"org/gradle/swiftpm/**",
        "org/gradle/model/**",
        "org/gradle/testkit/**",
        "org/gradle/testing/**",
        "org/gradle/vcs/**",
        "org/gradle/work/**",
        "org/gradle/workers/**",
        "org/gradle/util/**", // contains Path that clashes with `org.gradle.api.model.Path` imported above. This line should not appear before "org/gradle/api/**"
    )

    val excludes = listOf("**/internal/**")

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Mit Trio ausführen

Dann können Sie die Befehlszeilenoption `--worker-class` mit dem Wert `trio` übergeben:

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

Und das startet Hypercorn mit Ihrer Anwendung und verwendet Trio als Backend.

      TF_NewStatus(), TF_DeleteStatus);
  std::unique_ptr<TFE_Context, decltype(&TFE_DeleteContext)> context(
      TFE_NewContext(opts.get(), status.get()), TFE_DeleteContext);
  tensorflow::ServerDef server_def = GetServerDef("worker", 3);

  // This server def has the task index set to 0.
  std::string serialized = server_def.SerializeAsString();

  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package gradlebuild.incubation.action

import org.gradle.workers.WorkAction


abstract class IncubatingApiReportAggregationWorkAction : WorkAction<IncubatingApiReportAggregationParameter> {
    override fun execute() {
        val byCategory = mutableMapOf<String, ReportNameToProblems>()

    listOf(
        // We pass the 'maxParallelForks' setting as 'workers.max' to limit the maximum number of executers even
        // if multiple test tasks run in parallel. We also pass it to the Gradle build as a maximum (maxParallelForks)
        // for each test task, such that we are independent of whatever default value is defined in the build itself.
        "-Dorg.gradle.workers.max=$maxParallelForks",
        "-PmaxParallelForks=$maxParallelForks",

        val expectedInstallationPaths = if (os == Os.WINDOWS) windowsPaths else linuxPaths

import org.gradle.api.tasks.Nested;
import org.gradle.api.tasks.Optional;
import org.gradle.api.tasks.OutputFile;
import org.gradle.api.tasks.TaskAction;
import org.gradle.util.GradleVersion;
import org.gradle.workers.WorkQueue;
import org.gradle.workers.WorkerExecutor;

import javax.inject.Inject;
import java.io.File;
import java.net.URISyntaxException;
import java.security.CodeSource;
import java.security.ProtectionDomain;

  };

  tensorflow::mutex execution_mutex_;
  ExecutionState execution_state_ TF_GUARDED_BY(execution_mutex_) =
      ExecutionState::kIdle;
  // Tells the worker thread that there is new work.
  tensorflow::condition_variable start_execute_;
  // The worker thread notifies that work has finished.
  tensorflow::condition_variable finished_execute_;
  // Notifies a StartExecute that the previous Join has finished.

<div class="termy">

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Run with Trio

然后你可以传递值`trio`给命令行选项`--worker-class`:

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

这将通过您的应用程序启动 Hypercorn，并使用 Trio 作为后端。

现在您可以在应用程序内部使用 Trio。 或者更好的是，您可以使用 AnyIO，使您的代码与 Trio 和 asyncio 兼容。 🎉

## 部署概念

// Return a shape op fetching the shape of `a`.
TFE_Op* ShapeOp(TFE_Context* ctx, TFE_TensorHandle* a);

// Return an allreduce op adding up input tensor `in` from `group_size` workers.
TFE_Op* AllReduceOp(TFE_Context* ctx, TFE_TensorHandle* in, int group_size);

// Return a SendOp op `op_name` with send input tensor `in` and attributes
// `send_device`, `recv_device`, and `send_device_incarnation` set.