{**note.dict()}
```

`**note.dict()` "unpacks" the key value pairs directly, so, `{**note.dict()}` would be, more or less, a copy of `note.dict()`.

And then, we extend that copy `dict`, adding another key-value pair: `"id": last_record_id`:

```Python
{**note.dict(), "id": last_record_id}
```

So, the final result returned would be something like:

```Python
{
    "id": 1,
    "text": "Some note",