code: def run_transducer_loss(
      self,
      scalar_t,
      fuse_softmax_backward,
      packed_input,
      for_vector_kernel,
  ):
      self.gen_input(scalar_t, for_vector_kernel)
      my_loss = TransducerLoss(
          fuse_softmax_backward=fuse_softmax_backward,
          packed_input=packed_input,
      )
      if not packed_input:
          loss_tst = my_loss(
              x=self.x_tst,
              label=self.y,
              f_len=self.f_len,
              y_len=self.y_len,
              blank_idx=self.blank_idx,
          )
          loss_tst.mean().backward()
          grad_tst = self.x_tst.grad
      else:
          loss_tst = my_loss(
              x=self.x_tst_packed,
              label=self.y,
              f_len=self.f_len,
              y_len=self.y_len,
              blank_idx=self.blank_idx,
              batch_offset=self.batch_offset,
              max_f_len=max(self.f_len),
          )
          loss_tst.mean().backward()
          grad_tst_packed = self.x_tst_packed.grad
          grad_tst = self._unpack(grad_tst_packed)
  
      return loss_tst, grad_tst
  
file_path: apex/apex/contrib/test/transducer/test_transducer_loss.py
imports: import unittest
  import torch
label_desc: Use image node_id 5 for calling the TransducerLossTest obj's underlying member method code with example usage: obj.run_transducer_loss(scalar_t, fuse_softmax_backward, packed_input, for_vector_kernel) and returns: loss_tst,  grad_tst