code: def loss(self, outputs, targets):
      if targets is None:
          return None
      return nn.BCEWithLogitsLoss()(outputs, targets.view(-1, 1))
  
file_path: tez/examples/nlp/imdb_sentiment_classification.py
imports: import pandas
  import torch
  import torch.nn
  from sklearn import metrics, model_selection
  from transformers import AutoConfig, AutoModel, AutoTokenizer, get_linear_schedule_with_warmup
  from tez import Tez, TezConfig
  from tez.callbacks import EarlyStopping
label_desc: Use image node_id 3 for calling the IMDBModel obj's underlying member method code with example usage: obj.loss(outputs, targets) and returns: nn, None