class_docstr: SGDDecoder
class_docstr_tok: ["SGDDecoder"]
docstr: Returns tensor with negative logits that will be used to mask out unused values for a particular service 
  Args:
      logits: logits whose shape and type will be used to create negative tensor
docstr_tok: ["Returns","tensor","with","negative","logits","that","will","be","used","to","mask","out","unused","values","for","a","particular","service","Args",":","logits",":","logits","whose","shape","and","type","will","be","used","to","create","negative","tensor"]
code: def _get_negative_logits(self, logits):
      """Returns tensor with negative logits that will be used to mask out unused values for a particular service
      Args:
          logits: logits whose shape and type will be used to create negative tensor
      """
      negative_logits = (
          torch.finfo(logits.dtype).max * -0.7
      ) * torch.ones(
          logits.size(), dtype=logits.dtype, device=logits.get_device()
      )
      return negative_logits
  
file_path: NeMo/nemo/collections/nlp/modules/dialogue_state_tracking/sgd_decoder.py
imports: from typing import Dict, Optional
  import torch
  from torch import nn
  from nemo.core.classes import NeuralModule, typecheck
  from nemo.core.neural_types import LogitsType, NeuralType
label_desc: Use image node_id 8 for calling the SGDDecoder obj's underlying member method code with example usage: obj._get_negative_logits(logits) and returns: negative_logits