class_docstr: Output layer for multilabel sequence classification models.
  
  Args:
      outputs (Dict[str, ClassificationOutputLayer]): Output for multilabels
      optional label_weights (Dict[str, int]): Dict of label_names along with the
      weight for label
code: def torchscript_predictions(self):
      scores = [
          o.torchscript_predictions() for o in self.outputs.values()
      ]
      return jit.script(MultiLabelClassificationScores(scores))
  
imports: import functools
  import operator
  from typing import Any, Dict, List, Optional, Tuple
  import torch
  import torch.nn
  from caffe2.python import core
  from pytext.data.tensorizers import Tensorizer
  from pytext.utils.usage import log_class_usage
  from torch import jit
  from .doc_classification_output_layer import ClassificationOutputLayer
  from .output_layer_base import OutputLayerBase
label_desc: Use image node_id 6 for calling the MultiLabelClassificationLayer obj's underlying member method code with example usage: obj.torchscript_predictions() and returns: jit