code: def gen_input(self, scalar_t, for_vector_kernel):
      self.B = 5
      T_min = 23
      T_max = 51
      U_min = 12
      U_max = 25
      V = 16 if for_vector_kernel else 14
      self.blank_idx = V - 1
      device = "cuda"
  
      self.x_tst = torch.randn(
          (self.B, T_max, U_max, V),
          dtype=scalar_t,
          requires_grad=True,
          device=device,
      )
      self.y = torch.randint(
          0,
          self.blank_idx,
          (self.B, U_max - 1),
          dtype=torch.int,
          device=device,
      )
      self.f_len = torch.randint(
          T_min, T_max + 1, (self.B,), dtype=torch.int, device=device
      )
      self.y_len = torch.randint(
          U_min - 1, U_max, (self.B,), dtype=torch.int, device=device
      )
      self.f_len[torch.randint(0, self.B, (1,)).item()] = T_max
      self.y_len[torch.randint(0, self.B, (1,)).item()] = U_max - 1
      self.x_tst_packed, self.batch_offset = self._pack(self.x_tst)
      # Generate reference
      x_ref = self.x_tst.data.clone()
      x_ref.requires_grad = True
      loss_grad = torch.ones(
          x_ref.size(0), dtype=x_ref.dtype, device=x_ref.device
      ) / x_ref.size(0)
      (
          _,
          _,
          self.grad_ref,
          self.loss_ref,
      ) = transducer_ref.transducer_loss_reference(
          x=x_ref,
          label=self.y,
          f_len=self.f_len,
          y_len=self.y_len,
          blank_idx=self.blank_idx,
          loss_grad=loss_grad,
      )
  
file_path: apex/apex/contrib/test/transducer/test_transducer_loss.py
imports: import unittest
  import torch
label_desc: Use image node_id 2 for calling the TransducerLossTest obj's underlying member method code with example usage: obj.gen_input(scalar_t, for_vector_kernel) without return types