#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/tstring.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

// Return a tensor handle containing a float scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value);

* <a href="https://docs.pydantic.dev/latest/usage/types/extra_types/extra_types/" target="_blank"><code>pydantic-extra-types</code></a> - for extra types to be used with Pydantic.

Additional optional FastAPI dependencies:

  /**
   * Sets the default value for {@code type}, when dummy value for a parameter of the same type
   * needs to be created in order to invoke a method or constructor. The default value isn't used in
   * testing {@link Object#equals} because more than one sample instances are needed for testing
   * inequality.
   */
  protected final <T> void setDefault(Class<T> type, T value) {
    tester.setDefault(type, value);
  }

  /**

import javax.annotation.CheckForNull;

/**
 * An implementation of {@link GraphConnections} for directed graphs.
 *
 * @author James Sexton
 * @author Jens Nyman
 * @param <N> Node parameter type
 * @param <V> Value parameter type
 */
@ElementTypesAreNonnullByDefault
final class DirectedGraphConnections<N, V> implements GraphConnections<N, V> {
  /**

* <a href="https://docs.pydantic.dev/latest/usage/types/extra_types/extra_types/" target="_blank"><code>pydantic-extra-types</code></a> - for extra types to be used with Pydantic.

Additional optional FastAPI dependencies:

 * of {@code Comparator} for pre-Java-8 users, in the same sense that {@link FluentIterable} is an
 * enriched {@link Iterable} for pre-Java-8 users.
 *
 * <h3>Three types of methods</h3>
 *
 * Like other fluent types, there are three types of methods present: methods for <i>acquiring</i>,
 * <i>chaining</i>, and <i>using</i>.
 *
 * <h4>Acquiring</h4>
 *
 * <p>The common ways to get an instance of {@code Ordering} are:

        return error  # type: ignore[return-value]

    def create_body_model(
        *, fields: Sequence[ModelField], model_name: str
    ) -> Type[BaseModel]:
        field_params = {f.name: (f.field_info.annotation, f.field_info) for f in fields}
        BodyModel: Type[BaseModel] = create_model(model_name, **field_params)  # type: ignore[call-overload]
        return BodyModel

 *
 * <p>The Invoker is designed to be flexible, allowing for different implementations
 * that can handle various types of {@link InvokerRequest InvokerRequests}. It also implements
 * {@link AutoCloseable} to ensure proper resource management.</p>
 *
 * @param <R> The specific type of {@link InvokerRequest} this {@code Invoker} can handle, extending {@link InvokerRequest}
 *
 * @since 4.0.0
 */
@Experimental

    }
    val type = source.readByte() and 0xff
    val flags = source.readByte() and 0xff
    val streamId = source.readInt() and 0x7fffffff // Ignore reserved bit.
    if (type != TYPE_WINDOW_UPDATE && logger.isLoggable(FINE)) {
      logger.fine(frameLog(true, streamId, length, type, flags))
    }

    if (requireSettings && type != TYPE_SETTINGS) {

type BucketRemoteIdenticalToSource struct {
	GenericError
	Endpoint string
}

func (e BucketRemoteIdenticalToSource) Error() string {
	return fmt.Sprintf("Remote service endpoint %s is self referential to current cluster", e.Endpoint)
}

// BucketRemoteAlreadyExists remote already exists for this target type.
type BucketRemoteAlreadyExists GenericError