// placed on each underlying device.
class ParallelDevice {
 public:
  // Eager async execution is only supported when remote eager is not in use
  // (b/157523095).
  explicit ParallelDevice(const std::vector<std::string>& devices,
                          bool is_async = false, int in_flight_nodes_limit = 0);

  ~ParallelDevice();

                        const int in_flight_nodes_limit)
      : status_(TF_NewStatus()),
        // If the context's default exector is set to async, re-using that in
        // each thread would cause collectives to deadlock. For consistency we
        // create a new sync executor for every thread.
        //
        // TODO(allenl): We should have an async API that works with the

  TFE_Execute(op, out_value, &num_retvals, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteOp(op);
  TF_DeleteStatus(status);
}

void TestRemoteExecuteChangeServerDef(bool async) {
  tensorflow::ServerDef server_def = GetServerDef(2);

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

  server_def.set_task_index(1);

// TODO(b/154564140): Move this to its own header. This requires splitting
// c_api_experimental.h
struct TFE_ContextOptions {
  TF_SessionOptions session_options;
  // true if async execution is enabled.
  bool async = false;
  TFE_ContextDevicePlacementPolicy device_placement_policy{
      TFE_DEVICE_PLACEMENT_SILENT};
  // If true, use TFRT backend
  bool use_tfrt = false;

#include "xla/pjrt/pjrt_client.h"
#include "tensorflow/core/framework/resource_mgr.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/tfrt/common/async_value_tensor.h"
#include "tensorflow/core/tfrt/common/global_state.h"
#include "tensorflow/core/tfrt/common/pjrt_state.h"
#include "tensorflow/core/tfrt/common/pjrt_util.h"
#include "tsl/platform/errors.h"

    username has the login username of the Pull Request Event
  @return {string} Return the domain name of the user's email. Empty string if not found
*/

const get_email_domain = async ({github, username}) => {
  const user = await github.rest.users.getByUsername({
    username
  });
  if (user.status >= 400) {
    console.log(user);
    throw `Error Getting user data for ${username}`;
  }

    visibility = ["//visibility:public"],
    deps = [
        "//tensorflow/compiler/jit:pjrt_tensor_buffer_util",
        "//tensorflow/core:framework",
        "//tensorflow/core/tfrt/common:async_value_tensor",
        "//tensorflow/core/tfrt/common:global_state",
        "//tensorflow/core/tfrt/common:pjrt_state",
        "//tensorflow/core/tfrt/common:pjrt_util",
        "@com_google_absl//absl/status",

}

// Note: this function looks up a thread local policy. So it should be called in
// the appropriate client thread. In particular, in async mode, it may not be
// safe to call this function from the async EagerExecutor threads.
extern TFE_ContextDevicePlacementPolicy TFE_ContextGetDevicePlacementPolicy(
    TFE_Context* ctx) {
  return static_cast<TFE_ContextDevicePlacementPolicy>(

      tensorflow::unwrap(cancellation_manager));
  status->status = absl::OkStatus();
}

TFE_Executor* TFE_NewExecutor(bool is_async, bool enable_streaming_enqueue,
                              int in_flight_nodes_limit) {
  return new TFE_Executor(is_async, enable_streaming_enqueue,
                          in_flight_nodes_limit);
}

void TFE_DeleteExecutor(TFE_Executor* executor) { delete executor; }

  ops_->flush(file_.get(), plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

Status ModularWritableFile::Sync() {
  if (ops_->sync == nullptr) return Flush();

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  ops_->sync(file_.get(), plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}