docstr: Computes the head of the model.
  
  Args:
      backbone_features (Tensor): The backbone features
  
  Returns:
      The output of the model
code: def compute_head(self, backbone_features: Tensor) -> Dict[str, Any]:
      """Computes the head of the model.
  
      Args:
          backbone_features (Tensor): The backbone features
  
      Returns:
          The output of the model
      """
      y_hat = self.head(backbone_features)
      y_hat = self.apply_output_sigmoid_scaling(y_hat)
      return self.pack_output(y_hat, backbone_features)
  
imports: import importlib
  import warnings
  from abc import ABCMeta, abstractmethod
  from functools import partial
  from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
  import numpy
  import pytorch_lightning
  import torch
  import torch.nn
  import torchmetrics
  from omegaconf import DictConfig, OmegaConf
  from pandas import DataFrame
  from torch import Tensor
  from torch.optim import Optimizer
  from pytorch_tabular.models.common.heads import blocks
  from pytorch_tabular.models.common.layers import PreEncoded1dLayer
  from pytorch_tabular.utils import get_logger, reset_all_weights
label_desc: Use image node_id 17 for calling the BaseModel obj's underlying member method code with example usage: obj.compute_head(backbone_features) and returns: self