}

    /**
     * The base directory for all reports
     * <p>
     * This value can be changed, so any files derived from this should be calculated on demand.
     *
     * @return The base directory for all reports
     */
    public File getBaseDir() {
        return baseDirectory.getAsFile().get();
    }

    /**

	case AFMADDQ:
		return &inst{0x43, 0x0, 0x0, 96, 0x3}
	case AFMADDS:
		return &inst{0x43, 0x0, 0x0, 0, 0x0}
	case AFMAXD:
		return &inst{0x53, 0x1, 0x0, 672, 0x15}
	case AFMAXQ:
		return &inst{0x53, 0x1, 0x0, 736, 0x17}
	case AFMAXS:
		return &inst{0x53, 0x1, 0x0, 640, 0x14}
	case AFMIND:
		return &inst{0x53, 0x0, 0x0, 672, 0x15}
	case AFMINQ:
		return &inst{0x53, 0x0, 0x0, 736, 0x17}
	case AFMINS:

    attribute, that attribute will be overwritten with the `tf_device.launch`
    device.

    For example:

    ```mlir
      %island:5 = tf_executor.island {
        %a = "tf.opA"() : () -> tensor<i1>
        %launch:2 = "tf_device.launch"() ( {
          %b = "tf.opB"() : () -> tensor<i32>
          %c = "tf.opC"() : () -> tensor<f32>

Sie können mehrere Pfad-Parameter und Query-Parameter gleichzeitig deklarieren, **FastAPI** weiß, was welches ist.

Und Sie müssen sie auch nicht in einer spezifischen Reihenfolge deklarieren.

Parameter werden anhand ihres Namens erkannt:

=== "Python 3.10+"

    ```Python hl_lines="6  8"
    {!> ../../../docs_src/query_params/tutorial004_py310.py!}
    ```

=== "Python 3.8+"

    ```Python hl_lines="8  10"

     *
     * <p>The closures will be “evaluated” on demand whenever the value is needed (e.g. at generation time)</p>
     *
     * @param toSign A closure that produces a File for the object to sign (non File return values will be used as the path to the file)
     * @param classifier A closure that produces the classifier to assign to the signature artifact on demand

// These resources cannot be looked up on-demand.
//
// In some cases, we do not know the IP address of a Service. These services cannot be used for matching
// outbound traffic, as we only have L4 attributes to route based on. However,
// they can be used for Gateways.
// In this case, the key format will be "network/hostname".
// These resources cannot be looked up on-demand.
message Address {
  oneof type {

    absl::Span<Predicate* const> operands, bool is_and) {
  Predicate::Kind pred_kind =
      is_and ? Predicate::Kind::kAnd : Predicate::Kind::kOr;

  IncrementStackDepth stack_frame(this);
  if (stack_frame.HasOverflowed()) {
    return MakeInternedAndOr(
        std::vector<Predicate*>(operands.begin(), operands.end()), pred_kind);
  }

  Predicate::Kind other_pred_kind =
      is_and ? Predicate::Kind::kOr : Predicate::Kind::kAnd;

/**
 * A utility similar to {@link IteratorTester} for testing a {@link ListIterator} against a known
 * good reference implementation. As with {@code IteratorTester}, a concrete subclass must provide
 * target iterators on demand. It also requires three additional constructor parameters: {@code
 * elementsToInsert}, the elements to be passed to {@code set()} and {@code add()} calls; {@code

        1 * cacheBuilder.withInitialLockMode(FileLockManager.LockMode.OnDemand) >> cacheBuilder
        1 * cacheBuilder.open() >> { cache }
        1 * cache.close()
    }

    def "creates JAR file on demand for identifier '#identifier'"(String identifier) {
        def cacheDir = tmpDir.testDirectory
        def jarFile = cacheDir.file("gradle-${identifier}-${gradleVersion}.jar")
        def cacheBuilder = Mock(CacheBuilder)

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/passes.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/error_util.h"

#define DEBUG_TYPE "tf-executor-tpu-v1-island-inlining"

namespace mlir {
namespace tf_executor {

namespace {
constexpr llvm::StringRef kNestedModule = "_tpu_v1_compat_outlined";

#define GEN_PASS_DEF_EXECUTORTPUV1ISLANDINLININGPASS