// b) ConfigProto.gpu_options.allow_growth is set to `gpu_memory_allow_growth`.
// c) ConfigProto.device_count is set to `num_cpu_devices`.
TF_CAPI_EXPORT extern TF_Buffer* TF_CreateConfig(
    unsigned char enable_xla_compilation, unsigned char gpu_memory_allow_growth,
    unsigned int num_cpu_devices);

// Create a serialized tensorflow.RunOptions proto, where RunOptions.trace_level

    static final int CONSTRAINT_DELEGATIION_TYPE = 0xB;
    static final int CLIENT_UPN_TYPE = 0xC;
    static final int CLIENT_CLAIMS_TYPE = 0xD;
    static final int DEVICE_INFO_TYPE = 0xE;
    static final int DEVICE_CLAIMS_TYPE = 0xF;

    static final int LOGON_EXTRA_SIDS = 0x20;
    static final int LOGON_RESOURCE_GROUPS = 0x200;

    static final int MD5_KRB_SALT = 17;

    return ",".join(map(str, sorted(query)))


@app.get("/query/list")
def get_query_list(device_ids: List[int] = Query()) -> List[int]:
    return device_ids


@app.get("/query/list-default")
def get_query_list_default(device_ids: List[int] = Query(default=[])) -> List[int]:

    CHECK_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
    LOG(INFO) << "Device " << i << " has name " << device_name << ", type "
              << device_type;
    if (string(device_type) == DEVICE_GPU) {
      return device_name;
    }
  }
  // No GPU device found.
  return "";
}

string GPUDeviceName() {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(

@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"),

  TF_RETURN_IF_ERROR(ValidateTPOptimizerConfigs(optimizer_configs));

  CGraphOptimizerRegister(
      [=]() { return new CGraphOptimizer(optimizer, params.device_type); },
      optimizer_configs, params.device_type);

  return absl::OkStatus();
}

}  // namespace grappler
}  // namespace tensorflow

void TF_GetNodesToPreserveListSize(const TF_GrapplerItem* item, int* num_values,

#include "tensorflow/core/common_runtime/eager/context.h"
#include "tensorflow/core/common_runtime/eager/eager_operation.h"
#include "tensorflow/core/common_runtime/pluggable_device/pluggable_device_plugin_init.h"
#include "tensorflow/core/distributed_runtime/rpc/grpc_server_lib.h"
#include "tensorflow/core/framework/collective.h"
#include "tensorflow/core/framework/node_def.pb.h"

TF_Operation* Mul(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                  TF_Status* s, const char* name = "mul");

// If `op_device` is non-empty, set the created op on that device.
TF_Operation* MinWithDevice(TF_Operation* l, TF_Operation* r, TF_Graph* graph,
                            const string& op_device, TF_Status* s,
                            const char* name = "min");

TF_Operation* Neg(TF_Operation* n, TF_Graph* graph, TF_Status* s,

        "//tensorflow/core:test_main",
        "@com_google_absl//absl/strings",
    ],
)

cc_library(
    name = "custom_device_testutil",
    testonly = True,
    srcs = ["custom_device_testutil.cc"],
    hdrs = ["custom_device_testutil.h"],
    visibility = ["//tensorflow:internal"],
    deps = [
        ":c_api",
        ":c_api_experimental",
        ":c_api_test_util",