code: def predict(self, samples):
      output = self.forward(samples, is_train=False)
      return output
  
imports: from copy import deepcopy
  import torch
  import torch.nn.functional
  from lavis.common.registry import registry
  from lavis.common.utils import get_abs_path
  from lavis.models.albef_models import AlbefBase
  from lavis.models.albef_models.albef_outputs import AlbefIntermediateOutput, AlbefOutput
  from lavis.models.base_model import MomentumDistilationMixin
  from lavis.models.med import BertModel
  from lavis.models.vit import VisionTransformerEncoder
  from torch import nn
  from transformers import BertConfig
label_desc: Use image node_id 5 for calling the AlbefNLVR obj's underlying member method code with example usage: obj.predict(samples) and returns: output