root = null;
            dependencies = project.getDependencies();
            managedDependencies = project.getManagedDependencies();
            remoteRepositories = session.getService(ProjectManager.class).getRemoteProjectRepositories(project);
        } else {
            rootArtifact = request.getRootArtifact().orElse(null);
            root = request.getRoot().orElse(null);

            root = null;
            dependencies = project.getDependencies();
            managedDependencies = project.getManagedDependencies();
            remoteRepositories = session.getService(ProjectManager.class).getRemoteProjectRepositories(project);
        } else {
            rootArtifact = request.getRootArtifact().orElse(null);
            root = request.getRoot().orElse(null);

        for (Repository r : model.getRepositories()) {
            result.addRepository(session.toRepository(
                    session.getService(RepositoryFactory.class).createRemote(r)));
        }

        for (org.apache.maven.api.model.Dependency dependency : model.getDependencies()) {
            result.addDependency(convert(dependency, stereotypes));
        }

        Project project = sessionV4.getProject(session.getCurrentProject());

        List<org.apache.maven.api.RemoteRepository> repos =
                sessionV4.getService(ProjectManager.class).getRemoteProjectRepositories(project);
        sessionV4 = InternalMavenSession.from(sessionV4.withRemoteRepositories(repos));

// Currently we only allow `NextPluggableDevice` to be casted as `TF_Device`,
// but in theory every this is a C API for every kind of device.
TF_CAPI_EXPORT extern TF_Device* TF_GetDevice(TF_OpKernelContext* ctx);

// --------------------------  Resource  ---------------------------------------
// Create a `tensorflow::PluginResource` to the ResourceMgr provided by the

#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/tfrt/common/pjrt_util.h"
#include "tsl/distributed_runtime/coordination/coordination_service_agent.h"

TF_Device* TF_GetDevice(TF_OpKernelContext* ctx) {
  auto* cc_ctx = reinterpret_cast<tensorflow::OpKernelContext*>(ctx);
  return reinterpret_cast<TF_Device*>(cc_ctx->device());
}