quarkus/extensions/resteasy-classic/rest-client-jsonb/runtime/pom.xml
	quarkus/extensions/resteasy-classic/rest-client/runtime/pom.xml
	quarkus/extensions/jsonb/runtime/pom.xml
quarkus/extensions/jaeger/deployment/pom.xml
	quarkus/core/deployment/pom.xml
	quarkus/extensions/jaeger/runtime/pom.xml
	quarkus/test-framework/junit5-internal/pom.xml
	quarkus/extensions/arc/deployment/pom.xml
	quarkus/extensions/smallrye-metrics/deployment/pom.xml

  virtual absl::Status SummarizeValue(std::string& summary) const;

  // For LLVM style RTTI.
  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kEager || ptr->getKind() == kTfrt;
  }

 protected:
  explicit ImmediateExecutionTensorHandle(AbstractTensorHandleKind kind)
      : AbstractTensorHandle(kind) {}
  ~ImmediateExecutionTensorHandle() override {}
};

// This interface allows building and executing an operation in either
// tracing or immediate execution mode.
class AbstractOperation {
 protected:
  enum AbstractOperationKind {
    kGraph,
    kMlir,
    kEager,
    kTfrt,
    kTape,
    kOpHandler
  };
  explicit AbstractOperation(AbstractOperationKind kind) : kind_(kind) {}
  virtual ~AbstractOperation() {}

 public:

    byte[] key = fillByteArray(80, 0xaa);
    String data = "Test Using Larger Than Block-Size Key - Hash Key First";

    checkSha1("aa4ae5e15272d00e95705637ce8a3b55ed402112", key, data);
  }

  public void testRfc2202_hmacSha1_case7() {
    byte[] key = fillByteArray(80, 0xaa);
    String data = "Test Using Larger Than Block-Size Key and Larger Than One Block-Size Data";

#ifndef TENSORFLOW_C_EAGER_GRADIENTS_H_
#define TENSORFLOW_C_EAGER_GRADIENTS_H_

#include "absl/container/flat_hash_map.h"
#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/tape.h"
#include "tensorflow/core/common_runtime/eager/attr_builder.h"

namespace tensorflow {
namespace gradients {

Türü yol olmayan bir parametre (şu ana kadar sadece sorgu parametrelerini gördük) için varsayılan değer tanımlarsanız o parametre zorunlu olmayacaktır.

Parametre için belirli bir değer atamak istemeyip parametrenin sadece isteğe bağlı olmasını istiyorsanız değerini `None` olarak atayabilirsiniz.

Fakat, bir sorgu parametresini zorunlu yapmak istiyorsanız varsayılan bir değer atamamanız yeterli olacaktır:

```Python hl_lines="6-7"

#ifndef TENSORFLOW_C_EAGER_GRADIENT_CHECKER_H_
#define TENSORFLOW_C_EAGER_GRADIENT_CHECKER_H_

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/unified_api_testutil.h"

namespace tensorflow {
namespace gradients {

/* Returns numerical grad inside `dtheta_approx` given `forward` model and
 * parameter specified by `input_index`.

func (r *Reader) ActualSize() int64 { return r.actualSize }

// ETag returns the ETag computed by an underlying etag.Tagger.
// If the underlying io.Reader does not implement etag.Tagger
// it returns nil.
func (r *Reader) ETag() etag.ETag {
	if t, ok := r.src.(etag.Tagger); ok {
		return t.ETag()
	}
	return nil
}

// MD5Current returns the MD5 checksum of the content

#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/immediate_execution_operation.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"
#include "tensorflow/c/eager/tfe_context_internal.h"
#include "tensorflow/c/eager/tfe_op_internal.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/c/tf_status.h"

#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"
#include "tensorflow/c/tf_status_internal.h"
#include "tensorflow/core/common_runtime/eager/tensor_handle.h"
#include "tensorflow/core/framework/tensor.h"