TF_Function* function,
                                                  TF_Status* status);

// Removes a function from the context. Once removed, you can no longer
// TFE_Execute it or TFE_Execute any TFE_Op which has it as an attribute or any
// other function which calls it as an attribute.
TF_CAPI_EXPORT extern void TFE_ContextRemoveFunction(TFE_Context* ctx,

// Creates a new TensorHandle from memory residing in the physical device
// device_name. Takes ownership of the memory, and will call deleter to release
// it after TF no longer needs it or in case of error.
//
// Custom devices must use TFE_NewCustomDeviceTensorHandle instead.
TF_CAPI_EXPORT extern TFE_TensorHandle* TFE_NewTensorHandleFromDeviceMemory(

    for the required packages. Alternatively, use the said
    [tensorflow/build Docker images](https://hub.docker.com/r/tensorflow/build)
    (`tensorflow/tensorflow:devel` and `tensorflow/tensorflow:devel-gpu` are no
    longer supported for) development. Use TF SIG Build Dockerfiles in
    development to avoid installing the packages directly on your system (in
    which case remember to change the directory from `/root` to `/tensorflow`

  gpu_options->set_allow_growth(gpu_memory_allow_growth);

  (*config.mutable_device_count())["CPU"] = num_cpu_devices;

  // TODO(b/113217601): This is needed for EagerContext::runner_ to use a
  // threadpool, so that we avoid the possibility of running the runner_ in the
  // threadpool of GPU event mgr, as that can trigger more callbacks to be
  // scheduled on that same threadpool, causing a deadlock in cases where the