code: def predict_proba_on_batch(self, X_batch):
      X_batch = torch.autograd.Variable(torch.cuda.FloatTensor(X_batch))
      outputs = self.forward(X_batch, training=False)
      y_pred_batch = torch.stack(outputs, 1).data.cpu().numpy()[:]
      return y_pred_batch
  
file_path: deepchem/contrib/torch/torch_multitask_classification.py
imports: import torch
  import numpy
  from deepchem.metrics import from_one_hot
  from torch_model import TorchMultitaskModel
label_desc: Use image node_id 6 for calling the TorchMultitaskClassification obj's underlying member method code with example usage: obj.predict_proba_on_batch(X_batch) and returns: y_pred_batch