"The network name cannot be found.",
        "Not enough storage is available to process this command.",
        "The media is write protected.",
        "The device is not ready.",
        "A device attached to the system is not functioning.",
        "A device attached to the system is not functioning.",
        "The process cannot access the file because it is being used by another process.",

#endif
  } else {
    status->status = tensorflow::errors::InvalidArgument(
        "Unsupported Device Type for dlpack");
  }

  return ctx;
}

// Converts DLDevice to TF device name.
absl::optional<std::string> DeviceNameFromDlContext(const DLDevice& ctx,
                                                    TF_Status* status) {
  switch (ctx.device_type) {
    case DLDeviceType::kDLCPU:

    TF_ImportGraphDefOptions* opts, const char* prefix);

// Set the execution device for nodes in `graph_def`.
// Only applies to nodes where a device was not already explicitly specified.
// `device` is copied and has no lifetime requirements.
TF_CAPI_EXPORT extern void TF_ImportGraphDefOptionsSetDefaultDevice(
    TF_ImportGraphDefOptions* opts, const char* device);

// Set whether to uniquify imported operation names. If true, imported operation

        return item

    @app.get("/items/")
    def read_items() -> List[Item]:
        return [
            Item(
                name="Portal Gun",
                description="Device to travel through the multi-rick-verse",
                sub=SubItem(subname="subname"),
            ),
            Item(name="Plumbus"),
        ]

    client = TestClient(app)
    return client

	if err := syscall.Flock(int(lock.Fd()), syscall.LOCK_EX); err != nil {
		return 0, err
	}

	// In case we're booting a device or emulator alongside all.bash, wait for
	// it to be ready. adb wait-for-device is not enough, we have to
	// wait for sys.boot_completed.
	if err := adb("wait-for-device", "exec-out", "while [[ -z $(getprop sys.boot_completed) ]]; do sleep 1; done;"); err != nil {
		return 0, err
	}

    TF_LOCKS_EXCLUDED(session->graph->mu, session->mu);

std::string getTF_OutputDebugString(TF_Output node);

// Set whether to propagate assigned device information when constructing a new
// Graph from a GraphDef. By default assigned device information is not copied
// and is re-computed by the runtime.
inline void TF_ImportGraphDefOptionsSetPropagateDeviceSpec(

   * href="https://iabtechlab.com/wp-content/uploads/2019/06/VAST_4.2_final_june26.pdf">{@code
   * X-Device-IP}</a> header field name. Header used for VAST requests to provide the IP address of
   * the device on whose behalf the request is being made.
   *
   * @since 31.0
   */
  public static final String X_DEVICE_IP = "X-Device-IP";
  /**
   * The HTTP <a

    }
    auto tag = tensorflow::strings::StrCat("Device #", i, " (", name, ")");
    // Copy to device
    TFE_TensorHandle* hdevice =
        TFE_TensorHandleCopyToDevice(hcpu, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }
    // Copy from device to the same device.
    TFE_TensorHandle* hdevice2 =

@app.post("/items/")
def create_item(item: Item):
    return item


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),

@app.post("/items/")
def create_item(item: Item):
    return item


@app.get("/items/")
def read_items() -> list[Item]:
    return [
        Item(
            name="Portal Gun",
            description="Device to travel through the multi-rick-verse",
        ),
        Item(name="Plumbus"),