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",

  TF_Status* status = TF_NewStatus();
  string lib_path =
      tensorflow::GetDataDependencyFilepath(tensorflow::io::JoinPath(
          "tensorflow", "core", "common_runtime", "next_pluggable_device", "c",
          "test_next_pluggable_device_plugin.so"));
  TF_Library* lib = TF_LoadPluggableDeviceLibrary(lib_path.c_str(), status);
  TF_Code code = TF_GetCode(status);
  string status_msg(TF_Message(status));
  TF_DeleteStatus(status);

// These APIs are mainly to facilitate testing and are subject to change.

// Records the op name in the `ForwardOperation`.
Status Reset(AbstractOperation*, const char* op, const char* raw_device_name,
             ForwardOperation*);

// Records the inputs in the `ForwardOperation`.
Status AddInput(AbstractOperation*, AbstractTensorHandle*, ForwardOperation*);
Status AddInputList(AbstractOperation*,

        output->Unref();
      }
      TF_RETURN_IF_ERROR(ctx->RegisterFunction(func));
    }

    AbstractOperationPtr fn_op(ctx->CreateOperation());
    TF_RETURN_IF_ERROR(fn_op->Reset(fn_name, /*raw_device_name=*/nullptr));
    for (auto input : inputs) {
      TF_RETURN_IF_ERROR(fn_op->AddInput(input));
    }
    int retvals = outputs.size() - null_indices.size();
    std::vector<AbstractTensorHandle*> fn_outputs(retvals);

*   The following APIs are not longer experimental:
    `tf.config.list_logical_devices`, `tf.config.list_physical_devices`,
    `tf.config.get_visible_devices`, `tf.config.set_visible_devices`,
    `tf.config.get_logical_device_configuration`,
    `tf.config.set_logical_device_configuration`.
*   `tf.config.experimentalVirtualDeviceConfiguration` has been renamed to

)

# Config setting that is satisfied when CUDA device code should be compiled
# with clang. It does not imply that CUDA support has been enabled.
alias(
    name = "is_cuda_compiler_clang",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_compiler_clang",
        "@local_config_cuda//cuda:TRUE",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled

// 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

    TF_OperationDescription* desc =
        TF_NewOperation(host_graph_, func_name_, func_node_name_);
    for (auto input : inputs) {
      TF_AddInput(desc, input);
    }
    // Set device to CPU because some ops inside the function might not be
    // available on GPU.
    TF_SetDevice(desc, "/cpu:0");
    *op = TF_FinishOperation(desc, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  std::unique_ptr<ParallelTensor> DeviceIDs(TFE_Context* context,
                                            TF_Status* status) const;

  // The number of devices operations run on.
  size_t num_underlying_devices() const { return underlying_devices_.size(); }

  // The devices operations run on.
  const std::vector<std::string>& underlying_devices() const {
    return underlying_devices_;