code: def run_rnn_test(self, rnn, layers, bidir, state_tuple=False):
      for typ in [torch.float, torch.half]:
          x = torch.randn(
              (self.t, self.b, self.h), dtype=typ
          ).requires_grad_()
          hidden_fn = lambda: torch.zeros(
              (layers + (layers * bidir), self.b, self.h), dtype=typ
          )
          if state_tuple:
              hidden = (hidden_fn(), hidden_fn())
          else:
              hidden = hidden_fn()
          output, _ = rnn(x, hidden)
          self.assertEqual(output.type(), HALF)
          output[-1, :, :].float().sum().backward()
          self.assertEqual(x.grad.dtype, x.dtype)
  
imports: import unittest
  from apex import amp
  import random
  import torch
  from torch import nn
  from utils import common_init, HALF
label_desc: Use image node_id 3 for calling the TestRnns obj's underlying member method code with example usage: obj.run_rnn_test(rnn, layers, bidir, state_tuple) without return types