code: def softmax_mask(val, mask):
      inf = 1e30
      return -inf * (1 - mask.to(torch.float32)) + val
  
imports: from collections import namedtuple
  from logging import getLogger
  from pathlib import Path
  from typing import List, Tuple, Optional, Dict
  import numpy
  import torch
  from transformers import AutoModelForQuestionAnswering, AutoConfig, AutoModel
  from transformers.data.processors.utils import InputFeatures
  from deeppavlov.core.commands.utils import expand_path
  from deeppavlov.core.common.errors import ConfigError
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.models.torch_model import TorchModel
label_desc: Use image node_id 1 for calling a global function with example usage: softmax_mask(val, mask) and returns: unknown