code: def backward(ctx, loss_grad):
      (
          x,
          alpha,
          beta,
          f_len,
          y_len,
          label,
          batch_offset,
      ) = ctx.saved_tensors
      x_grad = transducer_loss_cuda.backward(
          x,
          loss_grad,
          alpha,
          beta,
          f_len,
          y_len,
          label,
          batch_offset,
          ctx.max_f_len,
          ctx.blank_idx,
          ctx.opt,
          ctx.fuse_softmax_backward,
          ctx.packed_input,
      )
      if ctx.fuse_softmax_backward == False:
          x_grad = x.backward(x_grad)
      return (
          x_grad,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
          None,
      )
  
file_path: apex/apex/contrib/transducer/transducer.py
imports: import torch
  import transducer_loss_cuda
  import transducer_joint_cuda
label_desc: Use image node_id 2 for calling the TransducerLossFunc obj's underlying member method code with example usage: obj.backward(ctx, loss_grad) and returns: x_grad,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None