inline semantics, unless -fgnu89-inline is used.  */
-#if (!defined __cplusplus || __GNUC_PREREQ (4,3)) && defined __GNUC__
+#if (!defined __cplusplus || __GNUC_PREREQ (4,3) || defined __clang__) && defined __GNUC__
 # if defined __GNUC_STDC_INLINE__ || defined __cplusplus
 #  define __extern_inline extern __inline __attribute__ ((__gnu_inline__))

		return true
	}
	return false
}

// MCR is not defined by the obj/arm; instead we define it privately here.
// It is encoded as an MRC with a bit inside the instruction word,
// passed to arch.ARMMRCOffset.
const aMCR = arm.ALAST + 1

// IsARMMRC reports whether the op (as defined by an arm.A* constant) is
// MRC or MCR.
func IsARMMRC(op obj.As) bool {
	switch op {

        new_field.key_field = create_cloned_field(  # type: ignore[attr-defined]
            field.key_field,  # type: ignore[attr-defined]
            cloned_types=cloned_types,
        )
    new_field.validators = field.validators  # type: ignore[attr-defined]
    new_field.pre_validators = field.pre_validators  # type: ignore[attr-defined]
    new_field.post_validators = field.post_validators  # type: ignore[attr-defined]

void TF_DeleteServer(TF_Server* server) {
#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
  delete server;
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
}

void TF_RegisterLogListener(void (*listener)(const char*)) {
#if !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
  tensorflow::logging::RegisterListener(listener);
#endif  // !defined(IS_MOBILE_PLATFORM) && !defined(IS_SLIM_BUILD)
}

    # shadowing typing.Required.
    RequiredParam: Any = Ellipsis  # type: ignore[no-redef]
    from pydantic.fields import (  # type: ignore[no-redef,attr-defined]
        Undefined as Undefined,
    )
    from pydantic.fields import (  # type: ignore[no-redef, attr-defined]
        UndefinedType as UndefinedType,  # noqa: F401
    )
    from pydantic.schema import (
        field_schema,
        get_flat_models_from_fields,

 * This interface allows users to define and configure various toolchains
 * that can be utilized by Maven during the build process. Toolchains can
 * include compilers, interpreters, and other tools that are necessary
 * for building a project in a specific environment.</p>
 *
 * <p>Toolchains are defined in the Maven toolchains.xml file and can be

  public static final MediaType WEBM_AUDIO = createConstant(AUDIO_TYPE, "webm");

  /**
   * L16 audio, as defined by <a href="https://tools.ietf.org/html/rfc2586">RFC 2586</a>.
   *
   * @since 24.1
   */
  public static final MediaType L16_AUDIO = createConstant(AUDIO_TYPE, "l16");

  /**
   * L24 audio, as defined by <a href="https://tools.ietf.org/html/rfc3190">RFC 3190</a>.
   *
   * @since 20.0
   */

    int64_t init_timeout_in_ms, int retries, TF_Status* status,
    bool clear_existing_contexts) {
#if defined(IS_MOBILE_PLATFORM)
  status->status = tensorflow::errors::Unimplemented(
      "TFE_ContextSetServerDef not supported on mobile");
#else   // !defined(IS_MOBILE_PLATFORM)
  tensorflow::ServerDef server_def;
  if (!server_def.ParseFromArray(proto, proto_len)) {

  }

  /**
   * Returns the number of times {@link Cache} lookup methods have returned either a cached or
   * uncached value. This is defined as {@code hitCount + missCount}.
   *
   * <p><b>Note:</b> the values of the metrics are undefined in case of overflow (though it is
   * guaranteed not to throw an exception). If you require specific handling, we recommend
   * implementing your own stats collector.
   */

  }

  /**
   * Returns the number of times {@link Cache} lookup methods have returned either a cached or
   * uncached value. This is defined as {@code hitCount + missCount}.
   *
   * <p><b>Note:</b> the values of the metrics are undefined in case of overflow (though it is
   * guaranteed not to throw an exception). If you require specific handling, we recommend
   * implementing your own stats collector.
   */