* limitations under the License.
 */

package com.google.common.collect;

import com.google.common.annotations.GwtCompatible;

/** Simple derived class to verify that we handle generics correctly. */
@GwtCompatible
class Derived extends Base {
  public Derived(String s) {
    super(s);
  }

  private static final long serialVersionUID = 0;

//
// auto* reader = TFE_MonitoringNewCounterReader("name");
// test();
// int64_t value = TFE_MonitoringReadCounter1(reader, "label-value");

// Opaque handle to a reader.
typedef struct TFE_MonitoringCounterReader TFE_MonitoringCounterReader;

// Returns a handle to be used for reading values from streamz counter. The
// counter can have been created with any number of labels.
TF_CAPI_EXPORT extern TFE_MonitoringCounterReader*

	}

	// We fake a local and remote server.
	remoteHost := remote.HostName()

	// 1: Echo
	register := func(manager *Manager) {
		errFatal(manager.RegisterStreamingHandler(handlerTest, StreamHandler{
			Handle: func(ctx context.Context, payload []byte, request <-chan []byte, resp chan<- []byte) *RemoteErr {
				for in := range request {
					b := append([]byte{}, payload...)
					b = append(b, in...)
					resp <- b
				}

// If source and destination are the same device, then this creates a new handle
// that shares the underlying buffer. Otherwise, it currently requires at least
// one of the source or destination devices to be CPU (i.e., for the source or
// destination tensor to be placed in host memory).
// If async execution is enabled, the copy may be enqueued and the call will
// return "non-ready" handle. Else, this function returns after the copy has
// been done.

        "The data was too large to fit into the specified buffer.", "A device attached to the system is not functioning.", "Incorrect function.",
        "The parameter is incorrect.", "Invalid access to memory location.", "The handle is invalid.", "The parameter is incorrect.",
        "The system cannot find the file specified.", "The system cannot find the file specified.", "End of file", "More data is available.",

## Use Case

Let's start with an example **use case** and then see how to solve it with this.

Let's imagine that you have some **machine learning models** that you want to use to handle requests. 🤖

The same models are shared among requests, so, it's not one model per request, or one per user or something similar.

Some of the options you could use as a TLS Termination Proxy are:

* Traefik (that can also handle certificate renewals)
* Caddy (that can also handle certificate renewals)
* Nginx
* HAProxy

## Let's Encrypt

Before Let's Encrypt, these **HTTPS certificates** were sold by trusted third parties.

  }
  tensorflow::EagerContext* context =
      tensorflow::ContextFromInterface(tensorflow::unwrap(ctx));
  tensorflow::TensorHandle* handle = nullptr;
  status->status = tensorflow::TensorHandle::CreatePackedHandle(
      std::move(tensor_handles), context, &handle);
  return tensorflow::wrap(handle);
}

void TFE_ContextSetSoftDevicePlacement(TFE_Context* ctx, unsigned char enable,

	opaRespBytes, err := io.ReadAll(resp.Body)
	if err != nil {
		return false, err
	}

	// Handle large OPA responses when OPA URL is of
	// form http://localhost:8181/v1/data/httpapi/authz
	type opaResultAllow struct {
		Result struct {
			Allow bool `json:"allow"`
		} `json:"result"`
	}

	// Handle simpler OPA responses when OPA URL is of
	// form http://localhost:8181/v1/data/httpapi/authz/allow

		case <-listener.ctx.Done():
			return false
		}
	}

	// Closure to handle TCPListener until done channel is closed.
	handleListener := func(idx int, listener net.Listener) {
		for {
			conn, err := listener.Accept()
			send(acceptResult{conn, err, idx})
		}
	}

	// Start separate goroutine for each TCP listener to handle connection.
	for idx, tcpListener := range listener.listeners {