class_docstr: Non-autoregressive seq2seq output layer.
class_docstr_tok: ["Non-autoregressive","seq2seq","output","layer","."]
code: def from_config(cls, config: Config, vocab: Vocabulary):
      return cls(
          vocab._vocab,
          create_loss(config.loss, ignore_index=vocab.get_pad_index()),
      )
  
file_path: pytext/pytext/models/seq_models/nar_output_layer.py
imports: from typing import Any, Dict, Tuple, Union
  import torch
  from pytext.config import ConfigBase
  from pytext.config.component import create_loss
  from pytext.data.utils import Vocabulary
  from pytext.loss import NARSamplewiseSequenceLoss, NARSequenceLoss, StructuredLoss
  from pytext.models.output_layers import OutputLayerBase
label_desc: Use image node_id 1 for calling the NARSeq2SeqOutputLayer obj's underlying member method code with example usage: obj.from_config(cls, config, vocab) and returns: cls