//
// SSE-S3 can use either a master key or a KMS as root-of-trust.
// The en/decryption slightly depens upon which root-of-trust is used.
//
// ### SSE-S3 and single master key
//
// The master key is used to derive unique object- and key-encryption-keys.
// SSE-S3 with a single master key works as SSE-C where the master key is
// used as the client-provided key.
//
//  1. Encrypt:

	return Token{ScanToken: token, text: text}
}

func (l Token) String() string {
	return l.text
}

// A Macro represents the definition of a #defined macro.
type Macro struct {
	name   string   // The #define name.
	args   []string // Formal arguments.
	tokens []Token  // Body of macro.
}

// Tokenize turns a string into a list of Tokens; used to parse the -D flag and in tests.
func Tokenize(str string) []Token {

limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_C_EAGER_C_API_UNIFIED_EXPERIMENTAL_INTERNAL_H_
#define TENSORFLOW_C_EAGER_C_API_UNIFIED_EXPERIMENTAL_INTERNAL_H_

#include <vector>

#include "tensorflow/c/c_api.h"
#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/abstract_context.h"

---

If you just don't know, use normal `def`.

---

**Note**: You can mix `def` and `async def` in your *path operation functions* as much as you need and define each one using the best option for you. FastAPI will do the right thing with them.

Anyway, in any of the cases above, FastAPI will still work asynchronously and be extremely fast.

/// warning

Notice that these parameters are passed directly to the *path operation decorator*, not to your *path operation function*.

///

## Response Status Code

You can define the (HTTP) `status_code` to be used in the response of your *path operation*.

You can pass directly the `int` code, like `404`.

* **Cloud services** that handle this for you
    * The cloud service will probably **handle replication for you**. It would possibly let you define **a process to run**, or a **container image** to use, in any case, it would most probably be **a single Uvicorn process**, and the cloud service would be in charge of replicating it.

/// tip

limitations under the License.
==============================================================================*/

#ifndef TENSORFLOW_C_EAGER_GRADIENTS_INTERNAL_H_
#define TENSORFLOW_C_EAGER_GRADIENTS_INTERNAL_H_

#include "tensorflow/c/eager/gradients.h"

namespace tensorflow {
namespace gradients {
namespace internal {

 * high contention, expected throughput of this class is significantly higher, at the expense of
 * higher space consumption.
 *
 * <p>This class extends {@link Number}, but does not define methods such as {@code
 * equals}, {@code hashCode} and {@code compareTo} because instances are expected to be mutated, and
 * so are not useful as collection keys.
 *

  // driver can be mounted separately with different `-o context` options. This is
  // typical for storage backends that provide volumes as filesystems on block
  // devices or as independent shared volumes.
  // Kubernetes will call NodeStage / NodePublish with "-o context=xyz" mount
  // option when mounting a ReadWriteOncePod volume used in Pod that has

     * a given entry might not include null. The right fix for the header problems is probably to
     * define a separate MultimapLink interface with a separate "header" implementation, which
     * hopefully could avoid implementing Entry or ValueSetLink at all. (But note that that approach
     * requires us to define extra classes -- unfortunate under Android.) *Then* we could consider